The blog post, “The 3 Biggest Software Testing Mistakes” from Daniel Knott focused on highlighting vital mistakes that software testing groups frequently come upon in their testing strategies. I chose this blog post because as we continue to learn different software testing strategies in class I think it was important to highlight some mistakes that could be made as a tester so we can avoid these in the future. 

 The first mistake that Knott highlighted was the mistake of not asking enough questions. When you are working as a tester your first job should be to ask as many questions during the development phase of the product as possible. This will allow you to verify that the product will work as intended for the customer. These questions should be highlighting product features, limitations, etc. The second mistake is trying to automate everything. Automation if done right can be very helpful however there are scenarios where automation can do more harm than good. Knott says that many teams mistakenly aim to automate everything, often driven by those unfamiliar with automation’s true benefits. Some parts of the code that are still in development, may not be ready for automation, while other areas will require detailed quality checks that automation cannot provide. Due to this, a risk assessment and informed questioning should precede test automation while working. Once suitable areas for automation are identified, decisions on the level of automated checks should be made by the team.The third mistake in software testing is reusing the same test data repeatedly. Software testing heavily relies on data such as text, images, or voice, and system configurations. Reusing test data compromises its integrity. The system’s state or configuration may change between tests which could affect results. To effectively test an application, the development team must define and generate appropriate test data. Generating test data can be complex, depending on the system’s intricacy and technologies involved. Ideally, scripts can create test data for specific tests, allowing for deletion or reset afterward. The conclusion of the blog post has Knott describing how mistakes can be good as they are a part of growing as a software tester. The best thing we can do is to be transparent about our mistakes to allow for a culture of learning.

After reading this blog post, I believe that I am now more confident and informed about how a software tester should go about testing strategies. Being able to identify common mistakes will be beneficial so I can avoid doing those mistakes in my own work. I found it interesting the fine line between automation since it can be both beneficial and harmful depending on just what you are working on. This is why as I read it is best to be left to a team decision as automation has its own list of pros and cons.

https://shiftsync.tricentis.com/testing-strategies-methodologies-42/the-3-biggest-software-testing-mistakes-95

From the blog CS@Worcester – Giovanni Casiano – Software Development by Giovanni Casiano and used with permission of the author. All other rights reserved by the author.

For this week’s blog post, I decided to discuss the article “Object-oriented Testing in Software Testing” by Mitali Varatiya. I chose this article because it compliments the object oriented testing topic in the syllabus. This article discusses what object oriented testing is, how you can develop test cases with object oriented testing, how to implement object oriented testing, different techniques with implementing object oriented testing, and challenges associated with the implementation of object oriented testing.

The author first discusses how object oriented testing can be done at multiple levels of a program, for example the algorithmic, class, cluster, and system levels. “Object Oriented testing can be performed at different levels to detect the issues. At the algorithmic level, a single module of every class should be tested. As discussed earlier, testing of classes is the main concern of the Object Oriented program. Every class gets tested as an individual entity at the class level. Generally, programmers who are creating the classes are involved in testing. Test cases for Object-Oriented Testing in Software Testing can be constructed based on the requirement specifications, programming language, and models.” The author then goes on to discuss how, at the class level, testing focuses on the integration of individual classes and their interactions with other classes in the program. “Once class-level testing is done, Cluster level testing will be performed. Cluster-level testing is the integration of individual classes. The main purpose of doing integration testing is to verify the interconnection between classes and how well they perform interclass interactions.” The author also discusses some ways in which object oriented test cases can be developed.

The author states that conventional methods of developing test cases are sufficient for creating object oriented test cases, but there are some features that may be helpful with object oriented testing that might be looked over when using more typical techniques on their own. “The following points should be considered while creating test cases for object-oriented environments. Which class is going to be tested should be mentioned properly within the test cases. What is the purpose of using particular test cases? What external pre-condition needs to be conducted while performing the test case? All the states should be specified for testing.” The author then discusses some of the challenges with implementing object oriented testing.

Some challenges that are associated with implementing object oriented testing as described by the author are the impossibility of dynamic testing, the necessity of different types of testing to be implemented to properly test the program, and the difficulties associated with the implementation of testing for inheritance in object oriented programs.

Article: https://www.scaler.com/topics/software-testing/object-oriented-testing-in-software-testing/

From the blog CS@Worcester – P. McManus Worcester State CS Blog by patrickmcmanus1 and used with permission of the author. All other rights reserved by the author.

As my final Apprenticeship Pattern blog post for my capstone course, I found it fitting to write about the “Share What You Learn” pattern. The idea is fairly simple, if you are gaining knowledge on a topic, you should be able to share that knowledge with others effectively to foster mutual growth, which results in everyone building on their ‘craftsmanship,’ which further results in better products from everyone involved.

We don’t work in a vacuum by ourselves, and so communication is incredibly important. We will always be working on teams of software developers, and even in our personal projects, we are working with information that we are informed about from the entirety of the software development ‘community.’ As such, learning to communicate your ideas and share your knowledge is always great for your team.

Different people have different specializations, and in software development, we have our own specializations and interests within this field, and it is beneficial to not only contribute your expertise to the project you are working on with your team, but also share things about that expertise to get everyone on the same board with what you are doing, and perhaps foster growth in them as people and the project as a whole.

The intersting thing is that you can also learn from others’ specializations and expertise when you are sharing your own, and you can also build on your knowledge from ideas and suggestions that others may make when hearing your ideas. It’s a bounce back and forth.

I think everyone has probably experienced this to some extent, even in small circumstances. As the authors mention, simply knowing one small thing more than another person allows you the opportunity to inform that person about your piece of knowledge, and that fosters growth, no matter how small. I know that, for me, I’ve had multiple people ask me about how to do things when they need reminders or help with assignments or issues that they run into at work, and in that situation, it is beneficial to know how to communicate solutions, suggestions and feedback in a way where everyone stands to gain.

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

In a recent episode of the Python Test Podcast, titled “TDD: Don’t Be Afraid of Test-Driven Development”, developer Chris May shared his journey with Test-Driven Development (TDD).  If you’re a programmer interested in improving your code quality and development process, this blog post offers a summary of the discussion and explores why TDD is a powerful technique.

What is Test-Driven Development?

TDD turns the traditional coding process on its head. Instead of writing a large chunk of code and hoping it works, you start by defining the precise behavior you expect from a piece of code. These expectations are written as tests, and they will initially fail because the code itself doesn’t exist yet.

Key Concepts and Benefits of TDD

The core of TDD is the “Red-Green-Refactor” cycle:

1. Red: Write a failing test that reflects a desired feature or behavior.
2. Green: Write the simplest possible code to make the test pass.
3. Refactor: Improve the code’s design and readability while ensuring all tests continue to pass.

This approach offers several key benefits:

• Improved Code Design: By focusing on functionality first, TDD encourages you to create well-structured, modular code.
• Less Debugging: Catching errors as early as possible through tests greatly reduces time spent troubleshooting complex issues later on.
• Increased Confidence: A comprehensive test suite provides a safety net, allowing you to make code changes with less fear of breaking existing functionality.
• Living Documentation: Tests serve as a clear explanation of how your code is intended to work.

Overcoming Challenges with TDD

As Chris May discussed in the podcast, TDD requires a change in how you think about coding. Here are some common concerns and how to address them:

• “It feels too slow”: It’s true that initially, TDD might seem to slow you down. However, the time saved from reduced debugging and a more solid codebase easily makes up for it in the long run.
• “I don’t know how to write tests”: Learning to write effective tests is a skill in itself. Start simple and leverage online tutorials and resources specific to your programming language.

Resources for Learning TDD

• Books:
  • “Test-Driven Development by Example” by Kent Beck
  • “Growing Object-Oriented Software, Guided by Tests” by Steve Freeman and Nat Pryce
• Online Tutorials: Explore the numerous tutorials and guides tailored to different programming languages.

Conclusion

While it may have a learning curve, Test-Driven Development offers a structured and rewarding approach to software development. By embracing TDD, you can write cleaner, more maintainable, and ultimately more reliable code.

Podcast link: https://podcast.pythontest.com/episodes/76-tdd-don-t-be-afraid-of-test-driven-development-chris-may

From the blog CS@Worcester – Site Title by Iman Kondakciu and used with permission of the author. All other rights reserved by the author.

A Path to Enhanced Development

Code reviews are an essential practice in software development, pivotal not only for error detection but also for fostering an environment of continuous learning and collaboration. When executed effectively, they can significantly enhance both individual skills and organizational efficiency.

The Foundation of Effective Code Reviews

An effective review scrutinizes how the proposed changes integrate with the existing codebase, focusing on clarity, correctness, and adherence to established coding practices. Reviewers should critically evaluate the necessity and implementation of the changes, suggesting more granular modifications if the changes are too expansive.

The Art of Communication

The tone in which feedback is delivered can dramatically influence team dynamics. Constructive feedback should be presented through open-ended questions and thoughtful suggestions rather than direct criticism. This approach encourages a collaborative atmosphere and reduces the likelihood of defensive responses. It is essential to recognize the efforts of developers and maintain an empathetic and supportive tone throughout the review process.

Decision Making in Reviews

The decision to approve changes, request modifications, or leave comments unresolved should be clearly communicated. Reviews should be flexible, allowing for follow-up changes when necessary, with reviewers making themselves available for quick re-assessments to accommodate urgent updates.

From Written Reviews to Direct Conversations

When extensive feedback from a review indicates potential misunderstandings, switching from written comments to direct conversations can be beneficial. This transition can help clarify issues more effectively and expedite the review process, especially in cases of complex or contentious changes.

Navigating Challenges in Remote Reviews

Remote and asynchronous reviews present unique challenges, particularly when reviewers are in different time zones. To mitigate these challenges, it’s advantageous to schedule discussions during overlapping working hours or to utilize video calls, enhancing clarity and collaboration.

Cultivating a Supportive Review Culture

Organizations should strive to create a culture that values thorough and empathetic code reviews, recognizing them as crucial to the development process. Continuous improvement in review practices should be encouraged, and engineers should feel empowered to both contribute to and learn from each review session.

By prioritizing effective communication, thoughtful feedback, and continuous improvement, organizations can make code reviews a cornerstone of development excellence, leading to higher quality software and more productive teams.

Integrating Newcomers through Code Reviews

For new team members, adapting to a new codebase and review process can be daunting. A supportive review culture is crucial in easing this transition. Experienced reviewers should use the initial code reviews to not only evaluate the technical aspects but also to mentor and guide newcomers. By explaining alternative approaches, pointing to coding guidelines, and maintaining a positive tone, reviewers can help new engineers integrate effectively while maintaining high standards. This practice ensures that new developers feel welcomed and supported as they navigate their initial contributions to the team.

Based on this blog link: https://stackoverflow.blog/2019/09/30/how-to-make-good-code-reviews-better/

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