Hello everyone,

For this week’s blog topic I will talk about JUnit, what it is, the importance of it, why it is used, the features that it offers and many more. First to start everything, what is even JUnit. So JUnit is an open source testing framework for Java and it allows programmers to write and then run automated tests. It is very useful to catch bugs early in the development when they are the least expensive to fix. Some of the key features that JUnit has to offer are its powerful testing abilities. It has easy and simple annotation, making writing down the tests even easier. It is intuitive and with just a few practices anyone can get the hang of it. Similar to the Happy Path Tests learnt with behavioral testing, JUnit encourages those normal operations first to be tested. It also supports negative cases and also boundary tests. The blog that I read was really useful as not only it explained what JUnit is but also recommended some good practices for new programmers. For example they advised to test one behavior at a time. This is important as you wanna test a single aspect of the code then move into the other parts of it. You should also use descriptive test names. This is helpful as a clear name can explain directly what you are trying to test for, eliminating confusion and possibly the chance of writing the same test twice. Another good advice given from the author of the blog is that you need to write tests which are independent. This means that different tests should not depend on each other’s results in order for them to run correctly. Lastly, you should always try to test the edge cases. Testing the boundary conditions of the code and also unexpected inputs. Your project should be ready for anything to handle even if an input does not make sense, it should be able to handle correctly and guide the user in the right path. The blog also gives a detailed tutorial on how to not only install JUnit, giving step by step instructions with examples included but also teaches us how to perform automated testing and even in the cloud. At the end of the blog it even offers a FAQ section, clearing any bit of confusion that readers might have. This is a great blog that I recommend everyone to read. It is useful for all ranges of programmers, from beginners to more experienced ones.

In conclusion JUnit Testing is a fundamental skill to learn if you wanna become a great Java Developer. It helps you verify how your code behaves, helps you catch and fix any bugs that might come up at any time of the project development time. Mastering JUnit will not only improve your code quality but also it will give you a boost of confidence when you make any changes, knowing that JUnit will be there for you to catch any bugs. 

Source:
https://testgrid.io/blog/junit-testing/

From the blog Elio's Blog by Elio Ngjelo and used with permission of the author. All other rights reserved by the author.

article https://www.browserstack.com/guide/static-software-testing-tools

This blog will focus on static testing. Static testing is the inspection of a code  program  without  execution. Static testing is an  early stage of creating a program, where a program is being developed, and code can be adjusted before the final product. A program’s files being reviewed before its release saves a company money, without the program being reworked. Review analysis and static analysis are two different methods for static testing. Informal review is a type of review analysis where team members provide code feedback, while static code analysis for static analysis uses software tools to detect coding errors. Static testing is used  multiple times in  coding a program. When a project is first assigned whether in a professional or academic setting, programmers need to understand the requirements of their projects. Usually after  instructions have been reviewed, coding would be the next step, but  static testing adds an extra step of  checking if  a program has the  documents used for  coding. Throughout the development of a program, a common practice is running the program, whether with unit testing or running a whole program, for a programmer  to know if the program is error free. Static testing at the coding stage can either be feedback from team members, or  different software tools such as Soot and checkstyle. BrowserStack Code Quality tool is one software tool for static testing. In my programming experience, I am used to  having to manually fix my errors. This past week, I was introduced to new visual studio code  software tools for coding errors. BrowserStack Code Quality tool is one tool of automated stack testing, where static testing is done through software tools. 

BrowserStack Code Quality has an assistant that recommends how large classes in a program can be split into smaller classes. BrowserStack Code Quality can be downloaded in either Android studio, Vscode, or Intellij, with a quick program scan with feedback. Another software tool is Checkstyle which only works with Java. Developers using Checkstyle  learn about  errors when writing code, compared to after a program has executed. Developers who are using Checkstyle can create coding  conditions, and  a program is checked for following defined coding conditions. Recently, I learned how to use PMD in Visual Studio Code. PMD  detects logical errors in code such as uninitialized variables, unused code. PMD has a copy paste detector that identifies duplicated code. PMD supports more than 10 different programming languages.

From the blog jonathan's computer journey by Jonathan Mujjumbi and used with permission of the author. All other rights reserved by the author.

This week I am discussing a blog post titled, “Control Flow Graph In Software Testing” by Medium user Amaralisa. When I read through this post initially, it immediately clicked for me with what we have been studying in class with different path testing types which capture the logic similarly. The comparison between CFGs and a map used to explore the world or get from point A to point B is incredibly useful as it explains the need for having a guide to explain the many execution paths of the program. The writer made the topic easy to understand while still including the technical information that is required to apply these techniques moving forward.

This post helped me see the bigger picture in terms of the flow of a program and how the logic is truly working behind the code we write. It tied directly into what we’ve covered about testing strategies, especially white-box testing, which focuses on knowing the internal logic of the code. The connection between the CFG and how it helps test different code paths felt like a practical application of what we’ve been reading about in our course.

It also made me think about how often bugs or unexpected behavior aren’t because the output is flat-out wrong, but because a certain path the code takes wasn’t anticipated. Seeing how a Control Flow Graph can lay out those paths visually gives me a better sense of how to test and even write code more deliberately. It’s one thing to read through lines of code and think you understand what’s going on, but when you actually map it out, you might catch paths or branches you hadn’t considered before. I could definitely see this helping with debugging too—like, instead of blindly poking around trying to find what’s breaking, I can trace through the flow and pinpoint where things start to fall apart.

I also really liked that the blog didn’t try to overcomplicate anything. It stuck to the fundamentals but still gave enough technical depth that I felt like I could walk away and try it on my own. It gave me the confidence to try using CFGs as a tool not just during testing but also during planning, especially for more complex logic where things can easily go off track.

Moving forward, I am going to spend time practicing using CFGs as a part of my development process to ensure that I am taking advantage of tools that are designed to help. Whether it’s for assignments, personal projects, or even during team collaboration, I think having this extra layer of structure will help catch mistakes early and improve the quality of the final product. It feels like one of those concepts that seems small at first, but it shifts the way you approach programming altogether when applied properly.

From the blog cameronbaron.wordpress.com by cameronbaron and used with permission of the author. All other rights reserved by the author.

This week in class, we did activities based on static testing. We analyzed code with Gradle And Gradle is not a new tool we’re just hearing about, as we’ve worked with it throughout the semester. And since it is an automation tool with a lot of cool features, I took a further look into automation in software development. I wanted to know what the best features were as well as potential drawbacks from using automation. I ended up finding a blog called “Automation in Software Development: Pros, Cons, and Tools.”

What Else can be Automated?

We’ve learned by now that software testing can be automated. But is that it? Absolutely not. There are some other important software processes that can be automated. One of them is CI/CD (Continuous Integration/Continuous Deployment). Automating continuous integration allows changes in code by multiple developers to be continuously integrated into a common version control repository throughout the day, after which tests are run automatically, making sure that newly written code is not interfering with existing codes. Automating continuous deployment results in integrated and tested code in the production phase being released automatically. Releases are quicker due to the automated deployment, and better because every new line of code is tested before even being integrated.

Automation can also be used to monitor and maintain code. There are automation tools that help analyze data, identify issues, and also provide notifications of a deployed software product. With automation, issues can even be resolved automatically. This is really helpful because it drastically reduces time and resources spent trying to correct errors.

Pros

Three of the largest benefits that come with automation are reduction in manual workload, lower development costs, and an increase in software quality. When tasks are automated, developers can use that now-free time to find ways to improve the software. This way, there is a better chance of the software having more advanced features, as well as customers being satisfied with the product. Many errors and defects of a deployed product come from human errors made during the development of the software. This is where automated testing comes in. Testing tools such as Gradle, JUnit, and Selenium were created for this purpose. Automated testing tools provide feedback on code at the snap of a finger compared how long manual testing might take, which as said before, leads to less time and money being spent to rectify errors. Reduced time and cost are two of the most key automation features that persuade businesses to use automation.

Cons

The challenges most faced when implementing automation tend to be: complexity of the tools, financial constraints, and human resistance. Automation tools can be tough for a corporation to set up and some automation tools require skills that a corporation’s employees might not have. So that means they have to be trained to use it, which means more time and money spent. Though the last paragraph mentioned how automation had lower costs, it can be quite expensive when first implemented. From purchasing the required motion control equipment to paying subscription and renewal fees, automation on a large scale seems to only be a realistic option for large companies. The return on investment might not be immediate either. There is also a concern that automation will soon replace human employees. This can create uncertainty and division in the workplace because employees might not know if they are at risk of being let go or not, so they might object to using automation.

Reference

https://www.orientsoftware.com/blog/automation-in-software-development/

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

Software testing is crucial to ensure that the system acts as expected. However, when dealing with complex systems, it can be challenging to test components in isolation since they rely on external systems like databases, APIs, or services. This is where mocking is used, a technique that employs test doubles. Mocking allows developers to simulate the behavior of real objects within a test environment, isolating the components they want to test. This blog post explains what mocking is, how it is applied in unit testing, the categories of test doubles, best practices, and more.

What is Mocking?
Mocking is the act of creating test doubles, which are copies of real objects that behave in pre-defined ways. These fake doubles stand in for actual objects or services and allow the developers to isolate chunks of code. Mocking also allows them to simulate edge cases, mistakes, or specific situations that could be hard to replicate in the real world. For instance, instead of conversing with a database, a developer can use a mock object that mimics database returns. This offers greater control of the testing environment, increases testing speed, and allows finding issues early.

Knowing Test Doubles
It is important to know test doubles to completely comprehend mocking. Test doubles are mock objects that replace actual components of the system for the purpose of testing. Test doubles share the same interface with the actual object but act in a controlled fashion. There are different types of test doubles:

Mocks: Mocks are pre-initialized objects that carry expectations for being called. Mocks are used to force particular interactions, i.e., function calls with specified arguments, to occur while the test runs. When interactions are  not up to expectations, then the test would fail.

Stubs: Stubs do not care about interactions. They simply provide pre-defined responses to method calls so that the test can just go ahead and not worry about the actual component behavior.

Fakes: They are more evolved test doubles with smaller implementations of real components. For example, an in-memory database simulating a live database can be used as a fake to speed up testing without relying on external systems.

Spies: Spies are similar to mocks but are employed to log interactions against an object. You can verify the spy after a test to ensure that the expected methods were invoked with the correct parameters. Unlike mocks, spies will not make the test fail if the interactions are unexpected.

The Role of Mocking in Unit Testing
Unit testing is testing individual pieces, such as functions or methods, in isolation. But most pieces rely on external services, such as databases or APIs. These dependencies add complexity, unpredictability, and outside factors that can get in the way of testing.

Mocking enables developers to test the unit under test in isolation by substituting external dependencies with controlled, fake objects. This ensures that any problems encountered during the test are a result of the code being tested, not the external systems it depends on.

Mocking also makes it easy to test edge cases and error conditions. For example, you can use a mock object to throw an exception or return a given value, so you can see how your code handles these situations. In addition, mocking makes tests faster because it avoids the overhead of invoking real systems like databases or APIs.

Mocking Frameworks: Mockito and Beyond
Various mocking libraries are utilized by programmers in order to craft and manipulate the mocks for unit testing. Among the most commonly used libraries used in the Java community is Mockito. Mockito makes it easy for one to write mock objects, specify their behavior, and confirm interactions in an easy-to-read manner.

Highlights of Mockito include:

Behavior Verification: One can assert that certain methods were called with the right arguments.
Stubbing: Mockito allows you to define return values for mock methods so that various scenarios can be tested.
Argument Matchers: It provides flexible argument matchers for verifying method calls with a range of values.
Other than Mockito, other libraries like JMock, EasyMock, and JUnit 5 can also be used. For Python developers, the unittest.mock module is utilized. In the.NET ecosystem, libraries like Moq and NSubstitute are commonly used. For JavaScript, Sinon.js is the go-to library for mocking, stubbing, and spying.

Best Practices in Mocking
As terrific as mocking is, there is a best-practice way of doing it and having meaningful, sustainable tests. Here are a few rules of thumb to bear in mind:

Mock Only What You Own: Mock only entities you own, such as classes or methods that you have created. Mocking third-party APIs or external dependencies will lead to brittle tests, which will be broken when outer dependencies change.

Keep Mocks Simple: Don’t overcomplicate mocks with too many configurations or behaviors. Simple mocks are more maintainable and understandable.

Avoid Over-Mocking: Over-mocking your tests can make them too implementation-focused. Mock only what’s required for the test, and use real objects when possible.

Assert Behavior, Not Implementation: Tests must assert the system’s behavior is right, not how the system implements the behavior. Focus on asserting the right methods with the right arguments are called, rather than making assertions about how the system works internally.

Use Mocks to Isolate Tests: Use mocks to isolate tests from slow or flaky external dependencies like databases or networks. This results in faster and more deterministic tests.

Clear Teardown and Setup: Ensure that the mocks are created before each test and destroyed thereafter. This results in tests that are repeatable and don’t produce any side effects.

Conclusion
Mocking is an immensely valuable software testing strategy that provides developers with a way to segregate and test separate components isolated from outside dependencies. Through the use of test doubles like mocks, stubs, fakes, and spies, programmers are able to fake out actual conditions, test on the boundary, and make their tests more reliable and quicker. Good practices must be followed, like mock only what you own, keep mocks as plain as possible, and assert behavior and not implementation. Applied in the right way, mocking is a great friend in creating robust, stable, and quality software.

Personal Reflection

I find mocking to be an interesting approach that enables specific and effective testing. In this class, Quality Assurance & Testing, I’ve gained insight into how crucial it is to isolate the units being tested in order to check their functionality in real-world settings. Precisely, I’ve understood how beneficial mocking can be in unit testing in order to enable the isolation of certain interactions and edge cases.

I also believe that, as developers, we tend to over-test or rely too heavily on mocks, especially when working with complex systems. Reflecting back on my own experience, I will keep in mind that getting the balance right, mocking when strictly required and testing behavior, not implementation, is the key to writing meaningful and sustainable tests. This approach helps us ensure that the code is useful and also adjustable when it encounters future changes, which is, after all, what any well-designed testing system is hoping for.

Reference:

What is Mocking? An Introduction to Test Doubles by GeeksforGeeks, Available at: https://www.geeksforgeeks.org/mocking-an-introduction-to-test-doubles/.

From the blog Maria Delia by Maria Delia and used with permission of the author. All other rights reserved by the author.