For this blog post I read an article about test documentation. We haven’t talked about this in class yet, so I was curious to learn about how documentation for testing differs from normal documentation. The blog post starts about stressing the importance of testing and how it helps keep consistency, structure, and record keeping. The author then lays out their five key elements of good testing standards to keep in mind when working on a project.

The first point is that documentation should define the boundaries and scope of the project by detailing what they tests are testing for and how far the functionality of the application can go. This also helps with efficiency because it can keep people on the important objectives and not get lost working on things that are not needed. The next point is that documentation should reflect your testing strategy and approach. This includes mentioning what level or test you are running, unit, integration, or user testing (which is what my last blog talked about). It should also define the project specifications and the reasoning for the test and how why it is necessary to ensure functionality. A third element to have in testing documentation is to detail the software, hardware, equipment, and configurations for the testing, to reduce the number of variables that can account for unexpected and untested program behavior. Another key point is to have a test schedule and milestones as part of your outline and documentation to assist in workflow and keep large teams on track. The final part that should be included in the included information is the approach to be taken for defect management and error reporting. This will facilitate improvement by being consistent with company standards and working towards a complete set of tests. The author summarizes his suggestions that all comments and documentation should be consistent, clear, and regularly updated.

I wanted to look into a blog post about documentation because I know that it is important, and I personally rely on in depth documentation when looking at a new project for the first time. In this or other classes, proper annotation in code isn’t taught because of everything else that needs to be covered so I thought it would be a good topic to research on my own. With certain testing tools, sometimes it can seem that documentation is more than what is needed due to detailed automated reports that come with testing but when tracing code or looking through tests that have failed for any number of reasons it can be invaluable to have comments that describe a method’s intended function. Going forward, with the next project I do that involves testing I will make an effort to write proper documentation that follows the five elements described in the blog.

Test Management 101: Creating Comprehensive Test Documentation

From the blog CS@Worcester – Computer Science Blog by dzona1 and used with permission of the author. All other rights reserved by the author.

The blog I chose to write about this week details what different types of tests do and how they should be prioritized to test efficiently. The blog post starts with the writer talking about their own experience testing and how early on they tested their program only through the user interface, which quickly showed the downsides of this method. It was slow, couldn’t be run on all devices, and needed manual checks. Testing like this is called end to end testing and it is, slow, expensive, and not always the most revealing about potential problems. Instead, unit tests are much preferred as they test the very basic functionality and are quick. A middle ground between these two is instance or integration testing, which are able to cover most of the program without having to go through a limited user interface. These three types of testing create a pyramid to show that a majority of your cases should be unit tests, then instance tests being next most common, and finally end to end tests.

The distribution pyramid is based on five principles that make up the Smurf mnemonic. The first is speed, that has you prioritize many quick tests that will catch problems sooner. Next is maintainability that gives importance to tests that will scale well or not be subject to many dependencies. Utilization is important when keeping in mind the cost of running your code repetitiously and minimizing the resources used. Reliability states that you should always have tests that will only return an error when something is actually wrong and using these as indicators of crucial issues that need to be addressed. Lastly, fidelity is testing that recreates the users experience from start to finish, or end to end. Each type of test in the pyramid is distributed across these five factors in variable amounts, each showing their use.

I chose this blog because I wanted to learn more about writing test cases for a complete program in a work environment. I thought that this blog did well in that respect and helped in so far as providing an outline to begin with when starting to write test code. One addition that could have improved the post would be some examples, but they are easily accessible elsewhere. This will be a helpful resource and reference to use in the future when I am put in the position where I would need to start writing test from scratch, as well as being something to keep in mind when looking at prewritten tests to compare.

Test Pyramid Google Testing Blog: SMURF: Beyond the Test Pyramid

From the blog CS@Worcester – Computer Science Blog by dzona1 and used with permission of the author. All other rights reserved by the author.

The blog post that I chose to write about this week is one that gives an overview of equivalence class and boundary analysis testing. The main reason why you would use these is to reduce the number of tests you run for a program while still testing full functionality and not sacrificing coverage. It does this by sectioning the range of inputs into different equivalency classes. Equivalency classes are groups of inputs that in theory should behave identically when put into the tested function. The blog then shows a helpful diagram showcasing what this looks like plotted on a number line. This way, tests will give better information by only testing the function where problems may arise and will detail the behavior of the function near edge cases better than other methods.

The blog post also details how you can represent the classes as functions themselves for where the inputs would be, for example, true, false, or valid, by defining ranges of values with interval notation. After then going over boundary test cases, the author explains how these two methods can be used together to efficiently test around the limits of the function behavior. The blog concludes with another example plotted on a table that shows how equivalence classes and boundary testing can be combined to use a minimum number of tests while also ensuring that you test the function at its most important parts where the process will change based on inputs.

I selected this blog to help refresh myself for the upcoming test about different testing methods and to reinforce what I had learned in class. I think that one of the more important takeaways from this blog is the emphasis the author puts on combining the two methods not just because they are two different methods but because they strengthen the overall testing procedure, and this will make me think about how new testing methods can be combined to lead to better and more efficient test cases. Demonstrating the testing in terms of models on number lines and as graphs help visualize what is actually happening and why it works, similar to the models taught in class but the added element of real numbers with example values helps demonstrate the importance of this kind of testing and how it can be useful for any kind of real-world situation. As an introductory post to the topic, and in my case a review, it works well but from here I would like to look more into the different combinations of testing methods that can work well together and some that may not as I learn more methods through the rest of the class.

https://www.testbench.com/blog/equivalence-class-partioning-and-limit-value-analysis/

From the blog CS@Worcester – Computer Science Blog by dzona1 and used with permission of the author. All other rights reserved by the author.

The blog post I’ve chosen talks about the different mind sets that you should use when tackling different situations. When writing tests, it helps to write tests with different goals so that you don’t forget to test every aspect of some section of code. The blog author talks about how trying to do the tests out of order or without any order in mind you can forget things and cause it to take more time in the long run. The author categorizes these as “hats” to wear during each progressive stage. There is the ambitious hat which is for when you are testing the code in the way the customer will be using the code. There is then an uncomfortable hat which is for when your tests are failing, and you need to fix what you can in your testing. The confident hat is the one you can wear while you are refactoring your code and running just to confirm everything passes. The author also makes specific mention to not try and wear multiple hats at once.
From my experience in the classes I’ve taken so far, I’ve done some built in testing in files for whole programs that I myself have written, and so I know exactly what the code should do, what I need to have pass in order to meet the homework criteria. In these cases, because I am both the author of the code and the author of the test cases, I am able to make edits in both parts with the knowledge of exactly what the test cases should be. This has helped in my current class so far but as we move forward, we will be approaching testing like it is done in the workplace and when the people testing the code are a separate group that has not touched the program code. I’ve definitely seen myself as the coder that the author describes who frantically moves around the code and tests trying whatever I can to get everything to work instead of approaching it with any methodology. I want to become both better and more efficient at testing code as it will help me write code also and further my understanding of what makes a complete program. Testing is a big part of working in the computer science field and I know that quality assurance is very important, so I look forward to both learning more about this within the course and doing more blogs about the industry.

Chris James – The TDD Thinking Hats

From the blog CS@Worcester – Computer Science Blog by dzona1 and used with permission of the author. All other rights reserved by the author.

This week I wanted to blog about Rest API. The repository that we have been working on in class has a decently large backend that uses a wide variety of methods to act as a good example and introduction of Rest API. I wanted to look into it and try to find more examples to look at and get a better understanding by looking at implementations that either had a different format or was used for different purposes. While looking I found a blog that detailed the documentation that developers have made a standard to put with code that aids in understanding.

The article starts off with some common mistakes that can really decrease the effectiveness of your documentation such as not enough examples, the lack of English explanations, and unmaintained documentation. As aspect that the article touches upon is that the documentation should be written to be understood by entry level developers, which makes sense as your implementation shouldn’t be opaque to the users. The article provides a survey taken by web developers that ranked the most desired features of API documentation, and ranks examples, status, and error messages in the top five. This makes sense as these are some of the things that contribute most to being able to understand already existing code. Spec-driven development is also explained here and talks about using software like Swagger to keep track of and simplify your code to easily understand how the program uses the data. The blog also puts emphasis on the industry standards that should be used, and it goes a long way to help users get a grasp of new code when they start to look at new projects.

This post was helpful in understanding how to read other repositories of API, especially as it was written in the form of the writer’s or maintainer’s point of view. Although I have not yet and don’t plan to yet, write and document an API designed by myself, this write-up was equally descriptive for explaining how to read the documentation. I think that this is an extremely useful skill to have because, like in our class assignments, we won’t always be designing something from the ground up and so we need to understand what is already there. The web page had lots of pictures to illustrate the point they were making and to provide examples. It always helps to learn more of these industry standards to be better prepared for real world or out of classroom applications and strengthen your skills as a programmer.

Original Blog Post – How to Write API Documentation

From the blog CS@Worcester – Computer Science Blog by dzona1 and used with permission of the author. All other rights reserved by the author.