Software Comparisons

The progressive web apps vs native apps battle intrigues many developers and businesses. So, will progressive web apps (PWAs) replace native apps in the future? What is the difference between PWA and native apps? What are the strengths and weaknesses of PWAs and native apps? Keep reading this blog post to find out. 

According to a report by Statista, smartphone subscriptions worldwide today surpass six billion. This number is predicted to grow further by several hundred million in the next few years. This creates an exciting opportunity for businesses to leverage the power of mobile apps to offer seamless user experiences. However, the last few years have seen rising support for progressive web apps (PWAs), and companies now face a pressing question: should they build a PWA or a native app? 

Also, read: React Native vs Swift: iOS Mobile App Development

Let’s explore the key differences between progressive web apps (PWAs) and native apps and determine which is better in 2024. Let’s get started!

Progressive web apps vs Native apps: What are the differences between PWAs and native apps? 

PWAs are web apps that can work seamlessly on any device, regardless of the platform, be it mobile, desktop, or tablet. PWAs offer a native app-like experience with the convenience of a website. They leverage modern web capabilities like service workers, and web app manifests to deliver a seamless user experience. PWAs can be easily installed on a user’s home screen, allowing them to access the app quickly without the need to go through the app store.

Native apps, on the other hand, are applications that are built specifically for a particular platform, such as iOS or Android. Native apps are installed on a user’s device through an app store, designed to take advantage of the device’s hardware and software capabilities. Native apps are built using specific programming languages and tools native to the platform, making them highly optimized for the platform they run on.

Also, read What Is Best for App Development: Flutter, Dart Language or Something Else?

What are some PWA and native app examples?

Let’s take a look at them below. 

• Twitter Lite: Twitter launched its PWA in 2017 and offered its users web push notifications, an “Add to Homescreen” prompt, and temporary offline browsing. Twitter achieved a 75 percent increase in Tweets sent, a 20 percent reduction in the bounce rate, and a 65 percent increase in pages per session. 
• Flipkart: In 2015, Flipkart launched its PWA and reported a 70 percent increase in conversion rate, a 40 percent increase in re-engagement rate, and increased time spent on site by 3x.
• Starbucks: In 2017, Starbucks launched its PWA and reported a 23 percent increase in order diversity and a 2x increase in their daily active users.
• Pinterest: After launching its PWA, Pinterest noticed a 60 percent increase in core engagements and a 44 percent increase in ad revenue rate.

Let’s look at some successful examples of native apps:

• Instagram: With over 2.3 billion active monthly users, Instagram is the second most-downloaded app globally. This native app allows users to share photos and videos with friends and followers.
• Uber: Uber is a ride-hailing app that allows users to book rides on demand. The annual revenue generated by Uber in 2022 was $31.8 billion, with an 82.62% increase from the previous year.
• Spotify: Spotify is the world’s leading music streaming application, with over 205 million premium subscribers worldwide. The app allows users to listen to their favorite songs and discover new music. 
• Headspace: With 1.32 million downloads worldwide in the fourth quarter of 2022, Headspace is a meditation and mindfulness app that helps users reduce stress and anxiety and is popular for its recognizable animations.

Read, also: Top 3 Databases for iOS Mobile Applications

Progressive web apps pros and cons

Here are the main pros and cons of PWAs you need to keep in mind. 

Pros

• Cost-effective: Progressive web apps require less development time and are easier to maintain, resulting in lower development costs than native apps.
• Fast and responsive: They offer quick loading and a smooth user experience due to the service worker technology that enables offline usage and caching.
• Cross-platform compatibility: PWAs are built using web standards and are accessible on any device or browser, including desktops, mobile, and tablets.
• Lower storage requirements: They take up less space on a device than native apps.
• SEO-friendly: PWA can be indexed by search engines like any other website, which means better visibility on search engine result pages (SERPs).
• Secure: PWAs are secure as they follow HTTPS protocols and transmit encrypted information.

Cons

• Limited access to native device features: Progressive web apps may be unable to access all of the features available on a user’s device, including push notifications, a camera, and an accelerometer.
• Limited discoverability: PWA is not widely available on app stores like Google Play or Apple App Store.
• Security risks: PWAs are vulnerable to cyberattacks and may require additional security measures to protect user data.
• Limited user engagement: Progressive web apps may not have the same engagement as native apps, such as social sharing or user-generated content.

Native apps pros and cons 

Just like PWAs, native apps come with their own pros and cons. They’re as follows. 

Pros

• Fast & efficient: Native apps are faster and more efficient compared to web apps as they are designed specifically for the platform they are running on.
• Better user experience: They offer a better user experience as they can use the features and hardware of the device to their fullest potential.
• High performance: Native apps can be accessed offline, providing better performance and stability.
• Offline mode: They can use push notifications and provide offline data storage.
• Accessible: Native apps can be downloaded from app stores, making it easy for users to discover and install the app.

Cons 

• Slow time to market (TTM):  Native apps require more resources and time to develop, requiring a separate version for each platform.
• Frequent upgrades: Native apps must be updated and maintained separately for each platform.
• Higher cost: The development cost of native apps is higher than web apps.
• Lengthy downloading process: Native apps require users to download and install them, which can be a barrier to entry for some users.

Progressive web apps: Use cases

Let’s quickly look at the use cases of PWAs below.

• Offline Mode: Progressive web apps work offline, making them an ideal choice for users who are traveling or have limited connectivity. The PWA can save the user’s data and allow them to continue using the app without a stable internet connection.
• News and Media: Progressive web apps are an excellent choice for news and media companies that want to offer a fast, responsive mobile experience, such as Forbes, Medium, etc.
• Travel and Hospitality: PWAs can help travel companies offer a fast and reliable booking experience by providing real-time updates on travel information, such as flight status, gate changes, and delays. Some well-known examples include Trivago, Make My Trip, Ola, etc.
• Banking and Finance: PWAs are ideal for banking and finance companies as they can offer users the ability to access their accounts, check balances, and pay bills. Examples include payment systems such as PayPal and Stripe.
• Health and Fitness: Progressive web apps can help health and fitness companies offer an interactive and personalized experience. They can provide users with workout plans, track their progress, and deliver customized tips and advice—for example, Fitbit, Headspace, Nike Training Club, etc.

Native apps: Use cases

And here are the use cases of native apps.

• E-commerce: Native apps are often used for e-commerce businesses, allowing customers to purchase directly from their mobile devices—for example, Amazon, eBay, etc.
• Social media: Popular social media apps like Facebook, Instagram, and Twitter are all native apps, allowing users to easily access and share content on their mobile devices.
• Gaming: Native apps are also commonly used for gaming, with popular titles like Candy Crush, Clash of Clans, and Angry Birds.
• Education: Native apps are also used in education, with many schools and universities providing mobile apps that allow students to access course materials, communicate with instructors, and more. Some popular apps include Duolingo, Minecraft Education Edition, Photomath, etc.
• Productivity: Native apps can also be used for increasing productivity, with popular apps like Microsoft Office, Evernote, and Trello.
• Entertainment: Native apps are often used for entertainment purposes, with streaming services like Netflix, Hulu, and Disney+.

Progressive web apps vs Native apps: Which is better in 2024?

The answer to this question depends on various factors, such as your business goals, the target audience, and the required features. However, let’s look at the key differences between PWAs and native apps to determine which is better in 2024.

• Development cost and time
  One of the primary reasons why businesses are turning towards PWAs is their development cost and time. Building a PWA is generally less expensive than a native app, and the development time is relatively shorter. PWAs are built using web technologies that are already familiar to developers and can be easily deployed to multiple platforms.
• User experience
  Native apps offer a more polished and refined user experience than PWAs. Native apps are designed to take advantage of the hardware and software capabilities of the device, providing a seamless and responsive experience to users. On the other hand, PWAs are limited to the capabilities of the web browser and may not offer the same level of responsiveness as native apps.
• Accessibility
  PWAs are more accessible than native apps, as they can be accessed on any device with a web browser. Native apps, on the other hand, are limited to a particular platform and require users to download and install the app before they can use it. This means that PWAs can reach a wider audience than native apps.
• Maintenance and updates
  Maintaining and updating a PWA is generally easier than a native app. With PWAs, updates can be made on the server side, and users can access the latest version of the app without needing to download and install anything. On the other hand, native apps require users to download and install updates, which can be cumbersome.

Conclusion 

It takes careful planning and assessment of project requirements, resources, and timelines to choose the best technology for building your next mobile application. Both PWAs and native apps have their own pros and cons. You can take your pick based on various factors like product requirements, business goals, and target audience. If a business wants to reach a wider audience and save development costs and time, then PWAs are a better choice. On the other hand, if a business wants to provide a more refined and polished user experience and take advantage of the hardware and software capabilities of the device, native apps are what they need. 

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What is the difference between black box testing vs white box testing? What are common black box testing techniques? What are common white box testing techniques? What are the steps to perform black box testing? What are the different types of white box testing?

Let’s answer all these questions one by one.

What is black box testing?

Black box testing is a testing method wherein the testing team does not know about the internal structure and design of an application. This testing happens by comparing the input value and output value. 

Black box testing focuses on understanding user experience and happens post-completion of software applications or products. 

What are the steps to perform black box testing?

Steps to perform black box testing include…

1. Examine system requirements and specifications
2. Create a positive test scenario to check if the system processes requests correctly
3. Create a negative test scenario to check the system’s capability to identify issues
4. Determine expected outputs for all inputs
5. Construct and execute test cases
6. Compare outputs with inputs
7. Validate the right results and fix persisting issues
   

What is white box testing?

White box testing is a testing method wherein the testing team examines the internal structure and design of an application. With white box testing, the team checks the data flow from input to output. 

White box testing focuses on finding hidden errors and optimizing code for a more efficient software application or product. 

What are the steps to perform white box testing?

Steps to perform white box testing include….

1. Identification of component, feature, or program for testing
2. Mapping all possible paths in a flow chart
3. Integrating user journey, use cases, and technical information in a flow chart
4. Writing test cases to cover each path in the flow chart
5. Testing and checking whether you get the desired outcomes
   
   Related Post: 10 Popular Software Testing Trends in 2024
   

Black box testing vs white box testing: Key differences 

Key differences between black box testing and white box testing

What are some common black box testing techniques?

Common black box testing techniques include …

1. Equivalence partitioning

   Equivalence partitioning divides data into partitions of valid and invalid values wherein the partitions exhibit the same behavior. If a condition of one partition is false, then the condition of the other partition should also be false, and vice-versa.
   
   For example, if you create a software function that accepts 6 digits to verify an OTP, then each partition of that function with six digits should be able to check the value. Also, if you enter more or less than six digits, the function should direct the user to the error page.
   

2. Error guessing

   Yet another popular black box testing technique is error guessing. This technique involves identifying problematic areas of software with common testing questions. There is no specific method of error guessing. The tester must rely on their experience and test cases for other applications.
   
   Some of the common error-guessing questions include…
   
   Null pointer exceptions
   Entering invalid parameters
   Dividing by zero
   Uploading maximum files to test file limit
   Checking buttons without entering values
   Blank space in text fields
   

3. Boundary value analysis
   

   Boundary value analysis is among the necessary black box testing techniques that check boundary values that are prone to error. The tester checks whether the software produces the correct output upon entering the boundary value.

4. State transition testing
   

   State transition testing uses inputs to check for the desired output. The objective of state transition testing is to see if there is a change in the system during the transition from one state to another.
   
   The tester must analyze transition data and design test cases to probe what happens when the system transitions from one state to another and does not give desired outputs.

5. Decision table testing
   

   Decision table testing tests the software system for outcomes produced by different input combinations. By using decision table testing, you can check all the possible conditions necessary for generating the desired output.
   
   
   

   Decision table testing is a popular black box testing technique.

What are some common white box testing techniques?

Common white box testing techniques include …

1. Statement coverage testing

   Statement coverage is code inclusion testing that calculates the number of explanations implemented in the source code of an application. Also, it ensures that all statements in the code run at least once.
   
   By using statement coverage as one of your white box testing techniques, you can eliminate dead code and uncover unused statements.
   
   The formula of statement coverage is as follows:
   
   Number of statements implemented / Total number of statements
   

2. Branch coverage testing

   The next white box testing technique is the branch coverage testing method. In this technique, the tester identifies all conditional and unconditional branches. Also, the tester ensures that each branch has conditional logic and undergoes unit tests.
   
   For example, A, B, and C are conditional branches if the system implements them upon meeting a condition, whereas D can be an unconditional branch that the system executes every time after executing A.
   
   The formula of branch coverage is as follows:
   
   Number of branches implemented / Total number of branches
   

3. Path coverage testing

   Path coverage testing is a structured process that allows the tester to check each line of code. Path testing helps focus on program logic as you can check vital parts of code through cyclomatic complexity and unit tests.
   
   For example, in this code below,
   
   If a > b
   // do something
   Else
   // do nothing
   
   In the above code, the tester will first create a flow diagram by breaking the code into separate statements. After that, the tester will create different paths for outcomes. Finally, the tester will calculate cyclomatic complexity and run a unit test to validate codes.
   
   In the example, the cyclomatic complexity is 2, as a minimum of 2 test cases are necessary to cover all code execution paths.
   
   Related Post: Unit Testing vs Integration Testing: 4 Key Differences Explained

Summary

Black box testing focuses on software behavior, whereas white box testing focuses on the internal functioning of the software. Testers require both testing methods at different stages of product development. 

So, organizations must carefully understand the differences between black box testing and white box testing to choose the best testing method for their applications and software.

Are you looking to hire developers familiar with black-box testing and white-box testing?

Try Turing. 

Turing helps you hire the top 1 percent of developers in 3-5 days. Companies can choose from a pool of 3 million developers with 100+ skills to find a suitable candidate. 

FAQs

1. What are the different types of white box testing?

Different types of white box testing include…

White box penetration testing – In this method, an ethical hacker attacks an application based on knowledge of its code and design.
Unit testing – Unit testing tests all written code to see if it works as expected.
Mutation testing – Mutation testing checks code resilience by making small changes to the code structure.
Integration testing – This method checks integration points in the internal software and external systems.
Static code analysis – This method uses machine learning and predefined patterns to identify issues in static codes.

2. What are the different types of black box testing?

Different types of black box testing include….

Functional testing – Functional testing validates software against functional requirements and specifications.
Non-functional testing – Non-functional testing checks how the system operates rather than the specific functions of the system.
Regression testing – Regression testing checks whether a system behaves differently after updates or code improvements. 

How do you answer the question: what are your strengths and weaknesses? Why do interviewers ask about strengths and weaknesses in a job interview? What are common employee strengths? What are common employee weaknesses?

This blog post will help you answer all of the above questions. 

Why do interviewers ask about strengths and weaknesses?

Every interviewer asks questions to learn about the value you will bring to the organization. So, by asking about your strengths and weaknesses, they try to figure out the following…

• Whether you are conscious of your best qualities and how you apply them at work. 
• Whether you can discuss your shortcomings and how you try to overcome them. 
• Whether your qualities and skills will complement existing team members.

And so, bragging about your strengths while hiding weaknesses can make you appear arrogant. On the other hand, answering such questions correctly gives you a great opportunity to show the interviewer that you’re a self-aware individual. 

Remember, interviewers love honest, humble candidates who know their strengths and are willing to admit their weaknesses. 

How do you talk about your strengths during an interview?

Most applicants wonder how to answer the question: what are your strengths? So don’t worry. You’re not alone. To begin with, ensure you answer the question in a professional manner without boasting or coming off as egocentric. You can even share an engaging story that highlights your strong suits rather than just giving a one-lined, bland answer like: I’m detail-oriented and hard-working. 

Make a list of your personal strengths, or ask a friend to assist you in this process. If you are not aware of your strengths, you can take free online assessments or follow the below-mentioned steps. 

Here are six steps to identify your strengths…

1. Brainstorm: Sit down and list your strengths. Think really hard and aim for at least 10. Take notes of every strength you can think of. You can always make changes to the list later. 
2. Prepare examples: Instead of just mentioning the strength in one word, share an example based on your work experience where you displayed your strength. Scroll down for some examples if you’re unsure how to do this.
3. Be accurate: Make sure to pick the skills you actually have. Refrain from sounding too general. Choose “relationship building” or “persuasive communication” instead of “people skills” or “good communicator.” The latter are often overused.
4. Don’t be too modest: This is not the time to be self-conscious. You need to use this question to show what value you can bring to the company. And so, it is important to practice your answers. If you plan ahead, you will be able to answer the question in a way that feels natural and genuine. 
5. Look for hints in your performance reviews: Go through past performance assessments. Look for the compliments you received from your peers and manager. Go through old emails that praised your work. 
6. Get technical: Several online tools can help you identify your strengths. All you need to do is answer a series of questions to obtain a report that lists your key strengths.

Here are five common strengths and examples of each…

• Leadership skills
  A great example of strength for a job interview is leadership skills. Demonstrating this skill can help you land a key managerial role. You can list instances in your previous company where you guided your peers to do better or spearheaded a project to achieve a goal.
  
  Sample answer: I managed a large marketing team and helped new recruits crack their first assignment by guiding them throughout the project. With the same ad budget allocated to our team as the previous quarter, I was able to increase sales by 30 percent. 
  
  
• Communication skills
  Candidates with good communication skills leave a lasting impression on recruiters. They come across as strong, confident individuals. There are four main types of communication: Verbal, non-verbal, visual, and written. In a job interview, you should be well-prepared to leverage all four. 
  
  Sample answer: As a part of my last role, I communicated with a variety of clients on a day-to-day basis. I made sure to understand their requirements clearly before working on them. I also crosschecked all information before conveying it ahead. In addition, I ensured there were no communication silos in the team by promoting transparency. 
  
  
• Dedication
  Dedication and commitment are important traits that can help candidates impress recruiters. Candidates who can convince recruiters that they have the hunger for success and give their 110 percent do well in the hiring process.
  
  Sample answer: I am a passionate and disciplined individual who works with dedication and commitment on assigned projects. I take care of every little detail to ensure that the objective we have set out to achieve gets accomplished at all costs.
• Positive attitude  
  Candidates with a positive attitude always look at the bright side and face challenges in a stride. They work toward finding a solution instead of getting stumped. Naturally, such individuals are a great asset to any company. Their optimism keeps the team’s morale high and drives them to do better.
  
  Sample answer: My greatest source of strength is a positive attitude that helps me approach things with a forward-thinking mindset. I look to fix problems instead of crying over their outcome. My seniors in the previous company always praised my optimism and said that it served as motivation for them. 
  
  
• Hard skills
  Along with soft skills, it is equally important to share a few hard skills relevant to the job role as strengths for job interviews. Hard skills are objective, quantifiable skills gained through education, training, or work experiences. Hard skills can often be taught or learned. And so, hard skills can be easily proven — you either know how to write code, or you don’t. 
  
  Sample answer: I am a software developer with 10 years of experience with programming languages like JavaScript, Python, Kotlin, C#, Go, and PHP, among others. I am also well-versed in front-end and back-end frameworks, cloud computing, big data analytics, and microservices architecture. 

Here are a few more examples to answer – What are your greatest strengths?

1. I’ve always picked things quickly. My hunger to keep learning and evolving as a person is one of my key strengths. I work hard to become a better version of myself every day.
2. I am great at interacting with others, working in a variety of teams, and collaborating on a wide range of projects. As the head boy of my school, I encouraged my batch mates to participate in school events to ensure representation. In college, I participated in extracurricular activities with the drama and debate community, volunteered for NGOs, and was also nominated as a campus ambassador for several internships.
3. My ability to relate to people and comprehend their needs is my greatest strength. For example, during one summer internship, I got a call from an angry customer who had been terminated from our service. The company was unable to help her. However, I helped her consider other options and she got really happy with the solution. 

Related post: Ten Tips to Crack a Software Developer Job Interview

How do you talk about your weaknesses?

One of the most dreaded interview questions is: what are your weaknesses? 

Here’s the thing: it’s okay to talk about your weaknesses. All you need to do is find the right balance while doing so. Claiming you have no flaws can make you sound arrogant in the interview. On the other hand, listing down too many can harm your chances of landing a job. 

You must project an air of humility while talking about your weaknesses. At the same time, you must also show a strong willingness to overcome them. For this, you need to identify shortcomings that you’re already working on. Ask a friend or close coworker to help you with this. If you’re still struggling…

Here are three steps to identify your weaknesses…

1. Self-evaluate: Look at your past performance and make a list of the instances where you fell short of expectations. Examine this list to identify patterns. These patterns are can be your weak points.
2. Solicit feedback: Asking for feedback from coworkers or supervisors is one of the best strategies to recognize your professional inadequacies. Your colleagues certainly know your working style better than anybody else and can provide good insights.
3. Review performance metrics: You can examine this qualitative data from your previous performance evaluations to get a better understanding of any weaknesses. 

If the above-mentioned steps do not help, pick some weaknesses and examples from the list below that are most relatable to your personality.

Here are five common weaknesses and examples of each…

• Obsession with small details
  A major weakness for job interviews is the inability to submit projects on time till everything is perfect. Candidates who obsess over the tiniest of details and worry over things not being perfect often miss the big picture. Recruiters want candidates who do not compromise the project in terms of both time and work quality.
  
  Sample answer: My weakness is that I overanalyze my projects and redo them without getting initial client feedback. I am working on this area by sharing my project progress with my colleagues and seniors so that I do not compromise my team’s productivity and project deadlines. 
  
  
• Difficulty saying no
  Candidates who find it difficult to say no can find themselves taking on more work than they can do. Candidates who overwork comprise not only their own but also their team’s work quality. And so recruiters prefer hiring candidates who’re aware of the fine line between dedication and overworking. 
  
  Sample answer: I want to tell you that I find it difficult to say no to my seniors and colleagues. I think I will upset them, and it will negatively affect our professional relationship. However, I am working on this trait as I understand that if I keep doing it, I will suffer from constant burnout and eventually hamper my team’s performance. 
  
  
• Lack of self-awareness
  Self-awareness is essential in giving an honest assessment of one’s skills. Candidates who lack self-awareness can find it difficult to talk about their strengths and weaknesses in job interviews. In contrast, self-aware candidates know their strong suits and shortcomings well.
  
  Sample answer: I did not know that I was bad at integrating code until my previous manager revealed it to me. After that, I took some code integration workshops and attended coding boot camps where they taught code integrations. I am slowly improving and am open to such feedback from my colleagues. 
  
  
• Delegation
  Lack of delegation skills can prove to be a major challenge for employees irrespective of their job position. Candidates who cannot delegate in a timely organized manner need to trust their colleagues more and offer them a chance to learn and grow.
  
  Sample answer: I find it difficult to delegate as I think I am not in control of the project anymore. I have worked hard to get over this mindset and constantly tell myself that it is my duty to help other team members learn from me. Now I am delegating more and more tasks to my colleagues. However, I make sure to go over everything once before sending it ahead.
  
  
• Striking a good work-life balance
  Candidates who fail to strike a good work-life balance start hating their job eventually. After spending all the time at work, candidates can feel depressed and lonely. Such candidates need to organize their tasks and plan their time. So, they can turn one of their weaknesses for job interviews into their strengths.
  
  Sample answer: It was quite difficult to strike a balance between work and my personal life. I used to neglect my family for work and often miss out on important days. After a while, I discussed this with my HR and now I have a new timetable for work which tells me to get out of the office early on specific days.

Here are a few more examples to answer – What are your biggest weaknesses?

1. My tendency to be overly critical of myself is my biggest weakness. Early in my career, I always concentrated on what I wasn’t particularly good at rather than appreciating how far I had gone and how I could improve. I’ve discovered that deliberately seeking out opportunities to reflect and put more of an emphasis on accomplishments while also continuously bettering myself is the greatest method to break this behavior.
2. I strive for perfection. I always look for ways to make things better until I’m satisfied with them, sometimes even going above and beyond. My friends always expressed concern about this habit of mine. I didn’t realize it myself until a college assignment a few years ago. My drive to strive for perfection nearly cost my team the course’s credits. I took that as a lesson and have since made it a point to complete tasks on time, with my best effort, and with a sense of satisfaction.
3. My biggest flaw is that sometimes I deprioritize simple tasks and only work on challenging jobs. However, I’m currently working on this issue. I am learning to prioritize tasks according to submission deadlines. I have also started asking my colleagues and managers to put specific timelines or priority levels for all tasks. 

Related post: Six Common Interview Mistakes Remote Developers Make

List of common strengths and weaknesses

Summary 

To answer questions related to strengths and weaknesses for job interviews, it is important that you are honest with yourself and the interviewer. In addition, you must narrate your personal experiences and tie them with the question that interviewers ask to give a compelling answer that can increase your chance of getting a job. 

Are you looking for software development jobs?

Try Turing. Turing offers remote software developer jobs with unmatched compensation and long-term career growth in top US companies. Visit our jobs page to know more.

FAQs

1. How do you answer what are your strengths and weaknesses for job interviews?
   While discussing your strengths and weaknesses in a job interview, ensure that you narrate personal or professional incidents that made you aware of your strong suits and shortcomings. 

2. What are common employee strengths?
   Some common employee strengths include leadership skills, communication skills, self-motivation, empathy, initiative, and patience, among others. 

3. What are common employee weaknesses?
   Some common employee weaknesses include lack of delegation, insecurity, no self-awareness, lack of confidence, and no knowledge of particular skills, among others. 

Is R better than Python? Is R easier than Python? Why is Python more popular than R? Do most companies use R or Python? Who is the winner in the R vs Python battle? 

Keep reading this blog post to find out.

What is Python?

Python is a high-level, general-purpose programming language. Python focuses on code readability with a decluttered visual layout and simple syntax. Python primarily emphasizes syntactic sugar – a simple, consistent syntax design focusing on keywords instead of punctuations. Dutch programmer Guido Van Rossum released the first version of Python, Python 0.9.0, on 20th February 1991.

Python is flexible, easy to learn, free, and accessible. Python hosts many open-source libraries for data wrangling, processing, and analysis. Programmers prefer Python for its versatility, code efficiency, debugging capabilities, embeddable code, and other sophisticated functionalities.

Related Post: Python for Data Scraping and Data Wrangling

What is R?

R is a programming language and environment for statistical computing and graphics. R is primarily used for statistical computing, data analysis, visualization, and more. Data miners, statisticians, data scientists, and researchers rely on R and its packages for a wide range of applications. R, its libraries, and its user-developed packages host robust features that are very useful for data scientists. 

Statisticians Ross Ihaka and Robert Gentleman developed ‘R’, an open-source programming language, in 1993.

R programming language includes data structures like vectors, arrays, lists, and data frames that define the method of data processing. R also supports an array of arithmetics, graphs, computationally intensive tasks, and a wide range of statistical techniques.

Both R and Python have some unique features, advantages, disadvantages, and individual use cases. They produce different forms of outputs and solve data analysis problems with different methodologies. 

R vs Python for Data Science 

Data science is an interdisciplinary field that applies information from data across a wide range of applications by using scientific methods, procedures, algorithms, and systems to infer knowledge and insights from noisy, structured, and unstructured data. According to some estimates, the market share of data science platforms will surpass $320 billion by 2026. 

People rely on data science to obtain insights from a given data set. The insights help them drive important decisions, devise strategies, plan budgets, and more. Data scientists use programming languages like Python, SQL, C++, Java, R, and Perl for data mining, analysis, cleaning, processing, visualizing, indexing, and organizing.

Python is the most widely used programming language for data science. More than two-thirds of data scientists globally rely on Python. However, R has also surfaced as a popular choice among data experts recently, as it can perform many complicated mathematical and statistical operations seamlessly.

Here is a detailed comparison of R and Python.

R vs Python: Key Differences

R vs Python: Which programming language should you choose?

Choosing the right programming language depends on many factors. Most junior developers prefer Python due to its syntactic sugar. Data scientists prefer R due to its analytical efficiency and progressive functionalities.

Similarly, software developers, web developers, systems administrators, and software engineers prefer Python due to its popularity and expansive range of libraries. Academicians, researchers, scientists, and data engineers prefer the R programming language, as it offers beautiful graphics for data visualization and the capability to process large data sets.

Both of these programming languages are unique in their way and have different applications and use cases. So, consider their popularity, functionality, and modularity to choose one.

Are you a skilled R or Python developer looking for a remote job? Try Turing!

Turing offers long-term, high-paying IS remote software jobs to software developers around the globe. Visit the Apply for Jobs page to learn more.

FAQs

1. Is R better than Python?
   Data analysts who need to process large data sets and visualize them with attractive graphics would prefer R over Python. Junior developers who require basic web scraping, data processing, and scalability prefer Python.
   
   
2. Is R easier than Python? 
   Both R and Python programming languages are easy to learn. However, Python has a better learning curve due to syntactic sugar, i.e., simple keyword-based syntax.
   
   
3. Why is Python more popular than R?
   Python’s simplicity, large repository of libraries and packages, scalability, massive community support, and multi-functional features make Python more popular than R.
   
   
4. Do most companies use R or Python?
   Most big techs, especially MAANG companies, use R and Python in combination for various tasks ranging from data processing and presentation to setting up web servers and web scraping.

Which is better C++ vs Java? Which is more powerful C++ or Java? Should I learn C++ or Java in 2022? Keep reading this blog post to find out.

The choice of the programming language depends on multiple factors, such as its type, complexity, TTM (time to market), scalability, security, and more. Applications written in complex programming languages can be feature-packed, modular, and scalable. However, they require a long time to code. 

Knowing the technical differences between C++ and Java would help developers choose the right programming language for their projects. Let us explore the situations where C++ or Java could be an ideal choice for developers.

What is C++?

Danish scientist Bjarne Stroustrup developed C++ as an extension of C, or ‘C with Classes’ in 1985. C++ is one of the most popular programming languages in the world. Developers use C++ to develop full-fledged software applications and operating systems.

C++ is a multi-paradigm, object-oriented language with low-level memory management. Large-scale organizations like Microsoft, Apple, Facebook, NASA, Google, Amazon, and more heavily rely on C++.

In addition, C++ is a platform-independent programming language, so C++ programs can seamlessly run on many operating systems and interfaces.

What is Java? 

James Gosling, a Canadian computer scientist from Sun Microsystems, developed Java in 1995. Java is an open-source, high-level, general-purpose programming language that is designed to have minimum implementation coupling. Java is a WORA (write once, run anywhere) language that makes Java code compilation easy on all platforms.

Java is simple, reliable, secure, affordable, and portable. Developers use Java to develop applications for gaming consoles, general computers, smartphones, data centers, scientific computers, smartwatches, and more. Google, Airbnb, eBay, Spotify, Slack, Intel, and many other companies use Java for developing web applications.

What is the difference between C++ and Java?

C++ and Java resemble the syntax of C programming language. However, the ecosystems of Java and C++ are very different. C++ code can be called into C, C++ libraries, or API of operating systems. On the other hand, Java code is only ideal for Java-based libraries.

In addition, C++ interacts with hardware more effectively than Java due to its low-level nature and lack of automatic memory management. 

Here are the differences between C++ and Java in detail: 

• Multiple inheritance

  In Object-oriented programming, multiple inheritance is when a child class inherits attributes and methods from a parent class. Java does not support multiple inheritance. However, C++ supports multiple inheritance features.
  
  Multiple inheritance helps create a DSL (domain-specific language), perform advanced calculations during compilation, and improve project type safety.
  

• Code reusability

  For reusing code, both programming languages have generic versions of classes. Java offers generics and C++ hosts templates that work with any data type. C++ templates are more flexible and easy to implement for advanced programming purposes.
  
  C++ compilers can create customized functions or classes whenever different data types come in use. C++ also hosts template specialization, wherein templates can call custom functions. Depending on the type of parameters of top-level functions, particular data types are allowed to have specialized code.
  
  Java does not have template specialization and instead follows ‘type erasure.’ In the type erasure process, Java compilers create generic objects without data types. Type-checking is performed during compilation, but the behavior of a generic class cannot be modified based on its type parameters.
  
  Related Post: Kotlin vs. Java: What Should You Choose for Your Next Project?

• Runtime reflection

  Java developers can view structural details of the Java code during runtime. This feature is ‘reflection,’ and it lets developers view the availability of members in a class/class type.
  
  C++ does not have a full-fledged reflection feature; instead, it offers RTTI or runtime type information. With RTTI, developers can detect specific object types, but they cannot view the object’s members and other similar information.
  

• Memory management

  There are two main approaches to memory management: manual and automatic. For manual memory management, developers must keep track of code, objects, and elements to manually release unused memory.
  
  Java has an automatic memory management system called ‘garbage collection. Java’s garbage collection enables easier memory management and reduces errors caused by releasing memory, thereby reducing security vulnerabilities.
  
  On the other hand, C++ has ‘smart pointers’ that use reference counting for memory management. Destructors in C++ release the allocated memory when an object is removed.
  
  In addition, C++ supports heap allocation and stack allocation, while Java only supports heap allocation. Stack allocation can be faster, safer, and simpler due to the linear data structures of C++. The stack allocation of C++ also supports a programming technique known as RAII (Resource Allocation Is Initialization).
  

• Runtime performance

  C++ outperforms Java, as C++’s manual memory management is faster than Java’s automatic garbage collection. However, Java can also perform better than C++ in some cases with the help of the JIT (Just In Time) compilation.
  
  In addition, the reduced usage of heap allocations in C++ requires less memory and performs better than the garbage collector of Java’s standard memory library. Nevertheless, Java is generally fast and an ideal choice for developing applications unless latency is a top priority.
  

• Build and package management

  Build and package management is how developers build projects and connect external dependencies to the application.
  
  Build and package management affects developer efficiency, project timelines, update management, component tracking, and much more. Maven, a specialized Java tool, can transpose Java code to Integrated Development Environments (IDEs) like IntelliJ IDEA.
  
  Related Post: 7 Best Java IDEs and Editors in 2022
  
  C++ does not have a standard build and package management repository or tool. A few commercial C++ libraries are binary-formatted, which adds to the complexity of the coding process. 

Summary

Your choice of programming language between C++ and Java will depend on the specific requirements of your projects. C++ and Java both have their individual use cases and have certain advantages over each other. Therefore, there is no universal answer to the question of what programming language should be your primary choice between Java and C++.

Java is ideal for software developers who are not well-versed with low-level programming concepts. C++, however, is ideal for software developers who wish to create games, operating systems, desktop applications, embedded systems, and more.

Are you a C++ developer? Do you have experience in building Java-based applications? Are you looking for long-term, high-paying remote jobs at top companies in the US? Try Turing.com!

Turing offers better stability, career growth, and higher compensation for software developers. If you have more than 3 years of experience as a software developer, you should try Turing Jobs. For more information, visit the Apply for Jobs page now.

FAQs

1. Which is better C++ or Java?
   Java is highly modular and performs great on all kinds of platforms. Java is faster with short code execution However, C++ outperforms Java in long code execution.
   
   
2. Which is more powerful C++ or Java?
   C++ is closer to hardware and has better object management, performance, and speed. Thus, C++ is more powerful than Java, especially for compiling and running large applications.
   
   
3. Should I learn C++ or Java in 2022?
   Java is a beginner-friendly language that is ideal for junior developers. C++ has a steeper learning curve than Java.
   
   C++ is the 4th most popular programming language in 2022, with millions of jobs for remote developers. Java is used across various industries like big data, IoT, AI, ML, and more, as major companies are always looking for experienced Java developers. 

What is Node JS? What is the advantage of Adonis? Which is better, NodeJS or ExpressJS? Which is the best JS framework between Adonis and Express? Who wins the Adonis JS vs Express JS battle? 

Keep reading this post to find out.

One of the biggest innovations of the world wide web is the ability to create applications with scalable web servers. However, almost a decade ago, creating web servers was tedious. The most popular web server software – Apache HTTP server, had a lot of limitations.

The Apache HTTP server could not handle 10,000 or more concurrent connections. The sequential programming method for creating Apache code blocked the entire process or required multiple execution stacks. Ryan Dahl solved this bottleneck by creating Node.js – a low-level I/O API, an event loop, and Google’s V8 JavaScript Engine.

What is Node.js? 

Node.js is a back-end JavaScript runtime system that runs on Google’s V8 JavaScript Engine. Node.js executes JavaScript code external to a browser and lets developers write command line tools with JavaScript. Node.js features server-side scripting that produces dynamic web page content before the page loads in the browser. 

Node.js unifies web app development with a single programming language – JavaScript for server-side and client-side scripts. Node.js features an event-driven architecture with asynchronous input/output. Companies like Amazon Web Services (AWS), Microsoft, LinkedIn, IBM, Yahoo!, Walmart, PayPal, Netflix, SAP, GoDaddy, and Rakuten use Node.js.

Node.js frameworks

Node.js frameworks are workspace platforms that support web development with Node.js and use JavaScript for front-end and back-end development. Node.js frameworks can build functions and create unique capabilities for Node.js applications. There are three types of Node.js frameworks: 1) MVC frameworks, 2) Full-stack MVC frameworks, and 3) REST API frameworks.

Related Post: Why and When to Use Node.js? A Brief Guide.

What is an MVC framework?

Model-View-Controller frameworks feature an important design pattern that separates application logic into three parts: models, views, and controllers. The separation makes web development an easy, efficient, and scalable process. 

Express JS and Adonis JS are two of the most popular MVC frameworks based on Node.js.

What is Adonis JS?

Adonis JS is a fully featured back-end framework for Node.js. It creates dynamic data-driven web apps or API servers. Adonis JS can handle HTTP requests, database queries, data validation, user authentication protocols, file transfers, email handling, and a lot more.

Adonis JS is an MVC framework that is based on the Laravel architecture. The concepts of dependency injection are employed with Inversion of Control (IOC). Adonis JS is ideal for developing fast web applications and web-based services that must return JSON responses from a controller.

What is Express JS?

Express JS is a minimalistic Node.js framework with a simple learning curve. A basic understanding of Node.js functionalities is enough to work with Express JS. Companies like Uber, Accenture, IBM, Twitter, Trustpilot, and Stack use Express JS to develop and deploy web applications. 

Express JS features rapid server-side programming packages, template engines, and process managers. The asynchronous programming of Express JS results in better performance, as multiple operations can be executed simultaneously and independently. The simplicity, flexibility, and scalability of Express JS make it a popular choice among other Node.js frameworks.

Adonis JS vs Express JS: What is the difference?

Both of these Node.js frameworks have quite a few differences, unique features, and factors that separate them from each other. Let us learn in-depth about the differences between Adonis JS vs Express JS.

1. Architecture
   

   Adonis JS is a Node.js MVC framework useful for creating scalable web applications. Every Adonis JS project is deployed with a well-defined set of folders and files. So, developers must understand the underlying structure of folders before they start developing with Adonis JS.
   
   Express JS, on the other hand, is very minimalistic and flexible. It can be used with any database, object-relational mapping (ORM), or folder structure. Even junior developers can set up the back-end side of web applications easily and quickly with Express JS.
   

2. Object-Relational Mapping (ORM)
   

   Object-Relational Mapping, or ORM, is a programming technique that uses the object-oriented programming language to create a ‘virtual database’ within the framework. Every framework has its ORM, and the ORM of Adonis JS is ‘Lucid.’ Lucid can quickly build queries, run seeds and factories, create and manage migrations, and hosts data modeling capabilities.
   
   Express JS does not ship with its ORM. Express JS supports many 3rd-party Node.js ORMs like Sequelize, Bookshelf, and Waterline. Developers can also choose to write plain SQL queries or use query builders like knex.js, instead of using a dedicated ORM.
   

3. Routing 
   

   A routing system defines how the application endpoints (URLs) respond to the web client’s requests. The Express Router hosts basic HTTP routing functionalities like app.get( ), app.post( ), and so on. The app.use( ) method route specifies middleware as the callback function.|
   
   Adonis JS hosts robust routing functionalities and allows the developers to bind routes to controllers. The Route.group method enables developers to group multiple routes and configure them instead of re-defining the same properties for every route. Using the Route module, routes are generally defined in the start/routes.ts file.
   
   Related Post: 12 Best Node js Frameworks for 2024
   

4. Authentication
   

   Adonis 5 features an authentication system that greatly reduces the time required for its development. The system supports three types of authentication: basic HTTP authentication, web sessions, and API-based tokens. The support for authentication relies on the @adonisjs/auth package, which relies on the Lucid package.
   
   Express JS does not have its own authentication system. Developers use third-party tools like Okta and integrate them with Express JS to handle user authentication. 
   

5. Performance
   

   The Adonis JS version 5 adds a few micro-optimizations and performance tweaks to the backend framework. Consistent updates of Adonis JS have led to great results with the HTTP server and the validator. Now, the HTTP server is almost on par with the benchmarks of Fastify.js.
   
   Express JS also performs great. However, it does not run as fast as Fastify. Express JS is more popular and stable than Fastify and does not compromise the I/O performance of Node.js.
   

6. Emails
   

   For Adonis JS, the official adonisjs/mail package can send emails from the web application. The package relies internally on the Nodemailer module for transferring emails. The package also supports AWS SES, Mailgun, Sparkpost and SMTP.
   
   The Nodemailer module can also be used with Express JS, but the drivers must be set up manually before the emails deploy. 
   

7. Templates
   

   Adonis JS hosts a templating engine – Edge. Edge can be used to create loops, layouts, components, add conditions, and a few more tasks. Edge can also inspect templates and debug them with a built-in tool. 
   
   Express JS does not have any templating engine. Developers can create their own templating engine with the app.engine(ext, callback) method. Since creating templating engine is very time-consuming, Express supports many external third-party templating engines. 

Adonis JS vs Express JS: Bottomline

Express is essentially a microframework that can be used to quickly build applications with Node.js. Adonis JS, on the other hand, Adonis JS is a full-featured Node.js framework that is Typescript-first. 

Both are exceptional Node.js frameworks and offer great benefits to web developers.   Depending on the requirements, developers can choose either of the two for their web applications. 

Are you a Node.js developer? Do you have 3+ years of experience as a software developer? Are you looking for high-paying remote software developer jobs? Try Turing.

Turing offers long-term, remote software jobs for developers. More than 3 million developers have signed up for Turing jobs. Turing guarantees steady career growth with an opportunity to work for the biggest companies in the U.S.

FAQs

1. What is the advantage of Adonis?
   Adonis is a complete MVC framework in itself. Adonis has many advantages like powerful analytical tools, easy migration, and offers an efficient collaborative environment. It hosts smart BPMN, modeling, and personalized views. AdonisJS is easy to set up and configure with high transparency.
   
   
2. Which is better, NodeJS or ExpressJS?
   ExpressJS is based on NodeJS, so it offers more features. ExpressJS makes it very easy to set up web servers with minimum configurations and has faster setup timelines. ExpressJS can perform the same tasks that NodeJS can; in a faster, efficient, and effortless manner.

Unit testing vs Integration testing, which is better? Can we do integration testing without unit testing? What is the main purpose of integration testing? What are two types of integration testing? What are unit testing tools?

This blog will help you answer all these questions. 

What is unit testing?

Unit testing is the type of testing wherein components or units of a software undergo testing. Unit testing happens during the development phase of the application to ensure that each part of the software performs design-specific functions.

By using unit testing, developers can conclude whether the tested part is ready to use or not. Unit testing isolates a part of the software to check it separately not affecting other parts of the software. Using the isolation technique, developers identify bugs in the early stage of development which keep the cost of fixing bugs low.

Unit testing is the process of checking the code of different software modules.

What is integration testing?

Integration testing is a type of software testing in which the different units, modules or components of a software application are tested as a combined entity. Integration testing ensures that two separate modules work seamlessly together.

By using integration testing, developers can combine different modules of separate software and integrate the modules into an end product. This testing method tests whether the two modules communicate with each other properly. 

Using dummy programs, developers can simulate the missing part of a software module that is not allowing smooth communication. Later they can code that part into the module.

Integration testing is the process of checking whether two software modules work together or not.

Here are the key differences between unit and integration testing.

1. Unit testing vs Integration testing: Team size

   Unit testing does not require a team of developers to check pieces of code. A single developer can easily perform software unit testing.
   
   On the other hand, integration testing requires a team of developers. The team of developers prepares test plans, designs test cases, run multiple tests, and identifies and fixes key issues with system integration testing.
   
   Check out this blog to know 4 Qualities of High Performing Teams.

2. Unit testing vs Integration testing: Code accessibility

   To perform unit testing, code accessibility is necessary as developers need to check the written code.
   
   Unlike unit testing, integration testing does not require code accessibility as developers only need to check the interfaces and module interactions.
   

3. Unit testing vs Integration testing: System-wide issues

   Software unit testing checks software parts and modules for issues. Developers only check the code and software functionality. They do not check any system issues.
   
   System integration testing checks for the connection between two or more modules. By doing this, developers check any system-wide issues that arise from the modules used for integration.
   

4. Unit testing vs Integration testing: Bug detection

   Bug detection in software unit testing is easy as developers check the piece of code, identify the issue, and rewrite the code to fix the issue.
   
   On the other hand, bug detection in system integration testing takes more time as developers need to understand the origin of the bug, find the solution and test the performance of the new approach. 
   
   Other key differences
   
   
   

   Main differences between integration testing and unit testing

What are some of the common unit testing tools?

Some of the common unit testing tools are as follows:

1. Junit: Junit helps conduct unit tests for Java programming language software applications. Junit helps test software data and code and offers assertions for the test method in use.
   
   
2. PHPUnit: PHP programmers can use PHPUnit for software unit testing that allows you to check small pieces of code individually.
   
   
3. JMockit: JMockit is an open-source unit testing tool based on the Java framework. JMockit helps mock objects in testing and uses instrumentation APIs to alter code during runtime. 

Related Post: 7 Popular Open Source Tools to Checkout 

What are the common approaches to integration testing?

Some of the common approaches to integration testing are as follows:

1. Big bang testing
   
   In this testing method, developers combine all the modules of a system as one unit and conduct integration tests. 
   
   
2. Top-down testing
   
   With this method, developers test the modules from top to the bottom. Top-down system integration testing checks the top modules before moving to the lower modules.
   
   
3. Bottom-up testing
   
   This method tests the modules from bottom to top. Bottom-up system integration testing checks the bottom modules before moving to the higher modules. 

Summary

Unit testing determines whether a particular module or part of the software works as per expectation by checking the code. Integration testing, on the other hand, determines whether different modules work together in a software system

Unit testing and integration testing are important stages in the software development cycle. Developers well-versed with unit testing or integration testing can help organizations develop excellent software in an efficient and timely manner.

Are you experienced in the unit or integration testing?

Turing can help you get your dream job. 

Turing offers long-term high paying remote software jobs in top US jobs companies. Visit our Jobs page to know more. 

FAQs

1. What are two types of unit testing?
   
   The two types of unit testing are manual testing and automated testing. Manual unit testing involves writing the code by hand whereas automated unit testing uses prewritten code script to solve common issues.
   
   
2. Is integration testing part of functional testing?
   
   No, integration testing is not a part of functional testing. Integration testing tests different modules for interaction in a system whereas functional testing tests the functionality of all parts of a software application.
   
   
3. What are the steps in integration testing?
   
   The steps in integration testing include preparing the test plan, designing test cases, test scenarios, use cases and scripts, module integration, error detection, bug fixing, and retesting functionalities.

Is Laravel good for big projects? What are the advantages of CodeIgniter? Which is easy to learn, Laravel or CodeIgniter? Is Laravel front-end or back-end? Which is the fastest PHP framework?

This blog will help you answer these questions. 

Developers can choose between CodeIgniter and Laravel as per the project requirement, framework knowledge, use cases, etc. A detailed comparison between these two popular PHP frameworks can help developers make the right choice.

What is Laravel?

Laravel is an open-source PHP framework that helps build robust applications with less code. Based on model-view-controller architecture, the Laravel framework offers an integrated packaging system and a devoted dependency manager. 

Applications built using the Laravel framework are highly scalable and have easy-to-maintain codebases. Laravel features include an extensive library with reusable components, web development tools, command line interfaces, and object-relational mapping, among others. 

What is CodeIgniter?

CodeIgniter is an open-source PHP framework that helps build dynamic, fully functional web pages. CodeIgniter offers a rich set of libraries to perform common and repetitive tasks. CodeIgniter framework uses a simple interface and logical structure to access the set of libraries.

Applications built using CodeIgniter have excellent database and session management. CodeIgniter features include flexible URL routing, full page caching, error logging, and form and data validation, among others.

According to statistics, 119,000 websites are currently using CodeIgniter, whereas 6,45,000 websites are using Laravel. Popular websites built using CodeIgniter include Buffer, The Mail and Guardian, Nissan, and Creditflux. On the other hand, popular websites built using Laravel include Watchseries, Laracast, Alphacoders, and Barchart, among others. 

Now, let’s compare the two.

1. Laravel vs CodeIgniter: Unit Testing

Laravel provides a built-in unit testing feature named PHPUnit. PHPUnit allows developers to check the application code thoroughly.

CodeIgniter does not offer any built-in unit testing support. Developers using the CodeIgniter framework must use third-party unit testing tools to check code quality and application

2. Laravel vs CodeIgniter: Learning Curve

CodeIgniter framework has a shallow learning curve making it easier for developers to learn and practice with CodeIgniter.

Laravel framework has a steep learning curve, with developers taking some time to learn and practice with Laravel.

3. Laravel vs CodeIgniter: Authentication

In CodeIgniter, developers must write custom CodeIgniter extensions for user authentication and authorization.

On the other hand, Laravel offers the authentication class feature to execute authentication and authorization for web applications. 

Related Post: CakePHP vs Laravel: Here’s What You Should Know about These Popular PHP Frameworks

4. Laravel vs CodeIgniter: HTTP routes

By using the Laravel framework, developers can define custom HTTP routes. Developers can also create a specific URL for each HTTP route.

CodeIgniter uses the response and request mechanism to set up HTTP routes. Developers must create paths to facilitate data transmission.

5. Laravel vs CodeIgniter: DBMS support

The Laravel framework offers support for Oracle, IBM, DB2, PostgreSQL OrientDB, JDBC, and MYSQL among others.

CodeIgniter also offers support for the above-mentioned database management systems, excluding IBM and JDBC. Additionally, the CodeIgniter framework supports Microsoft BI and MongoDB.

Check out this post to learn more about MongoDB and its features.

6. Laravel vs CodeIgniter: Modularity features

Laravel provides in-built modules that allow developers to divide parts of a big project into smaller modules. By doing this, developers can work on them separately.

Unlike Laravel, the CodeIgniter framework does not have any in-built modules. Developers must use extensions to create and maintain separate modules.

What are the advantages of Laravel?

The advantages of Laravel include

• Proper documentation
• Integration with mail services 
• Fewer repetitive tasks
• Short product development cycle
• Excellent exceptional handling 
• Smooth database migration
• Cache integration 
• High level of security
• Fast debugging 
• Automated testing 

What are the advantages of CodeIgniter?

The advantages of CodeIgniter include 

• Instant configuration
• Secure platform
• User-friendly interface
• Migration support services 
• Community support
• Test-driven development 
• Error-handling 
• Website customizability 
• Lightweight framework 

Other key differences between Laravel and CodeIgniter 

7 differences between Laravel and CodeIgniter.

Summary

The Laravel framework was launched five years after the CodeIgniter framework. Laravel is an advanced PHP framework that provides seamless updates and integration. In the Laravel vs CodeIgniter battle, Laravel does have the edge over CodeIgniter because of the elegant and advanced features it provides.

However, developers must choose their PHP framework as per the project’s requirements. In addition, they must carefully weigh the pros and cons of each PHP framework to make an informed decision.

Are you an experienced Laravel or CodeIgniter developer looking for a job?

Turing can help.

Turing offers remote software developers long-term jobs with unmatched compensation at top US companies. Visit our Jobs page to know more. 

FAQs 

1. Is Laravel good for big projects?
   Laravel is a flexible PHP framework that offers a wide range of features to successfully implement big projects. 

2. Is Laravel front-end or back-end?
   Laravel is a back-end PHP framework that helps you build modern websites and applications. 

3. Is CodeIgniter easy to learn?
   Yes, CodeIgniter is quite easy to learn for developers. 

GraphQL vs Rest: Is GraphQL better than Rest API? Is there a big difference between GraphQL and Rest API? What are the advantages of the REST API? Is GraphQL good for microservices?

This post will help you answer all these questions. Let’s get started.

Application Programming Interfaces or APIs allow software applications with distinct functions to access data and communicate with operating systems, microservices, and external software components. The four common ways in which APIs communicate are SOAP APIs, Websocket APIs, RPC APIs, and REST APIs. 

REST is an architectural style that helps develop APIs. In the REST API, the client sends server requests as data, and the server returns output data to the client. The client requests are in the form of a URL, and the server response is in plain text instead of a graphical rendering of web pages.

On the other hand, GraphQL is a flexible and efficient data query language that solves common data retrieval problems by integrating APIs. GraphQL requests allow developers to pull data from different sources in a single API call.

Rest API and GraphQL are different methods for data retrieval. This post will take you through both APIs to help you make the right choice. 

What is the REST API?

Representational State Transfer or REST is a popular software architectural style that helps develop web services using a set of constraints. REST, a.k.a. The REST API, provides an easy way of accessing web services using only HTTP requests. The client sends a request to the server as a URL through the REST API. 

The REST request is made up of an HTTP method, endpoint, body, and header. An endpoint contains the uniform resource identifier, headers contain information for caching, authentication, and AB testing, and the body contains information about the request payload.  

There are five common HTTP commands in REST-based architecture, namely GET, POST, PUT, DELETE, and PATCH, for client-server communication. When paired with data, these methods perform CREATE, DELETE, READ and UPDATE operations. 

What is GraphQL?

GraphQL is an open-source data query and manipulation language for APIs. GraphQL is useful for executing queries with existing data. GraphQL can optimize RESTful API calls that offer a declarative way of updating and fetching your data. 

With GraphQL, developers can choose the type of requests to load data from server to client and ask for specific pieces of data. GraphQL is made up of schema, resolve functions and queries. 

GraphQL schema defines the hierarchy of fields and types from data-back stores to describe the shape of data. The GraphQL schema specifies the available queries and mutations for clients to execute. To connect the data to the graph, you must write resolve functions and specify the details in the query to fetch relevant data. 

Here are the key differences between GraphQL and REST API: 

• GraphQL vs Rest API: Usability 

  GraphQL allows you to send a request to your API to get the exact result without requiring any other inclusions. Thus, GraphQL queries return highly predictable results providing excellent usability. GraphQL follows a simple approach and does not version APIs.
  
  The REST API utilizes HTTP and URI methods that make it difficult for the API to predict what will happen while calling a new endpoint. REST does not have standardized guidelines for versioning, allowing providers to use their own approach.
  

• GraphQL vs Rest API: Security 

  REST API uses HTTP, supports Transfer Layer Security encryption, and offers multiple API authentication methods. TLS ensures that the data exchange between two systems is unmodified and private. JavaScript Object Notation (JSON) web tokens complete the HTTP authentication for secure data transfer from web browsers.
  
  The security measures in GraphQL are not as mature as the ones in the REST API. Developers need to come up with authentication and authorization methods while utilizing existing features like data validation in GraphQL.
  

• GraphQL vs REST API: Performance 

  In GraphQL, developers can retrieve data in a single API request. The flexible style defines the structure of information requests and returns the same structure from the server, which prevents data from under-fetching and over-fetching.
  
  Unlike GraphQL, REST APIs have inflexible data structures that can return unwanted data before returning the right information. Developers have to make multiple calls as requests take time to hit the right data and return relevant information. 

Related Post: How to Use Python for Data Scraping and Data Wrangling

What are the advantages of GraphQL? 

• GraphQL queries are executed within the context of particular systems.
• Keeps documentation in sync with APIs.
• Developers do not have to define variables, as GraphQL is statically typed. 
• Product-centric and hierarchical. 
• Useful in caching and query batching.
• Supports rapid application prototyping.
• Offers readable queries. 
• Deals with multiple databases.
• Contains features of the application layer of the OSI model. 
• Enables schema discovery in an appropriate format. 
• Evolution of API without versioning. 
• Reusable fields. 

What are the advantages of the REST API?

• Scales software with ease. 
• Creates explicit process instances. 
• Provides development protocols across projects. 
• Offers several project environments.
• No requirement for routing information for the client machine.
• Developers can build user-specific APIs. 
• Decouples clients and server architectures.
• Supports various data formats like plain text, JSON, and HTML.

GraphQL vs Rest API

Related Post: Top 21 SQL Interview Questions and Answers for 2022

Summary  

Be it designing an API product, or fetching data from different web sources, GraphQL and REST API provide several unique and similar features. REST API is ideal for robust authentication and caching of web services, whereas, GraphQL provides a modern design style and utilizes a single request for fetching data. 

Developers must consider the pros and cons of GraphQL and the REST API along with the project requirements and size to choose the best API. 

Are you an experienced API developer looking for a job?

Try Turing!

Turing helps software developers land their dream remote jobs in top US companies with long-term career growth and unmatched compensation. Visit the Apply for Jobs page to know more!

FAQs

1. Is GraphQL good for microservices?
   GraphQL allows you to model your data into graphs that help multiple applications work together.
    
2. What are the best languages for REST API?
   REST API mainly utilizes XML and JSON for data communication and Ruby on Rails, Python, and JavaScript for programming. 
   
   
3. Is GraphQL scalable?
   Yes, GraphQL is scalable to the extent that each component is independent of one another. 

What is CherryPy used for? Is Flask worth learning in 2022? Which web framework should I learn in Python? Which framework is most used in Python? 

This blog post will help you answer all these questions. Let’s get started. 

Python is one of the most popular programming languages that offer a wide range of web frameworks. Python web frameworks are collections of modules and packages that help developers create web applications and services. Python frameworks are of two types: full stack and non-full stack.

Full stack frameworks provide complete solutions for application development, including form validation, template layouts, and form generators, among others. Popular Python full-stack frameworks include Django, Turbogears, web2py, Cubicweb, Giotto, Grok, Pylons, and more.

On the other hand, non-full stack frameworks help create small applications relying on modules in the Python library. Popular Python non-full stack frameworks include  CherryPy, Flask, Hug, Pyramid, Albatross, Falcon, and more.

What is CherryPy?

CherryPy is a minimalistic Python web framework for web development.

CherryPy is a Pythonic object-oriented programming system that helps developers build fast and reliable web applications. It is one of the oldest Python frameworks. CherryPy enables developers to create a database-driven web application with less source code. This framework offers to create, retrieve, delete and update functions.

What is Flask?

Flask is a popular Python microframework used for web development.

Flask is a lightweight Python microframework that provides essential features like routing, request handling, and more. Flask offers suggestions but does not impose any project layout or dependencies. Developers can choose the tools and libraries they want to use as per the project. This framework features a WSGI toolkit and a Jinja2 template engine.

Here are the key differences between Flask and CherryPy:

1. Flask vs CherryPy: Application security
   
   CherryPy offers built-in features that can help you with security solutions like user authorization, encoding, caching, and more. Additionally, it offers several tools for application testing and debugging.
   
   Flask, on the other hand, allows several security mechanisms that developers can add to Flask applications. This framework includes password hashing, token-based authentication, cross-site scripting, and JSON security. However, developers must set up a content security policy to protect application data while using Flask.
   
   
2. Flask vs CherryPy: Templating engine
   
   Flask’s templating engine Jinja helps developers access both static and dynamic template files. The pre-built Web Server Gateway Interface WSGI toolkit in Flask allows you to receive templating requests from web servers that you can integrate into the final document.
   
   Unlike the Flask framework, CherryPy does not have a templating engine. However, developers can easily integrate different templates like Cheetah, Jinja2, and Mako, among others, into the framework.
   
   
3. Flask vs CherryPy: Libraries and community support
   
   The Flask framework has several external libraries and third-party utilities that you can integrate with your projects. Flask offers rich community support that helps developers resolve any issues that arise during software development.
   
   Similarly, CherryPy is a flexible and highly scalable framework that offers seamless integration with Python libraries and modules. However, the community support for CherryPy is significantly low, meaning developers must resolve the issue on their own.
   
   
4. Flask vs CherryPy: Database support
   
   Flask utilizes Dbadapters to support different databases. Developers can use open-source libraries like Flask-Pony and Flask-SQLAlchemy for object-relational mapping and database support. By utilizing the extensions mentioned above, developers can use open-source libraries like MongoDB, CouchDB, Cassandra, and DynamoDB in Flask.
   
   Similarly, CherryPy does not offer a built-in relational database management system (RDBMS) or built-in SQL support. Developers must use SQLAlchemy to use different plugins and extensions for databases.
   
   
5. Flask vs CherryPy: Testing
   
   The Flask framework provides built-in unit testing support using Python’s unit test framework. The unit testing feature allows developers to test portions of source code that determine the usability for each portion.
   
   Unlike Flask, CherryPy does not provide built-in unit testing support. Developers must rely on modules like Nose and Webtest to test portions of source code.
   
   Related Post: 12 Most Popular Python Frameworks

Comparison between features of CherryPy and Flask.

Unique features and best use scope of CherryPy

CherryPy offers many unique features that include extensibility, scalability, simple syntax, an HTTP server for application hosting, data abstraction, and easy deployment on WSGI-compliant gateways.

CherryPy is ideal for creating Rest APIs with built-in tools and small-scale applications. Developers do not need extensive documentation, resources, and templates to use this framework.

Unique features and best use scope of Flask

Flask offers several unique features like synchronous request processing, extensive documentation, a good routing system, and conventional data storage.

The Flask framework provides high scalability to start-ups and builds simplistic web APIs and large-scale applications with ease. Also, Flask is a great choice for building project prototypes.

Related Post:  Django vs Flask: Which Framework to Choose?

Summary

CherryPy is a minimalistic Python web framework that allows developers to build web applications with cleaner code in less time. On the other hand, Flask is a microframework that allows you to build a high-functioning web application with a sound structure by compiling different Python modules and libraries

In the CherryPy vs Flask battle, Python developers must consider several factors before making a decision. After all, both frameworks offer unique features and are ideal for specific project requirements. 

Are you an experienced Flask or CherryPy developer looking for a job?

Try Turing!

Turing helps software developers land their dream remote jobs in top US companies with long-term career growth and unmatched compensation. Visit the Apply for Jobs page to know more!

FAQs

Is CherryPy a web server?

CherryPy is a web framework that offers a generic HTTP server and production-ready, thread-pooled, high-speed modularized components to develop web applications.

Is Flask a front-end or back-end framework?

Flask is a back-end framework that allows developers to choose tools, libraries, and extensions for their projects.

Which is better, Flask or Django?

Flask is better for small-scale applications, while Django is great for large-scale applications.

Is CakePHP better than Laravel? Is Laravel better than CakePHP? What is the difference between Cake PHP and Laravel? What is CakePHP used for? Is Laravel a coding language? 

This post will help you answer all these questions. 

According to usage statistics, around 6,50,000 websites currently use Laravel, whereas 1,20,000 use CakePHP. Popular websites built using Laravel include Barchart, Alphacoders, Alison, Watchseries, and Laracast. On the other hand, popular websites built using CakePHP are Mapme, Educationunlimited, Eliteperformanceandfitness, Mygasfeed, Followmytv, etc.

Developers can choose between Laravel and CakePHP depending on the project requirement, framework familiarity, and more. A detailed comparison between these two PHP frameworks can help developers choose the best framework for their projects. 

So, let’s find out the key differences between Laravel and CakePHP. 

What is Laravel?

Laravel is an open-source PHP framework that helps create web applications. Laravel offers expressive command-line interfaces, fast web development tools, an extensive library with reusable components, and similar features. 

Developers use Laravel to build robust applications with less code. These applications offer easy-to-maintain codebases and are highly scalable. In addition, Laravel developers use object-relational mapping to access and manipulate databases. 

Laravel is a popular open-source PHP framework.

What is CakePHP?

CakePHP is also an open-source PHP framework that facilitates the efficient development and maintenance of web applications. Cake PHP offers built-in validation, safe request handling, unit testing, business logic support, and other similar features.

Developers can leverage CakePHP’s environment flexibility to build fast web applications. Also, CakePHP provides support for databases like MYSQL, PostgreSQL, SQL Lite, and more.

Now, let’s compare the two.

1. Usage  
   
   Laravel and CakePHP are open-source frameworks. However, Laravel is free to use and operate. In contrast, CakePHP requires a license to operate and use.
   
   Laravel attracts more developers with its free-to-use feature in comparison to CakePHP.
   
   
2. Architecture
   
   Laravel uses MVC architecture. The model-view-controller architecture has three parts: the model, the view, and the controller. The model handles data of the application, the view displays data to the user, the controller interacts with the model for any data queries, and the view for user inputs and then updates the view accordingly. Laravel offers two-way data binding, which helps developers share and update data in different component classes.
   
   CakePHP uses Hierarchical-Model-View-Controller (HMVC) architecture. In the HMVC architecture, different components have separate model-view-controller triads that interact with each other to update the application. By using HMVC architecture, CakePHP reduces dependencies, increases reusability, and makes the application more extensible.
   
   The MVC architecture of Laravel is ideal for enterprise solutions, whereas the HMVC architecture of CakePHP is best suited for small websites.
   
   Related post:  MVC vs. Flux vs. Redux: What Should You Pick?
   
   
3. Templates
   
   Laravel uses Blade, a templating engine, to design unique layouts. Developers can use plain PHP code in blade views to create a consistent design and structure. Blade compiles and caches the views in the resources/view directory for easy accessibility.
   
   Templates in CakePHP are regular PHP files with ctp extensions, using alternative PHP syntax to control output and structures. These templates have the necessary logic to prepare the data sent by the controller into an organized presentation format ready for the user.
   
   Blade in Laravel does not affect the MVC structure, whereas CakePHP templates can affect the HMVC structure.
   
   
4. Object Relational Mapping
   
   Both CakePHP and Laravel use Eloquent ORM for building queries and retrieving data. Developers can organize the database quickly with the help of Eloquent ORM.
   
   However, Laravel offers two ORM options, Query Builder and Eloquent ORM. Both ORMs create bad returns.
   
   CakePHP, on the other hand, doesn’t create any issues during object-relational mapping, ensuring consistent outcomes.
   
   
5. Security
   
   CakePHP offers several advanced security features like hashing, encryption, and decryption. Also, CakePHP restricts actions to SSL, prevents form-tampering, handles blackhole call-backs, and limits cross-controller communication.
   
   However, Laravel only offers basic security features like user authentication, password validation, password reminder and reset protection from cross-site request forgeries, and more.
   
   Hence, CakePHP offers more security features than Laravel.
   
   
6. Testing
   
   Laravel offers two ways to test your application- unit testing and feature testing. Feature testing enables you to test your codebase, whereas unit testing allows you to test your classes, models, and controllers.
   
   CakePHP also offers two types of testing- unit testing and web testing. Unit testing allows you to test small parts of your code, whereas web testing enables you to automate testing for different website components to identify and resolve errors.
   
   Both Laravel and CakePHP offer good testing features. 

Other key differences

Key differences between CakePHP and Laravel

Related post: 10 PHP Frameworks Developers Should Look Out for in 2022 

So, which PHP framework is better, Laravel or CakePHP?

CakePHP allows developers to work in an organized manner without losing flexibility. By using CakePHP, developers do not have to build applications from scratch. 

Laravel offers several features to build robust web applications. By using Laravel, developers can immediately deploy applications. 

Developers must choose between Laravel and CakePHP as per the project requirements and project timeline. In addition, developers must check out the pros and cons of each framework before making their choice. 

Are you an experienced Laravel or CakePHP developer looking for a job?

Try Turing!

Turing helps software developers land their dream remote jobs in top US companies with long-term career growth and unmatched compensation. Visit the Jobs page to know more!

FAQs 

1. Is Laravel back-end or front-end?
   Laravel is a back-end framework that helps build server-side applications with features like order management, user accounts, etc. 
   
   
2. Is CakePHP easy to learn?
   CakePHP is a powerful open-source PHP framework that is easy to learn. 
   
   
3. What is Blade in Laravel?
   The Blade is a templating engine in Laravel that offers unique templates and makes syntax writing easy. 

Kotlin vs Java: Is Kotlin better than Java? Is there a big difference between Kotlin and Java? This blog post will help you answer all these questions. According to a survey, 36 percent of developers use Java compared to eight percent who use Kotlin. Java has been a popular choice for mobile and web applications for the past two decades. On the other hand, Kotlin is Google’s official programming language for developing Android apps.

Java is an object-oriented programming language, whereas Kotlin supports both object-oriented and functional programming. Popular applications developed using the Kotlin language are Netflix, Uber, Tinder, Airbnb, and Pinterest. Similarly, well-known applications developed using Java are Twitter, Spotify, and LinkedIn.

Is Kotlin replacing Java?

Kotlin language is a popular choice for android development. Kotlin has a range of features that make it more accessible and ideal for android development. However, Kotlin cannot replace Java, which is an old programming language used for several projects other than android development. Millions of developers around the world trust Java for their projects. 

Is Kotlin difficult to learn?

Kotlin language is very easy to learn. Developers interested in Kotlin must master the basics first and then learn more about design and syntax capabilities. Developers with Python or Java backgrounds can learn Kotlin faster.

Let’s take a look at the key differences between Java and Kotlin:

1. Kotlin vs Java: Extension functions
   
   In Java, extension functions are not available. Developers need to create a new class and parent class to add this feature.
   
   Kotlin helps developers easily add extension functions in existing classes. Developers must prefix the name of the class and function to enable extension functions.
   
   
2. Kotlin vs Java: Implicit conversion
   
   Implicit type conversion is the conversion of a data type automatically by a compiler. There are seven different data types in Java. Data types of the same kind convert to accommodate smaller data types into larger data types. Thus, java supports implicit conversion.
   
   Kotlin does not support implicit conversion of data types, which means smaller data types do not convert to larger data types.
   
   
3. Kotlin vs Java: Data classes
   
   Kotlin enables the smart creation of data classes. Developers need to declare the class with keyword data. Afterward, the Kotlin compiler creates constructor, getter, and setter methods automatically.
   
   Contrarily, developers need to define the constructor, getter, and setter methods in Java to create data classes.
   
   
4. Kotlin vs Java: Language scripting
   
   Language scripting helps developers execute different functions automatically, which otherwise would require manual operation.
   
   Kotlin enables language scripting integration in existing scripts, whereas Java does not allow language scripting.
   
   
5. Kotlin vs Java: Operator overloading
   
   Operator overloading allows the utilization of the same operator on different user-defined data types. Java doesn’t allow operator overloading except for the + function used for addition and concatenation in numeric and string types.
   
   Kotlin enables the implementation of the pre-defined set of operator types like + and * with precedence. Developers need to specify the member function with the specific name of the corresponding type for the operator modifier to implement overloading.
   
   
6. Kotlin vs Java: Static members
   
   Java uses static members for memory management. Developers can apply static java keywords to different methods, blocks, variables, and nested classes to make them static members. Also, developers can access these members without instantiating the class.
   
   Unlike other programming languages, static members in Kotlin do not use static variables in name fields.  Developers must use Kotlin objects to create a companion object inside the class. Since the companion object is single, it acts as a static member allowing direct access without disturbing the containing class.
   
   
7. Kotlin vs Java: String templates and expressions
   
   String templates are a set of string literals that contain a sequence of characters to display text to a user. In Java, string templates are enclosed within quotation marks but do not allow expressions.
   
   In Kotlin, there are two types of string templates raw strings and escape string templates. Kotlin allows expressions inside strings that can change the output of a pre-written program.
   
   
8. Kotlin vs Java: Smart cast
   
   Smart cast is an exclusive feature of the Kotlin language. Developers can use a smart cast to track the object and variable and then safely cast it into the call methods and types.
   
   Since the smart cast is not available in Java, developers need to perform two separate functions. The first function checks the variable type and the second function casts the object to the target type.
   
   
9. Kotlin vs Java: Type inference
   
   Type inference is a feature that allows the deduction of data types for specific expressions automatically. Java does not allow type inferences as developers need to specify each variable before a declaration.
   
   Kotlin allows type inference so that developers do not have to declare the type of each variable separately.  

A competitive analysis of the remaining features:

Summary

Kotlin is a programming language inspired by Java and developed exclusively for Android development. Developers can get things done with fewer lines of code using the Kotlin language.  However, for developing client-side applications and web applications, developers can choose Java over Kotlin.

In the end, developers should take their pick as per their project’s requirements. They should also list the pros and cons of each language to make an informed decision. 

Are you an experienced Kotlin or Java developer looking for a long-term, high-growth remote job?

Turing can help.

Turing offers remote software developers jobs with unmatched compensation and long-term career growth in top US companies. Visit the Jobs page to know more. 

FAQs 

How is Kotlin different from Java?

Kotlin is an enhanced version of Java. The language improves on Java aspects that previously made Android development time-consuming. Kotlin is faster and can compile code in fewer lines than Java. 

Should I learn Java before learning Kotlin?

Developers who are just starting out must learn Java to code well. Java is one of the oldest programming languages, so understanding Java basics help learn newer programming languages like Kotlin. 

What are the features of Kotlin?

Kotlin has many smart features like smart casts, lazy loading, null safety, and exception handling, among others.