Going into my future projects, especially those for my summer fellowship, I have taken a distinct interest in Python. Throughout this course I have learned a great deal of how to test for object oriented compiler languages, using Java as our learning tool. I have wondered how testing might differ across different languages. And with a large project in Python coming up, I’d like to prioritize doing this the right way. I would like to practice in python testing to prepare. Luckily, recently posted last week, there was an article on the home page of Stickyminds surrounding python testing. The article’s title is Ensuring Reliable Cloud Applications: A Guide to Testing State Machines with Python by Konstantin Sakhchinskiy

Testing state machines in cloud applications involves heavy use of APIs. Python scripting is effective to help to ensure reliability, performance, and resilience. This is one way that an efficient library-heavy scripting language like Python would be useful for cloud applications. It is very effective at being implemented for many applications now utilizing the language itself, if only as an effective testing language. In the case of a cloud app for example, managing external browser profiles for automation and web scraping, users interact via API to execute their needed functions. Python can be used to expedite this process, as a way to manage state machines necessary to operate this cloud app. General approaches to testing on these state machines include separating output generation from state transition logic, focusing on individual states and transitions, testing each possible state transition, exploring boundary conditions, testing resilience to invalid input or disruptions, and checking system interaction within the broader context. The article also mentions some key tactics for mastering state machine testing, including testing for race conditions, assessing external disruptions and network challenges, handling heavy loads, and understanding technical details such as hidden states. Python scripting can automate testing processes. Using asyncio and httpx, scripts can simulate user interactions with the cloud service, testing responsiveness. Tailoring tests to specific needs and monitoring system performance using tools like Grafana and Kibana are essentia, and made more efficient with Python’s wide variety of usable systems. Overall, testing state machines is crucial for ensuring application reliability, and Python scripting offers effective ways to automate and simulate real-world scenarios for comprehensive testing.

My view on testing applications was expanded greatly by this article. The prevalence of automated testing libraries throughout other languages to enforce scripting was a surprise to me. And this article has helped me to understand the real role of specific and intentional testing of software. I was also surprised to find that state machines were very important to understanding how to test and break down code, as this is something I learned a lot about in the fall. I am not working with external applications or languages outside of Python for this project, so I will not utilize these libraries to automate my testing, but going forward this knowledge is imperative.

Source:

https://www.stickyminds.com/article/ensuring-reliable-cloud-applications-guide-testing-state-machines-python

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.

For the summer, I will be working on a project revolving around Machine Learning and AI. I have a distinct interest in AI, and I have often wondered how it may affect the jobs of Computer Scientists. Testing specifically has been worked towards automation, but there is also the matter of human intervention required. This gave me a lot of interesting thoughts about how testing might be COMPLETELY automated using AI as the intermediary. My most used blog for testing information, stickyminds, had an article about this exact thought. The article’s title is Examining the Impact of AI on Software Testing: A Conversation with Jeff Payne and Jason Arbon by Todd Kominiak.

The integration of AI into various industries, including software development and testing, has sparked discussions regarding its potential impact. This article is an interview regarding the software testing community, and the outlook of anticipation and apprehension on how AI will reshape their roles and practices. Jeff Payne, the CEO of Coveros and Jason Arbon, CEO of TestersAI, were interviewed to delve into the implications of AI for software testing. Arbon challenges the notion that AI will make testers obsolete.And this is a sentiment that I agree with. He argues that AI will instead increase the importance of testers to ensure software quality, as AI can often err. Arbon states that the current response from testers towards AI has been somewhat ‘lackluster’, with many primarily focusing on experimenting with AI tools rather than fully utilizing its potential. One key piece of information Arbon offers is that testers would need to reevaluate their approach to testing if AI emerged as a driving force in testing. Even as AI technology evolves to automate certain testing tasks, human testers will be required to ensure the reliability and appropriateness of software solutions.This is something I think will be essential for all professions that go the route of automation through AI.  Arbon further suggests that the complexity and scale of software testing will increase alongside with the improvement of AI-testing. In the future, he envisions a pivotal role change for testers, wherein they ask essential questions of the structure and content of the code beyond mere functionality. This would also be beneficial, especially to address diversity concerns in coding, and to keep AI bias in check.

This interview opened my eyes greatly about software testing. Not just how AI will change the roles of testers, but it also changed how I think about testes as a whole. Going into this article I held the belief that a tester’s role was to assure the functionality of the code, but to also be able to address ethical concerns throughout the code, is another role entirely. I am less apprehensive now, about the role of AI in testing and software development for that matter. And I am more optimistic to see how my job will evolve as time goes on.

Source:https://www.stickyminds.com/interview/examining-impact-ai-software-testing-conversation-jeff-payne-and-jason-arbon

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.

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.

Unfortunately, just weeks after exploring test-project’s blog, it was shut down and replaced by a new blog in Tricentis. I was disappointed to find that I could no longer utilize this great resource. In searching however, I found that test-project was on its way out as far as automated testing goes, and this reaffirmed to me the ever changing world of software. In response I looked for blogs to improve my testing skills individually once more, and explored stickyminds again. The article I chose explained how practice can affect your software testing skill. The article’s title is Repetition in Practice by Justin Rohrman.

The article explores the pivotal role of repetition and practice in software testing, just as you would need in any other interest, like music. The author mentions his own experience with music in fact, and used his practice with music to inspire his software testing strategies. The article highlights the significance of deliberate practice in honing testing skills, advocating for an adaptive approach that considers the unique context of each testing scenario. A large failing of many software developers is the lack of practice, or lack of practice strategies. The article delves into some various methods for practicing software testing, to show how it connects with other interests. The most effective method introduced in the article is the ability to relate your own testing specific goals to other interests. For example: Heuristics is mentioned, and the author mentions if you like ‘Scrabble’ to play scrabble while thinking of heuristics and apply them to Scrabble. This will improve your skill in heuristics and allow you to improve it in your testing. This is an excellent strategy to help the mind focus on coding when other interests take priority. Overall the article emphasizes the importance of maintaining a growth mindset and embracing opportunities for learning and experimentation to refine testing proficiency. Outside of the article itself, there is a very valuable comment made by Michael Larsen. This comment mentions how testing is more subjective and abstract, and that it’s important to persevere when practicing. This is because unlike things like music, there are very little measurable improvements that you can see yourself, and you often have to wait for others to notice the improvements. This was an excellent thought provoking comment.

Through the CS-443 course, I have been considering how testing will play a role in my professional career and how I will develop these skills along with development. These kinds of practice strategies give me an engaging way to turn my brain into the mindset to code. This is very valuable to me, as often I can get very distracted. To be able to turn distractions into sources of thought for my own coding will be absolutely essential to developing my skills further. I chose this blog because I wanted to hone my skills but lack strategies to do so, and this applies beyond just testing for me.

Source:
https://www.stickyminds.com/article/repetition-practice?page=0%2C0

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.

After exploring more of testing, and different strategies, I wondered about how testing could be automated. I came across a blog for Postman, on the TestProject website explaining Postman’s use in automated API testing. This blog is focused on providing a tutorial to understand how to use Postman to automate testing, rather than understanding various testing practices as seen in my previous blogs. The article’s title is Getting Started with using Postman for API Testing by Dave Westerveld

The blog first defines what an API is, as Postman is specifically for API testing. The blog defines API as Application Programming Interfaces. These APIs are extremely important in facilitating communication between software systems. Testing them is paramount for this reason, to assure they are working properly. This is where Postman comes in. It is an automated API tester, with a fully fledged application download. The article outlines the setup of Postman, and explains how to get it to cooperate with your system: First open the app of Postman that you’ve downloaded and then sign in. After this you are allowed to make API requests, the new button is then used and an API request is created. You name the request, and create a collection, where the requests are stored. Following setup, the article explains how to execute a Postman request. During setup, the article created the collection name JsonPlaceHolder, and then used that collection as the URL for the Request URL. After this, Postman will send the request for you. This can be used to compare results from different requests of an API and assure they are the same, although some manual input IS required in automated testing. However more intricate API Testing is shown in further tutorials with Postman.

This is a topic that interested me greatly, as I have been given many suggestions to look into API testing. Through the CS-443 course, I had been looking for more options to test and explore coding. Automated testing is something immensely interesting, and I appreciate the comprehensive guide provided by TestProject for Postman. This is of great value to me as I will continue to look through this guide and potentially post more blogs on this topic, as I explore automated testing. This first blog is mainly involving setup, and the basic concept of requests, but I look forward to further automated API testing using Postman, as these articles are very well structured.

Source:
https://blog.testproject.io/2020/07/15/getting-started-with-using-postman-for-api-testing/

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.

While looking for more articles online involving testing, I came across SauceLabs. This website is another compendium of blogs, similar to stickyminds mentioned in my last blog. The layout and articles on this website were an excellent selection of resources dedicated to testing and quality assurance. While running through many bugs in my most recent projects and assignments, I was searching for an article dedicated to programming bugs. I found an article that fit my needs, dedicated to the differences between severity and priority of bugs, which is something I had not previously considered. The article’s title is Understanding Bug Severity vs. Priority: Key Differences and Best Practices by Chris Tozzi

The article provides (as the title indicates) a breakdown of bug severity and bug priority in software testing. It explains that bug severity is primarily concerned with the impact of a bug on the system’s functionality. Issues are categorized into the following levels of severity: critical, major, minor, and trivial. Each of these have a different level of impact on the system. For example, critical bugs may cause system crashes, while trivial bugs have a small functionality and performance impact. Bug priority focuses on the order in which bugs should be addressed, considering various factors that will impact the job as well as the program, such as deadlines, or bugs that are caused by higher priority bugs. Bugs with high priority require immediate attention, and those with low priority can be addressed later as the program develops and is tested further. It is an extremely important skill to be able to identify the severity and priority of bugs throughout the system and its development, so as to facilitate a smoother and more efficient development cycle. The article also provides some examples, such as a critical severity bug that causes data loss. This bug would ALSO have high priority because it is causing a lot of damage to the system’s structure.The article offers very useful recommendations for bug reports such as: establishing clear classification guidelines for bugs (priority/severity levels), communicating efficiently within teams, or reassessing bug statuses frequently.

I chose this blog because of my most recent experience in my assignments and projects. I had found that many bugs relied on each other, and I had never previously taken the initiative to learn more about bugs. When working with a team in industry, I will now have an understanding of how bugs are classified, as well as how to manage bug reports. This is something I had very little experience with prior to this article, and I will make sure to put extra effort into bug reports in my own projects with peers. I will continue to look into articles about bugs, testing, and QA to further improve my knowledge.

Source:
https://saucelabs.com/resources/blog/bug-severity-vs-priority

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.

After getting through a couple weeks of my classes, and looking through blogs online about testing, I found the stickyminds blog. In my first week I was given setup tasks for CS-443 Software Quality Assurance and Testing, and one of those tasks was to discover blogs and podcasts related to the course content. I used this blog for my setup tasks, and found it a useful compendium of resources. While searching through stickyminds, I focused on the area around ‘new to testing’, and found a specific article about how to improve your skills as a performance tester quite interesting. The article’s title is How to Become a Better Performance Tester 101 by Jun Zhuang.

The blog begins with a small piece of advice based on segmenting code for testing. While some people might argue that you should test and optimize after large portions of the code are complete, this blog argues instead for doing performance testing while it is still incomplete. It is also advised to learn performance testing under someone who is very experienced in the topic, as many performance testers don’t understand or know which questions they should be asking. This is why shadowing is very important, as it allows a new performance tester to pick things up quicker, and gather an understanding of the tools used more effectively. Jun Zhuang discusses Agile software development teams that are commonly used in industry. He describes them as being used to handle performance testing responsibilities. These teams use strategies such as getting developers involved in capturing performance issues early, communication between teams and testers, and holding critical team meetings more frequently. They still face occasional struggles to meet deadlines when performance issues arise, but these teams are overall described as efficient and useful. The latter half of the blog explains the importance of performance testing, and why you should put this effort into doing it. By exploring these components like applications, or databases testers can better design tests and diagnose issues. The blog also shares some personal accounts of testers utilizing their knowledge in programming to speed up testing processes, by writing stubs and generating test data. It stresses the importance that individuals with diverse technological backgrounds, even if less experienced in performance testing, can bring valuable insights and problem-solving skills to the role.

I chose this blog because I am very interested in improving my skills at all times. When I discovered the Stickyminds blog, I was excited by the amount of information it presented. This blog on performance testing I discovered in the new to testing section, which has a lot of very useful articles to help you improve your skills. Even small pieces of advice and tactics can make the difference when it comes to coding and testing especially. A personal weakness with testing in my own projects I had, was that I was worried my code was not optimized enough, and what I learned through this blog is something I will apply to improving optimization, especially seeking out someone experienced to work with and improve my skills. 

Source:

https://www.stickyminds.com/article/how-become-better-performance-tester-101

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.