I’ve been coding since around 2017, when I took my first Computer Science course in high school. Since then, I’ve worked on plenty of school projects and a couple of personal projects as well. Software testing had never been a thing I really bothered with meaningfully in this timespan, which is kind of fair considering that most of these projects and assignments weren’t really too complex. I would just print out results for each bit of code as I went along to make sure that the code I just wrote actually works, but I didn’t really go and write actual automated tests.
This semester, I had some exposure to standardized software testing when I worked on a homework assignment in my Software Design and Construction course that required me to adjust some code along with the tests that make sure the code works as intended with intended output. At first, I was sort of confused considering I had never worked with test files, but I appreciated the streamlined nature of this testing. We also had to read up on some software testing methods for a Scrum developer homework assignment we did for this class, Software Process Management.
Today, I wanted to research some software testing basics, and came across a post on IBM’s blog. The post goes over some reasons to software test (the importance of quality control for businesses, what testing even is, etc.) along with types of software tests and practices.
The different types of software tests are fairly easy to understand, and I’ve come across all of them in some capacity before. Acceptance tests ensure the system as a whole functions as intended, integration tests ensure that software components work as intended, and unit tests ensure the smallest testable snippets work as intended. Performance tests evaluate how well software works on different hardware, and stress tests check how much load the software can take without breaking. Regression tests see if new features harm the software at large, and usability tests evaluate how effective the software is for end-users.
Some good testing practices listed in the article are continuous testing, bug tracking, and service virtualization. Continuous testing is the practice of testing each build as soon as it’s available, fairly simple. Bug tracking is, well, bug tracking. The post mentions automated monitoring tools for tracking defects, but I sort of think of this in the sense of keeping an issues list on a git repository, as that’s what I’m more familiar with. Service virtualization is a little more complicated, it simulates functionality that hasn’t been implemented yet to reduce dependencies and test sooner.
What I’m mostly interested in is the applications of these practices, and I’ll likely look into it further at a later time. I understand these concepts fairly well, but the idea of automating tests, at least at my current understanding of it, sounds a bit daunting. I’m sure it saves a lot of time on larger-scale projects, where testing each piece of your code manually for multiple cases will take a lot of time. I’m interested to see what this looks like in an example.