Unit testing is an important method that hammers out bugs in our code and verifies its behavior. Every line of code is critical to keep our projects functioning, so we must understand the benefits and best practices for unit testing to maintain our code correctly. As the title suggests, this blog post, “Unit Testing | What it is, How it Works, Types & Top Benefits”, lays out the principles of unit testing, the different types, and the benefits for software development.

 Diane Wong’s blog is a concise guide to unit testing and its benefits. It covers the types, techniques, advantages/disadvantages, and best practices of unit testing, giving an overview for newcomers to coding and those well-versed in it. I chose this resource due to its simplistic coverage of many essentials to unit testing. The blog is organized with a table of contents that leads those seeking information on a particular aspect of unit testing. It was a good start for my understanding of unit testing, and those new to the method would benefit from the blog.

I found the information concise and direct when reflecting on the blog post. This isn’t a blog that will delve into specifics on any technique or method of testing but will give you a general overview, which is what I wanted. We discussed many aspects of unit testing in class, including testing techniques like Black Box, White Box, Gray Box, Mocking, and Stubs, so some information was a refresher. The main benefit I got from this blog is a better understanding of the advantages unit testing brings, best practices, and why we use it. It lowers overall costs, allows for automation, makes debugging more manageable, and increases the team’s efficiency. The best practices were short but something to remember when conducting unit testing, like focusing on one module at a time or using conventional naming practices. The blog recommended unit testing tools besides JUnit, like Jasmine, TestNG, PHPUnit, and Mocha, which I may look into if they have better features than JUnit. Overall, the blog filled in gaps in my knowledge, and it was something I could quickly go back to or recommend to people new to the concept.

 I intend to use that knowledge for future software development projects and teach those who are unaware so we can effectively build and debug our code. Before using unit testing in practice, developers must understand the fundamentals, best practices, and advantages so they can develop good habits from the beginning. 

Link to the blog: https://testsigma.com/blog/unit-testing/

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

This week’s blog post topic covers Pairwise and Combinatorial Testing. I chose this topic because we will soon cover it in class and having some background information prior to any activities involving this method will be useful to relate back to.

Pairwise Testing, also known as All-Pairs Testing, focuses on efficiency by testing every possible pair of input parameters, rather than every single combination. For instance, if you have a form with fields for name, email, and phone number, Pairwise Testing would cover combinations like name and email, name and phone number, and email and phone number. It’s a straightforward way to catch potential bugs without an overwhelming number of test cases. With Combinatorial Testing, it builds on Pairwise Testing by considering combinations of three or more parameters together. Using our form example, Combinatorial Testing would include triples like name, email, and phone number. This comprehensive approach aims to uncover bugs that might only appear with specific combinations of inputs. This testing method aims to optimize efficiency and coverage. Software testing can be time-consuming, especially with numerous parameters and scenarios. Pairwise and Combinatorial Testing streamline the process, allowing you to detect more bugs in less time.

The key benefits to this method is it helps in reducing the number of test cases needed to achieve “good” coverage. Instead of exhaustive testing, you’re strategically covering the most important combinations. Secondly, it helps in identifying interactions between parameters that might lead to unexpected behavior. By testing these combinations, you’re better prepared for real-world usage scenarios.

Of course, there are disadvantages to Pairwise and Combinatorial Testing. One, It can become tedious due to the large number of test cases required to cover all input combinations. Two, It relies on the interaction of pairs of parameters to determine outcomes, but this assumption may not always hold true, potentially missing bugs. And three, additional tests might be necessary to complement pairwise testing, adding extra time and effort to the testing process.

The main challenge when using this method is selecting the correct input parameters. The choice of relevant parameters impacts software behavior. Careful selection ensures thorough test coverage and defect detection. However, accurately determining parameter interactions is equally as difficult, because it could potentially result in the selection of incorrect combinations.

Some of the tools used by teams are PICT, IBM FoCuS, ACTS, Hexawise, Jenny, etc. These tools help automate the test case design process by generating a compact set of parameter value choices as the desired test cases. This is done by applying the all-pairs testing technique, which involves testing all possible combinations of two parameters.

Blog Post: https://testsigma.com/blog/pairwise-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.

While writing about static testing, I spoke about my positive disposition toward dynamic testing due to its ease of access. Over the time spent writing the last blog In Defense of Static Testing, I grew to understand the benefits of testing with that approach. Now I seek to learn why dynamic testing may not be as “easy” as I once understood it to be.

One lesson I learned from the previous reading on static testing was the idea of ‘time and place’. Both testing methods are to be used under certain circumstances, rather than interchangeably. The blog post, Dynamic Testing, written by Swati Twade brings up this very idea. Twade states that due to dynamic testing’s cost, it ought to be used in effective ways. Furthermore, she warns that if dynamic testing is not used enough during the early stages of development, then there will be much more costly issues down the line. Here a certain balance must be found. The development team must use dynamic testing sparingly to reduce costs, yet must use it frequently enough to prevent larger issues from forming during the final stages of production. In these situations, static testing may be appropriate, as between dynamic testing intervals the development team can review the code and documentation to ensure that all aspects of the program are meeting their specifications. Naturally, if the team was only focused on these two aspects, then static testing could help in minimizing the use of dynamic testing however, dynamic testing captures much more than the code. According to Twade’s definition of dynamic testing, it seeks to capture both errors during the program’s runtime and how the execution of the software affects the hardware. These two focuses of testing cannot be captured by static testing, and require resources to use dynamic testing.

Through this reading, I’ve slowly begun to understand why both dynamic and static tests must be used under certain circumstances. Before researching this topic, I thought the two could be used interchangeably, without considering the resources it takes to conduct each test. Furthermore, each test focuses on reviewing specific content. Dynamic testing places high priority how on the program behaves once executed, meanwhile static testing places its priority on both the source code and documentation. Using these tests interchangeably without first understanding the conditions they work most effectively under will yield less than successful findings. Ultimately between these two blog posts, I have reinforced my knowledge of the testing processes, and have learned under what circumstances each thrives in.

-AG

Link to Original Post:

https://www.educba.com/dynamic-testing

From the blog CS@Worcester – Computer Science Progression by ageorge4756 and used with permission of the author. All other rights reserved by the author.

Recently in our course, we began an exercise in which all groups utilized static testing to find errors within a program we did not write. During this exercise, I could only think, “This would be so much easier if we could just run the code”. Rather than settling into this rut of compliance with instruction instead, I sought to find what makes static testing such a valuable approach.

Static testing is the approach to debugging where a developer (or group of developers), views the source code of a program and its related documentation. This is to find errors ranging from minor inconsistencies in naming conventions to bugs that will cause the program to break. Since static testing does not require the program to execute, developers can review the code and find errors while the compiler, among other tools, is being developed. Furthermore, all developers should be familiar with the language of the tested program, so the ‘barrier of entry’ is much lower than that of using new software to test/debug. Static testing when done in a group, can help question and apply design philosophies to the tested program. This not only helps reshape the program in the team’s ideal image but may also help developers within the group see how this design philosophy is applied.

The article What Is Static Testing, by Alexander S. Gillis, helps expand upon these aforementioned points in his work. What I found most interesting in this article was how he divides static testing into two approaches: review and analysis. Static review focuses mostly on documentation going over design, specifications, system requirements, etc. Static analysis focuses on the source code by finding errors within the structure and logic of the program. It’s important to note that both of these processes can be automated. Additionally, these types of testing, review and analysis, benefit most when used together and should not be a substitute for another. 

When done on a smaller scale, I can understand the importance of Static testing as it allows the developer to catch fundamental issues in logic or smaller bugs much earlier in the development process of the program. However, static testing may become much more convoluted as the program grows in scale. One issue that may stem from statically testing a larger program is the level of abstraction. If the code is poorly documented, or the intent of the program is unclear, then having a team review it may not be as effective. Ultimately static testing is most efficient when a team of developers understand most if not all aspects of the program, and are already familiar with both the documentation and code. If done manually, this requires much less resources than dynamic testing, allowing those resources to be used in other areas of production.

-AG

Link to Original Post:

https://www.techtarget.com/searchsoftwarequality/definition/static-testing

From the blog CS@Worcester – Computer Science Progression by ageorge4756 and used with permission of the author. All other rights reserved by the author.

For this week’s blog, I decided to do more research about pairwise testing. During my search for more information I found the blog “Pairwise Testing | What It Is, When & How to Perform?” by Kiruthika Devaraj. In this blog, Devaraj breaks down the process of pairwise testing in simple steps, along with the advantages and disadvantages. She first defines pairwise testing as a “permutations and combinations based software testing technique that tests each pair of input parameters to verify that the system functions correctly for all possible discrete combinations”. It uses a minimum set of test cases to test all possible discrete combinations. The purpose of this kind of testing is to test all possible discrete combinations of inputs without the need to test every single combination. This reduces the time, cost, effort, and number of cases that need to be written. It also allows the tester to identify errors that may occur when multiple different parameters are combined which in turn increases the overall quality of the software.

Devaraj then explains the disadvantages and challenges of this testing technique. One of the disadvantages that is explained is that it can be time-consuming especially if there are a large number of test cases. Another case is where assumptions can be false because pairwise testing relies on all pairs of parameters interacting to determine the results. She explains the challenges in bullet points to make it easier for the reader to comprehend. Some of the bullets include challenges in finding meaningful inputs and the correct set of inputs. If you don’t test carefully then the test coverage may not be enough. One also needs to determine how parameters interact with each other. 

The last few paragraphs of the blog describe using pairwise testing to speed up cross-browser testing. In this example, she explains the parameters that one would test (browser, operating system, device type, and screen resolution) and how to follow through with a real-world example. The author also includes a list of testing tools to help with automation for this type of testing.

The last section of this blog is the answers to frequently asked questions like “Is pairwise testing completely automatic?” and “How effective is pairwise testing at finding bugs?”. It helped clarify some aspects of the testing technique that weren’t explicitly answered earlier in the blog. 

Overall I think this blog was helpful in understanding pairwise testing especially because the author included a lot of examples. It gave me a better understanding of a testing technique that I may use in the future when I have to test a complex system that has multiple input parameters and multiple possible values for each parameter. 

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.