Category Archives: CS-443

Unraveling the Efficiency of Pairwise and Combinatorial Testing in Software Development (Week-11)

In the dynamic landscape of software development, ensuring the reliability and functionality of applications is paramount. Traditional testing methods, while thorough, often require substantial time and resources, prompting the industry to lean towards more efficient strategies. Among these, Pairwise and Combinatorial Testing have emerged as pivotal techniques, providing a balance between testing depth and resource allocation.

Pairwise Testing: A Closer Look

Pairwise testing, a subset of combinatorial testing, operates on a principle that most defects in software are triggered by interactions between pairs of input parameters. This method systematically generates test cases to cover all possible pairs of inputs, significantly reducing the number of tests needed to identify potential bugs. According to Capers Jones, a luminary in software engineering, pairwise testing can detect up to 75% of defects, presenting a compelling case for its adoption (Jones, 2008). This efficiency stems from the recognition that not all input combinations are necessary to uncover the majority of the issues, thus optimizing the testing process.

Combinatorial Testing: Expanding the Horizon

Combinatorial testing extends the concept of pairwise testing by considering interactions among three or more parameters. This technique is particularly beneficial in complex systems where interactions extend beyond simple pairs. While it requires more test cases than pairwise testing, it’s still far less than the exhaustive testing of all possible inputs. The National Institute of Standards and Technology (NIST) has highlighted combinatorial testing’s effectiveness, noting its capability to uncover intricate bugs that pairwise might miss, making it an indispensable tool for ensuring software robustness (Kuhn et al., 2013).

Integrating Pairwise and Combinatorial Testing into Development

The integration of these testing methodologies into the software development lifecycle can significantly enhance the quality assurance process. By identifying the most impactful combinations of parameters, developers can preemptively address issues, leading to more stable releases. Tools such as PICT (Pairwise Independent Combinatorial Testing tool) from Microsoft and Hexawise facilitate the implementation of these strategies, enabling teams to automate test case generation and focus on critical test scenarios.

Conclusion

Pairwise and combinatorial testing represent a paradigm shift in software testing, moving away from exhaustive and resource-intensive methods towards a more strategic approach. By focusing on the interactions that most likely contribute to defects, these methodologies offer a practical pathway to improving software quality without the overhead of traditional testing techniques. As software systems grow in complexity, the adoption of pairwise and combinatorial testing is not just advisable but essential for developers aiming to deliver flawless applications efficiently.

The practicality and effectiveness of these testing strategies underscore a broader trend in software development towards optimization and efficiency. As we continue to push the boundaries of what software can achieve, the methodologies we employ to ensure their reliability must evolve accordingly. Pairwise and combinatorial testing stand at the forefront of modern software quality assurance.

References:

  • Jones, C. (2008). Applied Software Measurement. McGraw-Hill Education.
  • Kuhn, D. R., Kacker, R. N., & Lei, Y. (2013). Introduction to Combinatorial Testing. CRC Press.

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

Intro to Software Testing

Software testing != doing homework bt rather, Software testing == checking homework to make sure it’s done right. In this blog we’ll explore the basics: what testing is, how it’s done, and why it’s important. We’ll cover different ways to test, how deep we go into testing, some smart ways to test, and why testing is worth it. Let’s dive in!

What is Software Testing?

Software testing is the process of verifying and validating whether a software or application is bug-free, meets technical requirements, and satisfies user needs. It ensures that the software functions as expected, identifying errors, faults, or missing requirements in contrast to actual specifications. This process aims to enhance efficiency, accuracy, and usability.

Verification and Validation

  1. Verification: Ensures that the software correctly implements specific functions, answering the question, “Are we building the product right?”
  2. Validation: Confirms that the built software aligns with customer requirements, answering the question, “Are we building the right product?”

Different Types of Software Testing

  1. Functional Testing: Validates whether the software functions according to functional requirements.
  2. Non-functional Testing: Assesses non-functional aspects like performance, scalability, and usability.
  3. Maintenance Testing: Involves modifying and updating software to meet evolving customer needs.

Further, testing can be performed manually or through automation, each with its own set of advantages and applications.

Different Types of Software Testing Techniques

  1. Black Box Testing: Conducted without accessing the source code, focusing on software interface.
  2. White Box Testing: Involves knowledge of internal workings and access to source code.
  3. Grey Box Testing: Blends aspects of both black and white box testing, providing testers with partial knowledge of the internal workings. This approach offers a balanced perspective, allowing for effective testing while maintaining a degree of independence from the code’s intricacies.

Additionally, Grey Box Testing combines elements of both approaches.

Different Levels of Software Testing

  1. Unit Testing: Evaluates individual units or components of the software.
  2. Integration Testing: Tests the interaction between integrated units.
  3. System Testing: Assesses the complete, integrated system or software.
  4. Acceptance Testing: Determines system acceptability based on business requirements.

Each level serves a distinct purpose in ensuring software reliability.

Best Practices for Software Testing

  • Continuous Testing: Test each build as it becomes available to reduce risks and improve functionality.
  • User Involvement: Engage users to understand their needs and perspectives during testing.
  • Test Segmentation: Divide tests into smaller parts for efficient analysis and resource utilization.
  • Metrics and Reporting: Track project metrics and share test results for improved collaboration and decision-making.
  • Regression Testing: Continuously validate the application to maintain its integrity.
  • Avoid Programmer Bias: Programmers should refrain from writing tests to maintain objectivity.
  • Service Virtualization: Simulate systems and services to reduce dependencies and start testing sooner.

Benefits of Software Testing

  • Product Quality: Ensures delivery of high-quality software by detecting and fixing errors early.
  • Customer Satisfaction: Identifies and resolves issues before delivery, enhancing user experience.
  • Cost-effectiveness: Saves time and money by detecting and fixing bugs in early stages.
  • Security: Protects software from internal and external security vulnerabilities.

Sources https://www.geeksforgeeks.org/software-testing-basics/

From the blog CS@Worcester – CS: Start to Finish by mrjfatal and used with permission of the author. All other rights reserved by the author.

Testing Gone Mobile

In another of my classes I am beginning to learn android mobile app development. This gave me a lot of interesting thoughts about how testing might look for mobile app development. As the applications are full-stack applications, and require testing of the back and front ends. I had questions like: “What would testing a front end look like? Simply applying it and clicking around?” and “How might we test back-end functions if they are intrinsically tied to the front-end?”. To find out more I looked on stickyminds, where I find most of my articles. I found an article about Testing Usability in Mobile app Development The title struck me as answering the first of my questions, so I chose to delve into it. The article’s title is Testing Usability for Mobile Applications by Mukesh Sharma.

The article provides an in-depth analysis of the pivotal role of usability in mobile applications. Usability has a profound impact on user engagement and app longevity, and this is something I can corroborate, as I have chosen apps with higher usability over similar apps with better quality and functions, but lesser usability. The article highlights specific usability characteristics: app simplicity to facilitate navigation effectively, helpful error handling mechanisms to guide users through troubleshooting and make it less of a hassle, optimizing efficiency to speed up tasks, and prioritizing user satisfaction to keep the app functional and supported by users. The article also delves into the nuanced focus areas for usability testing, including functionality assessments to verify feature completeness, contextual evaluations to tailor experiences to user preferences and test them against other preferences, rigorous device compatibility testing to ensure seamless performance across diverse models of mobile device and OS, examining in detail and scrutinizing data entry methods, and comprehensive examination of multimodality, to avoid user uncomfortability. The article uses an example of the Skype app to explain these potential problems. When moving the phone away from your ear, it would switch the speaker in your phone from the call speaker, to the loud back speaker. This is similar to the function in my Samsung Galaxybuds. When you take them out of your ear, it stops what’s playing or disconnects entirely. These are examples of uncomfortable features that have not been tested fairly. By adhering to the best practices for testing, developers can fix these issues in the testing phase, and assure no issues come from the software.

This applied extensively to several of my classes. I had been wondering how to think about tailoring mobile applications to the user, since learning about their development in one of my classes. This article has given extensive explanations into some poor features, and how to test to avoid these issues in the creation of the app. This will be very useful not only for mobile applications, but for testing full-stack applications as a whole, as the article covers mainly abstract ideas for testing full-stack applications.

Source:
https://www.stickyminds.com/article/testing-usability-mobile-applications

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

Week 11

Deciding on a topic this week I decided to delve into Test Driven Development (TDD). I found an article with an engaging title “Test-Driven Development (TDD): A Time-Tested Recipe for Quality Software” by Ferdinando Santacroce. This would be very useful for me and the whole class because it’s fresh in our minds and we will continue to work with this concept. Getting a firmer grasp on this topic will help me with future assignments and homework. It’s always great to get an insider view with experience inside the field connecting it to what we learn in class.

This article begins with the history of TDD giving credit to Kent Beck one of the first “extreme programmers”. At the time nobody had ever reversed the idea of testing starting with a test instead of the actual code. The purpose of writing a test before the code would help programmers put them in the perspective of the maker making it easier to create the software. This would make more tunnel-focused code with much more simplicity because of just focusing on the test. Plus the codes get rapid feedback because all the tests have been made. TDD has the fastest feedback loop only surpassed by pair programing. Currently, TDD is widespread inside the field and several teams utilize it day to day. It’s hard to adapt to this type of coding scheme but with time it is proven to be a key to success. Minor grievances may also come up because this type of process can be too rigid or the lack of tools.  

After reading this article getting a glimpse into the history of how this came to be. It didn’t specifically specify when it started but I assume it was around the 90s because it mentions how common it is now. Understanding the benefits of doing this test answers my question why would you decide to do your coding process in reverse? What we have been learning is that it will be conventional to have code and then write the test connected to the already processed code. The benefits of cutting down time because of the faster feedback times and leading to less complicated code, I now understand its purpose. That is a recurring theme with code the simpler the better because you are never working alone. Maybe it is a self-contained project but your future self may not understand your complex code and updates to the code should be easy to do not a headache. 

https://semaphoreci.com/blog/test-driven-development

From the blog cs-wsu – DCO by dcastillo360 and used with permission of the author. All other rights reserved by the author.

Test Driven Development

Test driven development is an important method of developing which is based on first writing a test for what you want your program to do, this test will fail as you do not have any code written in orde for the test to pass but you then write the code which is necessary for the test to pass and then you continue repeating this process of writing a test then writing the code for said test to pass. You are encouraged to write the simplest possible code in order to make your test pass before moving on to the next test but you may need to do some refactoring between tests in order to ensure you do not have unused code, confusing methods or variables, etc. Test driven development is very helpful when it comes to testing the specifications of a system as you can write simple unit tests which would pass if a specification was met and when it fails you know that you still must add or change your code in order to make sure the specification was met for the end product. Other types of testing are also important to perform but test driven development can help you steer away from over complicated code and make sure that you do not have recurring duplication present when you regularly refactor between cycles.

I found this article to be particularly helpful when researching test driven development as it clearly breaks down the steps of test driven development in order for the reader to fully understand the process you must go through in order to follow this development method. Along with the thoroughly explained process this article also compares and shows how both acceptance test driven development and developer test driven development work together. As we just started working with test driven development in class I found this article to provide valuable insight into the definition and process of this testing/development model as it is something rather different compared to what we have worked on previously regarding testing as we usually have worked with code that needed tests written and not with tests that needed code to be written. Being new to TDD made it seem very confusing at first as it did not feel right to be writing the tests for code which did not even exist yet but the benefits of TDD are much easier to understand once you put this method into practice.

From the blog CS@Worcester – Dylan Brown Computer Science by dylanbrowncs and used with permission of the author. All other rights reserved by the author.

Test-Driven Development

For this week’s blog, I decided to find a blog that discusses test-driven development (TDD). I found a blog called “Test Driven Development is the best thing that has happened to software design” by Arek Torczuk. In this blog, the author walks through how they apply key elements through real examples. Throughout the blog, they explain their reasons for implementing TDD and walk through how to use TDD on code that is impossible to test. They split their explanation of how to test impossible code into small sections that include bits of example code to aid in the explanation. I found the organization of the blog along with the various examples to be particularly helpful in aiding the reader understand the topic and stay engaged.

The author first explains that TDD is implemented in a fail, pass, refactor cycle approach. They shorten the idea by explaining that “our focus remains on the ‘what’, and our knowledge of ‘how’ is postponed.” In this section, the author also provides a visual which I find to be effective in blatantly pointing out the important details of this section. They then go on to explain the differences between when tests are driven by code and when code is driven by tests. When tests are driven by code although the tests written for the code may pass it may not be the right approach as feedback about implementation and design may be lacking. There are 2 questions that one has to ask themselves when they take this approach: “When should I stop adding new tests?” And “Am I sure the implementation is finished?”. The latter approach (when code is driven by tests) forces you to ask yourself “What do I expect from the code?”. When code is driven by tests, you know when to stop. TDD provides fast feedback.

The various examples of code that are impossible to test were interesting to read through. One example I found fascinating was the “Bloated setup” and the “Mocking Hell” scenarios. The first scenario is where an object either has too many dependencies or the Single Responsibility principle has been broken. The author explained that in this case you should you should rethink your design. The latter is where a mock returns a mock that returns a mock.

Overall, I think this was an interesting read. I think reading through the various examples of how to test impossible code will be useful for the future as I will have to think through how to test different kinds of code and when I should rethink certain designs.

From the blog CS@Worcester – Live Laugh Code by Shamarah Ramirez and used with permission of the author. All other rights reserved by the author.

Week 11 Blog

This week’s blog will cover the main purpose of Object Oriented Testing and its usefulness. You most likely have heard the term “Object Oriented Programming”, which refers to a style of programming that utilizes classes, abstract classes, inheritance, polymorphism, concurrency, and more as a way of organizing code. These tools can be useful when dealing with multiple lines of code because it can be broken down into multiple files creating a more organized and readable product. Having a file with thousands of lines of code is a developers nightmare. Object Oriented Testing aims to test these systems and ensure they are behaving as expected. It is possible to have too much inheritance in a program, making it difficult to find where a piece of code is located, slowing down development. Unlike other test methods that primarily test function behavior, Object Oriented Testing analyzes the behavior of the entire class and its interactions with other files.

There are multiple techniques to Object Oriented Testing: Unit Testing, Integration Testing, Inheritance Testing, Polymorphism Testing, and Encapsulation Testing just to name a few. Unit testing refers to testing of individual components of the class before testing the interactions it has with other classes. Initially testing the classes functions will prevent scenarios where you can’t locate the bug in the program because there are too many inherited classes. An example is testing each function and ensuring the behavior. Integration testing refers to testing objects of different classes and ensuring they behave properly with all the components. Inheritance testing aims to test the relationship between parent and child classes. This technique of testing also tests overridden functions are properly implemented and are actually overriding the function. Polymorphism testing aims to verify that objects of different types can be used interchangeably. This type of testing ensures the behavior across all types of objects. Encapsulation testing tests access control and ensures the data being accessed is allowed to be accessed by the user.

The main benefits of running these tests is to detect defects early on rather than later in the development process. For this reason, it’s recommended to run tests throughout development. Object Oriented Testing ensures our project is modular, making it easier to maintain. In addition, it becomes easier to implement new features and classes without impacting existing code. Due to the never-ending demands of modern applications and the ever-evolving tech industry, the scalability of a program is crucial.

Blogs chosen: https://medium.com/@hamzakhan522001/object-oriented-testing-1f9619da40d0
and https://www.h2kinfosys.com/blog/object-oriented-testing/

From the blog CS@Worcester – Computer Science Through a Junior by Winston Luu and used with permission of the author. All other rights reserved by the author.

Test-Driven Development: Because Debugging is Overrated.

You know that heartbeat you skip when you press ‘run’ and pray everything works? Well, today I shall exhibit a certain method that has been around for some time that will have you save those skipped heartbeats for when your favorite TV show character nearly dies. Enter Test-Driven Development (TDD) – it’s kind of like having a buddy checking your work as you go, making sure you’re on track

Imagine you start cooking a new recipe you found. Would you start cooking without checking if you’ve got all the ingredients? You write a small test for a feature you’re about to whip up, see it fail (because it doesn’t exist yet), and then write just enough code to pass the test. It’s a cycle: write a test, code a bit, make it pass, and clean up your code without changing how it works. Rinse and repeat.

Yes, I’m not a telepath but I know what you are thinking right now, why even bother?

One benefit of TDD is that it nearly eradicates most of the bugs in your code, making you less likely to spend hours hunting down bugs. You’re checking your steps as you go, so you know exactly where things might have gone sideways.
Your code design is going to be more professional because when you write your tests first you can make your code more modular and easier to read, kind of like organizing your closet so that you can find your favorite shirt even in the dark.
Once you have a couple of tests, guess what? You can go update or refactor your code however you like, your tests will let you know if you broke something.
Apparently, the word online is that after getting used to it you’re actually going to code faster. The backtracking time to fix bugs adds a lot to your programming timer even if it doesn’t feel like it.

Okay, It’s not all Sunshine and Rainbows. I personally feel like Test-Driven Development feels like a drag at most times, especially for people who are not used to writing tests before you code, and from what I have experienced so far, writing good tests is an art form on its own. Still, once you start, you might just want to stick with it. The payoff in reducing headaches (I promise I’ll stop using this word in the future) and quality code will be worth it.

I really want to think of TDD as my coding companion, helping to keep my code clean and bug-free. It is somewhat of a mindset shift, more frontloaded work for sure but I feel like it will result in fewer late-night coding sessions and better-quality projects. Whether you are a solo developer or a team player, giving TDD a shot could be a game-changer. So try leading the way with tests next time you sit down to code and see how that goes.

Till next time,

Ano out.

References

https://testdriven.io/test-driven-development

https://www.browserstack.com/guide/what-is-test-driven-development

From the blog CS@Worcester – Anairdo's WSU Computer Science Blog by anairdoduri and used with permission of the author. All other rights reserved by the author.

Enhancing Code Quality: A Dive into Smoke and Acceptance Testing, Exploratory Testing, and Static Analysis in JUnit

In the world of software development, ensuring code quality is paramount. It’s not just about writing code that works; it’s about ensuring that the code is robust, reliable, and maintainable. This is where various testing methodologies and tools come into play. In this blog post, we’ll explore three crucial aspects of code quality enhancement in JUnit: Smoke and Acceptance Testing, Exploratory Testing, and Static Analysis.

Smoke and Acceptance Testing: Smoke testing, also known as build verification testing, is a preliminary test that focuses on ensuring that the most critical functionalities of an application work. It aims to identify fundamental issues that might hinder further testing. Acceptance testing, on the other hand, evaluates whether the software meets the acceptance criteria and is ready for release.

JUnit, a popular testing framework for Java, offers robust support for both smoke and acceptance testing. Through annotations and assertion methods, developers can easily write tests that verify the functionality of their code. By running these tests regularly, developers can catch regressions early in the development cycle, thereby ensuring a smoother development process and a higher quality end product.

For further information on Smoke and Acceptance Testing, you can refer to the documentation here.

Exploratory Testing: Exploratory testing is a hands-on approach where testers explore the software application without predefined test cases. Instead, testers rely on their domain knowledge, intuition, and creativity to uncover bugs and issues. While automated tests are valuable, exploratory testing can uncover issues that automated tests might miss.

In JUnit, exploratory testing can be facilitated through the use of parameterized tests and dynamic test generation. These features allow testers to generate test cases dynamically based on various inputs, enabling thorough exploration of the codebase.

To learn more about Exploratory Testing, you can explore the documentation here.

Static Analysis: Static analysis involves analyzing the code without executing it, typically to find potential defects or code smells. In JUnit, static analysis can be performed using various plugins and integrations with static analysis tools like FindBugs, PMD, and Checkstyle. These tools analyze the codebase for issues such as potential bugs, code style violations, and performance bottlenecks, providing developers with valuable insights into improving code quality.

For detailed information on Static Analysis in JUnit, you can refer to the respective documentation of static analysis tools and plugins integrated with JUnit.

In conclusion, leveraging Smoke and Acceptance Testing, Exploratory Testing, and Static Analysis in JUnit can significantly enhance code quality, leading to more robust and reliable software applications. By incorporating these practices into the development workflow, teams can streamline the testing process and deliver higher quality code with confidence.

From the blog Discoveries in CS world by mgl1990 and used with permission of the author. All other rights reserved by the author.

Chapter 4 of “Apprenticeship Patterns: Guidance for the Aspiring Software Craftsman” focuses on the concept of “Confront Your Ignorance.”

This chapter highlights that acknowledging your limitations is key to growth. It offers a roadmap for identifying these gaps and strategies for filling them.

The chapter lays the foundation with the Dreyfus Model, a roadmap for skill development. It breaks down learning into five stages: Novice, Advanced Beginner, Competent, Proficient, and Expert. The authors emphasize understanding your current level and adopting a lifelong learning mentality.

Imagine your skills and experiences as a developer stacked together, like a toolbox. This toolbox is your “knowledge portfolio.” The chapter argues that for a successful, long-lasting career, you shouldn’t just have a hammer. Instead, aim to be a “generalizing specialist.” This means having a go-to tool (deep expertise) but also filling your toolbox with various other useful tools (proficiency in diverse areas). This versatility allows you to tackle more problems and adapt to changing needs in the software-development world.

The chapter outlines several strategies for effectively addressing your ignorance:

  1. Build a Solid Foundation: Focus on mastering the fundamentals of your field. A solid foundation will prepare you for more advanced learning and future growth.
  2. Learn How You Fail: Reflect on past experiences, both successes and failures, to identify areas where you can improve your knowledge. Use these insights to guide your future learning.
  3. Expose Your Ignorance: Accept that you’re still learning and don’t be afraid to admit you don’t have all the answers. See your knowledge gaps as steppingstones to becoming a master.
  4. Confront Your Ignorance: Don’t shy away from opportunities to learn. Ask questions, take classes, and constantly seek out new information to fill in the gaps in your understanding.
  5. Find Mentors: Seek out experienced individuals who can mentor you and share their knowledge. A good mentor can offer valuable advice and insights based on their own experiences.

The interesting and useful concerns about this chapter is it discusses the importance of recognizing and accepting that you don’t know everything. It encourages embracing your ignorance as a steppingstone to learning and growth.

This chapter has changed the way i think about my profession as it emphasizes the importance of continually learning and expanding your skills beyond just coding. It suggests that software development is not just about writing code but also about understanding the business domain, interacting with customers, and collaborating effectively with others.

In essence, Chapter 4 of “Apprenticeship Patterns” emphasizes the significance of admitting what you don’t know as a software developer. By recognizing your boundaries and actively pursuing chances to learn and improve, you can strengthen your abilities and progress in your software development career.

From the blog CS@Worcester – THE SOLID by isaacstephencs and used with permission of the author. All other rights reserved by the author.