J UNIT 5 TESTING

Recently, I dove into unit testing with JUnit 5 as part of my software development journey. Unit testing helps ensure that individual parts of a program work correctly by writing small, focused tests. JUnit 5 is the framework that is used to write these tests for Java applications, and it makes the process simple and efficient.

The first things first, JUnit 5 uses something called annotations to define test methods. The most important one is @Test, which marks a method as a test case. These methods test small units of code, like individual methods in a class, to make sure they return the expected results.

Here’s a simple example of a test method I wrote to check the area of a rectangle:

import static org.junit.jupiter.api.Assertions.assertEquals;

@Test
void testRectangleArea() {
Rectangle r1 = new Rectangle(2, 3);
int area = r1.getArea();
assertEquals(6, area); // Checking if the area is correct
}

In this case try and write these small test cases to check specific outputs, and if something doesn’t match what you expect, JUnit will let you know right away.

The Structure of a Test Case

There are three simple steps you can follow for each test case:

Assert: Compare the result with what you expect using something called an “assertion.

Arrange: Set up the objects or data you are testing.

Act: Call the method you want to test.

For example, here is another test to check if a rectangle is a square:

@Test
void testRectangleNotSquare() {
Rectangle r1 = new Rectangle(2, 3);
boolean isSquare = r1.isSquare();
assertFalse(isSquare); // Checking if it’s not a square
}

In this case, using assertFalse helps to confirm that the rectangle is not a square.

Common JUnit Assertions

JUnit 5 offers several assertion methods, and I quickly got the hang of using them. Here are a few that I used the most:

  • assertEquals(expected, actual): Checks if two values are equal.
  • assertFalse(condition): Checks if a condition is false.
  • assertTrue(condition): Checks if a condition is true.
  • assertNull(object): Verifies if something is null.

These assertions make it easy to confirm whether a piece of code behaves as expected.

Managing Test Execution

One thing that surprised me was that test methods don’t run in any specific order by default. This means each test should be independent of the others, which encourages better organization. I also learned about lifecycle methods like @BeforeEach and @AfterEach, which allow you to run setup and cleanup code before and after each test case. For example, @BeforeEach can be used to initialize objects before each test:

@BeforeEach
void setup() {
// Code to run before each test
}

In conclusion, Learning unit testing with JUnit 5 has been a great experience. It helps me write reliable code and catch bugs early. By writing small tests and using assertions, I can quickly confirm that my programs work as they should. JUnit 5 makes testing simple, and I look forward to improving my skills even more in the future!

If you’re new to testing like I was, JUnit 5 is definitely a great place to start!

From the blog CS@Worcester – MY_BLOG_ by Serah Matovu and used with permission of the author. All other rights reserved by the author.

On Structuring and Managing Test Cases

 In this post, I’ll be discussing a recent article I came across on the TestRail website, which can be found here. The post interested me because it dives deep into the importance of organizing and managing test cases effectively, a topic that we have been covering closely in class. As someone who does a lot of tests in various stages, this article gave me some good notes about how proper test case management can streamline the testing process and reduce the risk of overlooked issues.

One of the key takeaways from the article was the concept of structuring test cases with clear, concise steps and expected outcomes. This was notable because I’ve often seen situations where poorly written test cases lead to confusion or unnecessary delays. The article emphasized that each test case should be easily understandable, even for someone unfamiliar with the project, which makes a lot of sense. Clear test cases not only make the process smoother for current testers, but they also provide better documentation for future test cycles. I’ve personally benefited from this approach, especially when revisiting a project after some time has passed, well-written test cases make it easier to pick up where I left off, and they can even give hints (though these shouldn’t be needed) as to what the code is intending to do, and where some logical boundaries may exist.

The article also discussed the importance of categorizing test cases based on their purpose—whether they’re functional, regression, or exploratory tests. This structure helps ensure that each test type is executed at the appropriate stage and that nothing gets missed. In my experience, this kind of organization is crucial, particularly for large-scale projects where test cases can easily become scattered. I’ve found that when I categorize my tests according to at least some standard, I’m able to prioritize them better and avoid redundant testing, ultimately saving time and effort. It’s a simple but effective way to maintain focus on what really matters. My personal default is to follow the code chronologically / in the order of execution, as that is what feels most natural to me.

Another point I appreciated was the article’s advice on using test management tools, like TestRail itself, to keep track of test cases, execution results, and bugs. Granted, they are going to try to sell their own software, but it is still notable. Managing test cases manually in a spreadsheet or document can quickly become cumbersome, especially as projects grow, and using a product or software to handle this for you can be very beneficial.

Overall, this article reaffirmed the importance of a well-organized approach to test case management. As I continue testing processes and software, I’ll be more mindful of how I structure, categorize, and track my test cases, ensuring that testing is as efficient and effective as possible.

From the blog Mr. Lancer 987's Blog by Mr. Lancer 987 and used with permission of the author. All other rights reserved by the author.

On Structuring and Managing Test Cases

 In this post, I’ll be discussing a recent article I came across on the TestRail website, which can be found here. The post interested me because it dives deep into the importance of organizing and managing test cases effectively, a topic that we have been covering closely in class. As someone who does a lot of tests in various stages, this article gave me some good notes about how proper test case management can streamline the testing process and reduce the risk of overlooked issues.

One of the key takeaways from the article was the concept of structuring test cases with clear, concise steps and expected outcomes. This was notable because I’ve often seen situations where poorly written test cases lead to confusion or unnecessary delays. The article emphasized that each test case should be easily understandable, even for someone unfamiliar with the project, which makes a lot of sense. Clear test cases not only make the process smoother for current testers, but they also provide better documentation for future test cycles. I’ve personally benefited from this approach, especially when revisiting a project after some time has passed, well-written test cases make it easier to pick up where I left off, and they can even give hints (though these shouldn’t be needed) as to what the code is intending to do, and where some logical boundaries may exist.

The article also discussed the importance of categorizing test cases based on their purpose—whether they’re functional, regression, or exploratory tests. This structure helps ensure that each test type is executed at the appropriate stage and that nothing gets missed. In my experience, this kind of organization is crucial, particularly for large-scale projects where test cases can easily become scattered. I’ve found that when I categorize my tests according to at least some standard, I’m able to prioritize them better and avoid redundant testing, ultimately saving time and effort. It’s a simple but effective way to maintain focus on what really matters. My personal default is to follow the code chronologically / in the order of execution, as that is what feels most natural to me.

Another point I appreciated was the article’s advice on using test management tools, like TestRail itself, to keep track of test cases, execution results, and bugs. Granted, they are going to try to sell their own software, but it is still notable. Managing test cases manually in a spreadsheet or document can quickly become cumbersome, especially as projects grow, and using a product or software to handle this for you can be very beneficial.

Overall, this article reaffirmed the importance of a well-organized approach to test case management. As I continue testing processes and software, I’ll be more mindful of how I structure, categorize, and track my test cases, ensuring that testing is as efficient and effective as possible.

From the blog Mr. Lancer 987's Blog by Mr. Lancer 987 and used with permission of the author. All other rights reserved by the author.

On Structuring and Managing Test Cases

 In this post, I’ll be discussing a recent article I came across on the TestRail website, which can be found here. The post interested me because it dives deep into the importance of organizing and managing test cases effectively, a topic that we have been covering closely in class. As someone who does a lot of tests in various stages, this article gave me some good notes about how proper test case management can streamline the testing process and reduce the risk of overlooked issues.

One of the key takeaways from the article was the concept of structuring test cases with clear, concise steps and expected outcomes. This was notable because I’ve often seen situations where poorly written test cases lead to confusion or unnecessary delays. The article emphasized that each test case should be easily understandable, even for someone unfamiliar with the project, which makes a lot of sense. Clear test cases not only make the process smoother for current testers, but they also provide better documentation for future test cycles. I’ve personally benefited from this approach, especially when revisiting a project after some time has passed, well-written test cases make it easier to pick up where I left off, and they can even give hints (though these shouldn’t be needed) as to what the code is intending to do, and where some logical boundaries may exist.

The article also discussed the importance of categorizing test cases based on their purpose—whether they’re functional, regression, or exploratory tests. This structure helps ensure that each test type is executed at the appropriate stage and that nothing gets missed. In my experience, this kind of organization is crucial, particularly for large-scale projects where test cases can easily become scattered. I’ve found that when I categorize my tests according to at least some standard, I’m able to prioritize them better and avoid redundant testing, ultimately saving time and effort. It’s a simple but effective way to maintain focus on what really matters. My personal default is to follow the code chronologically / in the order of execution, as that is what feels most natural to me.

Another point I appreciated was the article’s advice on using test management tools, like TestRail itself, to keep track of test cases, execution results, and bugs. Granted, they are going to try to sell their own software, but it is still notable. Managing test cases manually in a spreadsheet or document can quickly become cumbersome, especially as projects grow, and using a product or software to handle this for you can be very beneficial.

Overall, this article reaffirmed the importance of a well-organized approach to test case management. As I continue testing processes and software, I’ll be more mindful of how I structure, categorize, and track my test cases, ensuring that testing is as efficient and effective as possible.

From the blog Mr. Lancer 987's Blog by Mr. Lancer 987 and used with permission of the author. All other rights reserved by the author.

On Structuring and Managing Test Cases

 In this post, I’ll be discussing a recent article I came across on the TestRail website, which can be found here. The post interested me because it dives deep into the importance of organizing and managing test cases effectively, a topic that we have been covering closely in class. As someone who does a lot of tests in various stages, this article gave me some good notes about how proper test case management can streamline the testing process and reduce the risk of overlooked issues.

One of the key takeaways from the article was the concept of structuring test cases with clear, concise steps and expected outcomes. This was notable because I’ve often seen situations where poorly written test cases lead to confusion or unnecessary delays. The article emphasized that each test case should be easily understandable, even for someone unfamiliar with the project, which makes a lot of sense. Clear test cases not only make the process smoother for current testers, but they also provide better documentation for future test cycles. I’ve personally benefited from this approach, especially when revisiting a project after some time has passed, well-written test cases make it easier to pick up where I left off, and they can even give hints (though these shouldn’t be needed) as to what the code is intending to do, and where some logical boundaries may exist.

The article also discussed the importance of categorizing test cases based on their purpose—whether they’re functional, regression, or exploratory tests. This structure helps ensure that each test type is executed at the appropriate stage and that nothing gets missed. In my experience, this kind of organization is crucial, particularly for large-scale projects where test cases can easily become scattered. I’ve found that when I categorize my tests according to at least some standard, I’m able to prioritize them better and avoid redundant testing, ultimately saving time and effort. It’s a simple but effective way to maintain focus on what really matters. My personal default is to follow the code chronologically / in the order of execution, as that is what feels most natural to me.

Another point I appreciated was the article’s advice on using test management tools, like TestRail itself, to keep track of test cases, execution results, and bugs. Granted, they are going to try to sell their own software, but it is still notable. Managing test cases manually in a spreadsheet or document can quickly become cumbersome, especially as projects grow, and using a product or software to handle this for you can be very beneficial.

Overall, this article reaffirmed the importance of a well-organized approach to test case management. As I continue testing processes and software, I’ll be more mindful of how I structure, categorize, and track my test cases, ensuring that testing is as efficient and effective as possible.

From the blog Mr. Lancer 987's Blog by Mr. Lancer 987 and used with permission of the author. All other rights reserved by the author.

On Structuring and Managing Test Cases

 In this post, I’ll be discussing a recent article I came across on the TestRail website, which can be found here. The post interested me because it dives deep into the importance of organizing and managing test cases effectively, a topic that we have been covering closely in class. As someone who does a lot of tests in various stages, this article gave me some good notes about how proper test case management can streamline the testing process and reduce the risk of overlooked issues.

One of the key takeaways from the article was the concept of structuring test cases with clear, concise steps and expected outcomes. This was notable because I’ve often seen situations where poorly written test cases lead to confusion or unnecessary delays. The article emphasized that each test case should be easily understandable, even for someone unfamiliar with the project, which makes a lot of sense. Clear test cases not only make the process smoother for current testers, but they also provide better documentation for future test cycles. I’ve personally benefited from this approach, especially when revisiting a project after some time has passed, well-written test cases make it easier to pick up where I left off, and they can even give hints (though these shouldn’t be needed) as to what the code is intending to do, and where some logical boundaries may exist.

The article also discussed the importance of categorizing test cases based on their purpose—whether they’re functional, regression, or exploratory tests. This structure helps ensure that each test type is executed at the appropriate stage and that nothing gets missed. In my experience, this kind of organization is crucial, particularly for large-scale projects where test cases can easily become scattered. I’ve found that when I categorize my tests according to at least some standard, I’m able to prioritize them better and avoid redundant testing, ultimately saving time and effort. It’s a simple but effective way to maintain focus on what really matters. My personal default is to follow the code chronologically / in the order of execution, as that is what feels most natural to me.

Another point I appreciated was the article’s advice on using test management tools, like TestRail itself, to keep track of test cases, execution results, and bugs. Granted, they are going to try to sell their own software, but it is still notable. Managing test cases manually in a spreadsheet or document can quickly become cumbersome, especially as projects grow, and using a product or software to handle this for you can be very beneficial.

Overall, this article reaffirmed the importance of a well-organized approach to test case management. As I continue testing processes and software, I’ll be more mindful of how I structure, categorize, and track my test cases, ensuring that testing is as efficient and effective as possible.

From the blog Mr. Lancer 987's Blog by Mr. Lancer 987 and used with permission of the author. All other rights reserved by the author.

A Beginner’s Guide to Software Quality Assurance and Testing

In today’s fast-paced digital world, software is at the core of nearly everything we do—whether it’s managing bank accounts, connecting with friends, or working from home. With so many people depending on technology, ensuring that the software we use is safe, reliable, and user-friendly is more important than ever. This is where Software Quality Assurance and Testing come in.

What is Software Quality Assurance?

Software Quality Assurance is all about making sure that the software developed by companies meets a certain standard of quality. It’s not just about finding bugs after the software has been built; it involves creating guidelines, processes, and checks to ensure software is being built the right way from the start.

Here’s a simple way to think about it: Software Quality Assurance and Testing is like quality control in a factory. Just as a factory ensures that each product coming off the line meets specific standards, Software Quality Assurance and Testing ensures that software does the same.

Key Functions of Software Quality Assurance and Testing:

  • Process Monitoring: Ensuring that software development follows defined processes and standards.
  • Code Review: Examining the code to catch errors before the software is released.
  • Defect Prevention: Putting measures in place that reduce the chance of defects occurring in the first place.

What is Software Testing?

Testing, on the other hand, comes after the development process. It focuses on checking the actual software product to make sure it works as expected. Think of it like test-driving a car before it hits the market.

Software Testing involves running the software through various scenarios to make sure that everything functions smoothly and no bugs are present. It is crucial because even a small bug can cause significant problems for users, and companies could lose their reputation or customers if their software doesn’t work well.

Types of Software Testing:

  • Manual Testing: Testers use the software like a real user would, performing various actions to check for bugs.
  • Automated Testing: Automated scripts run tests on the software to save time and effort on repetitive tasks.
  • Functional Testing: Ensures the software behaves correctly according to requirements.
  • Performance Testing: Verifies how well the software performs under pressure (for example, when thousands of users are using it at once).
  • Security Testing: Identifies vulnerabilities that could expose users to data breaches or other risks.

Why Software Quality Assurance and Testing Are Important

You may wonder, why go through all this trouble? Well, poor-quality software can lead to disastrous results for both users and companies. Imagine if an e-commerce website crashed during Black Friday sales or a banking app exposed sensitive user data—that’s a nightmare scenario!

Here’s why SQA and Testing are critical:

  1. Minimizing Bugs: Testing catches problems early, so developers can fix them before they impact users.
  2. Improving Security: Testing helps find security holes that hackers could exploit, protecting users from cyber threats.
  3. Enhancing User Experience: Reliable, bug-free software creates a better user experience and increases user satisfaction.
  4. Cost Efficiency: Fixing bugs early is much cheaper than addressing problems after software has been released.
  5. Building Trust: Well-tested software builds trust with users, boosting brand reputation and customer loyalty.

How Software Quality Assurance and Testing Affect Everyday Software

Every time you open an app or visit a website, there’s a good chance that it has gone through rigorous quality assurance and testing processes. From banking apps ensuring secure transactions to streaming platforms delivering smooth experiences, Software Quality Assurance and Testing plays a major role in the seamless digital experiences we enjoy daily.

Even the smallest error—like a slow-loading webpage or a glitchy feature—can ruin the user experience, which is why companies invest heavily in making sure their software is as close to perfect as possible. The result? Fewer complaints, better user retention, and a competitive edge in the marketplace.

The Growing Demand for Quality Software

With the continuous rise of new apps, websites, and technologies, the need for high-quality software is more significant than ever. As businesses shift to digital solutions, software development teams face the challenge of delivering robust, reliable software in increasingly shorter timelines.

This demand for quality, combined with the complexity of modern applications, has led to growing opportunities in the field of Software Quality Assurance and Testing Whether you’re a developer, a project manager, or someone interested in tech, understanding the importance of Software Quality Assurance and Testing and how testing works can be a valuable skill in today’s job market.

Conclusion

Software Quality Assurance and Testing are essential for delivering reliable, secure, and user-friendly products in today’s tech-driven world. From preventing bugs to ensuring smooth performance, these processes ensure that the software we depend on every day works as it should.

As technology continues to evolve, the demand for well-tested, high-quality software will only grow. Whether you’re a tech enthusiast or just someone who relies on apps and websites, Software Quality Assurance and Testing and Testing ensure a safer, smoother digital experience for everyone.

So, next time you use a glitch-free app or enjoy a seamless online shopping experience, you can thank the Software Quality Assurance and Testing and Testing teams working behind the scenes to make it possible!

From the blog CS@Worcester – MY_BLOG_ by Serah Matovu and used with permission of the author. All other rights reserved by the author.

Mastering Software Quality: Path Testing and Decision-Based Testing in Real-World Applications

Introduction (GREAT NEWS!!!!)

Hello everyone, I apologize for the delay in posting this week’s blog. I’ve been balancing a lot lately, but I’m excited to share some great news with you. I recently secured a summer internship at Hanover Insurance Group as an automation developer, and I couldn’t be more thrilled! As I dive into this amazing opportunity, I want most of my projects to focus on solving, exploring, or even just addressing challenges within the insurance industry. That’s why this week’s post on Path Testing and Decision-Based Testing will highlight real-world applications in insurance software. Let’s jump in!

How Proven Testing Techniques Ensure Reliability in Insurance Software Systems

In the insurance industry, software systems play a critical role in managing claims, processing policies, and ensuring compliance. Given the complexity of insurance workflows, robust testing is essential to avoid costly errors and enhance customer satisfaction. Two effective testing methods: Path Testing and Decision-Based Testing, are invaluable in achieving high-quality software. Let’s explore these techniques with simple examples and see how they apply to real-world insurance applications.

What is Path Testing?

Ensuring Every Route in the Code is Tested

Path Testing involves checking all possible execution paths within a program to ensure each one functions as expected. This technique is particularly useful in complex systems where different inputs and scenarios lead to various execution routes.

Example:
Consider an insurance claims processing system where a claim can go through multiple steps:

  1. Eligibility Check: Is the policy active?
  2. Coverage Validation: Does the claim fall under covered incidents?
  3. Fraud Check: Are there any red flags?
  4. Approval Process: Does the claim meet all criteria for approval?

Path Testing would generate test cases to ensure every possible scenario is covered, such as:

  • Active policy, valid coverage, no fraud, claim approved (Success)
  • Inactive policy (Failure)
  • Valid policy but uncovered incident (Failure)
  • Fraud detected (Failure)

What is Decision-Based Testing?

Validating Every Decision Made by the Software

Decision-Based Testing (also known as Branch Testing) focuses on testing each decision point in the code, such as conditional statements and logic branches.

Example:
In the same insurance claims system, the decision to approve or deny a claim might depend on multiple conditions:

 ClaimCheck(isPolicyActive) {
    if (isCoveredIncident) {
        if (!isFraudulent) {
            System.out.println("Claim Approved");
        } else {
            System.out.println("Claim Denied: Fraud Detected");
        }
    } else {
        System.out.println("Claim Denied: Uncovered Incident");
    }
} else {
    System.out.println("Claim Denied: Inactive Policy");
}

Decision-Based Testing would create test cases to cover all possible outcomes:

  • Active policy, covered incident, no fraud (Approved)
  • Active policy, covered incident, fraud detected (Denied)
  • Active policy, uncovered incident (Denied)
  • Inactive policy (Denied)

Real-World Application: Insurance Claims Processing Systems

Why Insurance Software?
Insurance software involves complex business rules and multiple decision points. Errors in these systems can lead to mismanagement of claims, financial losses, or regulatory issues.

How Are These Testing Techniques Used?

  1. Path Testing: Ensures that all possible claim processing scenarios are thoroughly tested, including edge cases like expired policies or unusual claim amounts.
  2. Decision-Based Testing: Validates that all critical decisions, such as fraud detection or policy eligibility, are handled accurately by the system.

Example Scenario:
An insurance company uses a claims management system that automatically processes thousands of claims daily. Path Testing would ensure that every possible claim scenario is tested, while Decision-Based Testing would verify that all decision points, such as flagging a claim for manual review, function correctly.

Key Differences Between Path Testing and Decision-Based Testing

Aspect Path Testing Decision-Based Testing
Focus All possible execution paths Each decision point (branches)
Best For Complex insurance workflows Policy validation and claim decisions
Example Application Claims processing systems Fraud detection and approvals

Conclusion: Delivering Reliable Insurance Software with Strategic Testing

For software engineers working in the insurance industry, combining Path Testing and Decision-Based Testing is crucial. These techniques ensure the software is well-equipped to handle every possible scenario and make accurate decisions in policy and claims management. By implementing these robust testing strategies, insurance companies can boost efficiency, reduce errors, and maintain compliance with regulatory standards.

For further exploration, consider:

Software-testing-laboon-ebook

From the blog Rick’s Software Journal by RickDjouwe1 and used with permission of the author. All other rights reserved by the author.

Equivalence Class Testing

In the realm of software testing, equivalence class testing stands out as an efficient black-box testing technique. Unlike its counterparts—boundary value analysis, worst-case testing, and robust case testing—equivalence class testing excels in both time efficiency and precision. This methodology logically divides input and output into distinct classes, enabling comprehensive risk identification.

To illustrate its effectiveness, consider the next-date problem. Given a day in the format of day-month-year, the task is to determine the next date while performing boundary value analysis and equivalence class testing. The conditions for this problem are:

  • Day (D): 1 < Day < 31
  • Month (M): 1 < Month < 12
  • Year (Y): 1800 < Year < 2048

Boundary Value Analysis

Boundary value analysis generates 13 test cases by applying the formula:

No. of test cases(n = no. of variables)=4n+1\text{No. of test cases} (n \text{ = no. of variables}) = 4n + 1

For instance, the test cases might include:

  1. Date: 1-6-2000, Expected Output: 2-6-2000
  2. Date: 31-6-2000, Expected Output: Invalid Date
  3. Date: 15-6-2048, Expected Output: 16-6-2048

While this technique effectively captures boundary conditions, it often overlooks special cases like leap years and the varying days in February.

Equivalence Class Testing

Equivalence class testing addresses this gap by creating distinct input classes:

  • Day (D): 1-28, 29, 30, 31
  • Month (M): 30-day months, 31-day months, February
  • Year (Y): Leap year, Normal year

With these classes, the technique identifies robust test cases for each partition. For example:

  • Date: 29-2-2004 (Leap Year), Expected Output: 1-3-2004
  • Date: 29-2-2003 (Non-Leap Year), Expected Output: Invalid Date
  • Date: 30-4-2004, Expected Output: 1-5-2004

This approach ensures comprehensive test coverage, capturing edge cases missed by boundary value analysis.

Conclusion

Equivalence class testing offers a systematic approach to software testing, ensuring efficient and thorough risk assessment. By logically partitioning inputs and outputs, it creates robust test cases that address a wide array of scenarios. Whether dealing with complex date calculations or other software functions, equivalence class testing is a valuable tool in any tester’s arsenal.

In essence, this method not only saves time but also enhances the precision of test cases, making it an indispensable step in the software development lifecycle.

All of this can be found from this link:

Equivalence Class Testing- Next date problem – GeeksforGeeks

From the blog CS@Worcester – aRomeoDev by aromeo4f978d012d4 and used with permission of the author. All other rights reserved by the author.

Software Quality

Software quality is something that I discuss with a lot of my friends who are also interested in software engineering/developing. One of the main points that all of us make sure to implement in our projects is always clean and readable code. When working on each others code-bases, it has become so much easier when our style’s have become more similar in terms of quality and cleanness, obviously not everyone will have the same style of coding, but people should definitely follow certain guidelines when working on a product.

For the start of all of my projects now, I immediately make the layout in a specific way so that anyone who has to view or navigate the project will know exactly where to look. All packages written will be descriptive enough of what they will contain, all classes will have proper name cases as well, if it creates something it will usually be a factory, if its an object class, its a wrapper, and for core functionality we use services. There have been plenty of times where I’ve had to work on someone else’s code-base and I was immediately lost, everything was all over the place, packages didn’t have good naming conventions, classes didn’t belong to their own packages, even the code itself was just nasty.

This leads me to the next part of software quality, which is usually the most important part, code quality. If you’re coding and you use some obscure or weird naming conventions, that should probably stop. Working in production usually means someone else will eventually have to take a look at your work, and if they can’t even figure out what you were doing, that means you did a terrible job. Everything needs to be readable, now obviously someone may not initially understand what the code does, but that may just be a difference in experience, if someone at your skill level reads your code, they should be able to identify what each variable, method, class, ETC… does for the product and how they cant test it to make sure it all works.

Since I started learning more about code quality, making any sort of project for production has become way more optimized for myself. I’m thankful that I had friends there to help me understand where I was going wrong in the first place with poorly structured code. Instead of having to take time remembering how a project should look, its not basically ingrained in my head how to do, which I hope other developers do as well.

From the blog CS@Worcester – CS Blog by Mike and used with permission of the author. All other rights reserved by the author.