This week I am discussing a blog post titled, “Control Flow Graph In Software Testing” by Medium user Amaralisa. When I read through this post initially, it immediately clicked for me with what we have been studying in class with different path testing types which capture the logic similarly. The comparison between CFGs and a map used to explore the world or get from point A to point B is incredibly useful as it explains the need for having a guide to explain the many execution paths of the program. The writer made the topic easy to understand while still including the technical information that is required to apply these techniques moving forward.

This post helped me see the bigger picture in terms of the flow of a program and how the logic is truly working behind the code we write. It tied directly into what we’ve covered about testing strategies, especially white-box testing, which focuses on knowing the internal logic of the code. The connection between the CFG and how it helps test different code paths felt like a practical application of what we’ve been reading about in our course.

It also made me think about how often bugs or unexpected behavior aren’t because the output is flat-out wrong, but because a certain path the code takes wasn’t anticipated. Seeing how a Control Flow Graph can lay out those paths visually gives me a better sense of how to test and even write code more deliberately. It’s one thing to read through lines of code and think you understand what’s going on, but when you actually map it out, you might catch paths or branches you hadn’t considered before. I could definitely see this helping with debugging too—like, instead of blindly poking around trying to find what’s breaking, I can trace through the flow and pinpoint where things start to fall apart.

I also really liked that the blog didn’t try to overcomplicate anything. It stuck to the fundamentals but still gave enough technical depth that I felt like I could walk away and try it on my own. It gave me the confidence to try using CFGs as a tool not just during testing but also during planning, especially for more complex logic where things can easily go off track.

Moving forward, I am going to spend time practicing using CFGs as a part of my development process to ensure that I am taking advantage of tools that are designed to help. Whether it’s for assignments, personal projects, or even during team collaboration, I think having this extra layer of structure will help catch mistakes early and improve the quality of the final product. It feels like one of those concepts that seems small at first, but it shifts the way you approach programming altogether when applied properly.

From the blog cameronbaron.wordpress.com by cameronbaron and used with permission of the author. All other rights reserved by the author.

This week I am diving into an article by David Rodenas, PhD – a software engineer with a wide array of knowledge on the topic of Software Testing. I found the article, “Improve Your Testing #13: When F.I.R.S.T. Principles Aren’t Enough” which is one of many posts from Rodenas that helps provide insights to Software Testing that only a pro could provide. Through this article, Rodenas walks through each letter of the FIRST acronym with new meaning – not replacing what we know but instead enhancing what we know. As the author teaches us these new ways of understanding, examples are provided to look for ways in our own work in which these can be applied.

The acronym can be read as: Fast, Isolated, Repeatable, Self-Verifying, and Timely, but taking this one step further we can acknowledge the version that builds on top of this as: Focused, Integrated, Reliable, Significant, and Thoughtful. It is obvious that these definitions are not opposites of each other, they should also exist cohesively in our quest for trustworthy software.

One pro-tip that sticks out to me here is keeping your code focused by avoiding using the word “and” in the test name. When I first read it – it seemed kind of silly, but in a broad-sense it really does work. The writer relates this to the Single Responsibility Principle – by writing tests with a clear focus, our tests are fast and purposeful. Another takeaway is the importance of writing reliable and significant tests. Tests should not only validate but also provide meaningful information for what went wrong to cause them to fail. A test that passes all the time but fails to catch real-world issues is not significant. Similarly, flaky tests—ones that pass or fail inconsistently—break trust in the testing suite and should be avoided. Rodenas also emphasizes that integrating tests properly is just as important as isolating them. While unit tests should be isolated for precision, integration tests should ensure that components work together seamlessly. A good balance between both approaches strengthens the overall reliability of a software system.

Ultimately, this article challenges us to go beyond simply following FIRST principles and to think critically about our testing strategy. Are our tests truly adding value? Are they guiding us toward our goal of thoroughly tested software, or are they just passing checks in a pipeline? By embracing this enhanced approach to testing, we can ensure that our tests serve their true purpose: to build confidence in the software we deliver.

From the blog cameronbaron.wordpress.com by cameronbaron and used with permission of the author. All other rights reserved by the author.

This week, the blog that caught my attention was “How to Make Your Development Environment More Reliable” by Shlomi Ratsabbi and David Gang from the Lightricks Tech Blog. This work highlights common challenges encountered in software development and provides actionable solutions — specifically, how to optimize development environments. The insights offered in this blog align perfectly with our coursework, as we have continuously learned about and worked within our own development environments. This post emphasizes the importance of ensuring consistency and reliability when creating these environments, offering practical advice to achieve this goal.

The writers begin by outlining the necessity of development environments, describing the challenges that arise during software releases. These challenges include discrepancies between local and production configurations, mismatched data, permission conflicts, and system interaction issues. While creating a shared development environment may seem like the obvious solution, the authors point out that this approach introduces its own set of problems, such as debugging difficulties due to parallel testing, interruptions caused by developer collisions, and divergence between shared and production environments.

To address these challenges, the authors advocate for the implementation of branch environments. Branch environments are independent, isolated setups for developing and testing specific features or issues. These environments, when paired with tools like Terraform, Argo CD, and Helm, enable integration with Infrastructure as Code (IaC) and GitOps, automate infrastructure management, and ensure automatic cleanup of unused resources. This approach promotes consistent documentation of dependencies and application details within version control systems like GitHub. The blog includes a clear diagram and code snippets that effectively demonstrate how to set up branch environments using these tools, making it accessible and actionable for readers.

Branch environments offer several key advantages. By isolating changes, they ensure that all updates are properly tracked, simplifying debugging and maintaining consistency across development efforts. This isolation also eliminates conflicts inherent in shared environments, reducing the risk of outdated configurations or data interfering with new testing and development efforts. Tools like Terraform and Argo CD further enhance this process by automating repetitive tasks such as infrastructure provisioning and application deployment, saving developers time and reducing the likelihood of human error.

Additionally, branch environments improve resource efficiency. Since these environments are ephemeral, they are cleaned up automatically when no longer needed, freeing up valuable system resources and lowering costs. The inclusion of tools like Helm simplifies configuration management, even for complex architectures, ensuring a streamlined, manageable workflow.

Overall, this blog provides a thorough and practical framework for tackling one of the most common challenges in software development: creating reliable and consistent environments. The adoption of branch environments combined with IaC and GitOps principles enhances scalability, collaboration, and efficiency. As I continue to develop my own projects, I plan to incorporate these strategies and tools to build environments that are both robust and resource-efficient.

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

This week, I am focusing on the blog “The Software Architect: Demystifying 18 Software Architecture Patterns.” by Amit Verma. Verma is an architect who focuses on creating Java applications among other work. This blog aligns with our course work as we focus on software architecture and we have recently learned the details related to some of the design patterns mentioned here. This post has introduced me to new architecture design patterns to study and provided a vast array of knowledge like when to apply them and how to properly use them in my future projects.

Verma begins by specifying what software architecture is and how it differs from software design. I appreciate how this was explained because it makes the concepts simple to understand. Software architecture focuses on the high-level structure like the blueprint of the project, software design focuses on translating this blueprint into real project specifications which developers can implement. A concept in this post that was new to me was the architecture documentation approach, the C4 model. This model ensures that there is a structure that is able to be implemented by addressing four main levels: context, containers, components, and code. The C4 model encourages architects to create diagrams and written documents to ensure comprehensive project documentation.

The beauty of architectural patterns lies in their repeatability; they provide reusable solutions that address common goals and challenges across projects, enabling architects to achieve a specific, predetermined outcome efficiently. This post provides information related to 18 different architecture patterns that are commonly used and necessary for software developers to be familiar with. Some of the patterns were entirely new to me like the Layered Pattern, Pipe-filter Pattern, and the Microkernel Pattern. Beginning with the Layered Pattern, this architecture separates different functionalities into different layers. One common representation of this uses three main layers, the presentation layer which responsible for the UI and other user-focused components, the business logic layer which focuses on the business rules and the actual code to manage data and make calculations, and the data access layer which is handles database/external data source interactions. Next, the Pipe-filter Pattern uses independent components to process data using separate processing tasks. Beginning with the data source, moving into the pipe which connects components, then using filters to transform the data based on a given function, and finally the data sink or endpoint which receives the processed data output. Lastly, the Microkernel Pattern a.k.a. Pluggable Architecture allows for modular, flexible systems to be built. In this architecture, the system’s core services are handled in the microkernel and all other components are separated known as a plug-and-play concept.

This post is rich with vital information related to software architectures and provides knowledge far beyond what I have included here. I know I will be returning to this blog repeatedly as a resource to learn from and to use a basis of how these patterns can be implemented.

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

A blog that recently caught my attention was GitHub Engineer Sarah Vessels, “How to review code effectively: A GitHub staff engineer’s philosophy”. Vessels focuses on code review every single day which has brought her to create her own strategies for successful code review to ensure we are building good software. Though code review can be done in different ways I selected this blog because it directly involves code review via pull request reviews on GitHub which aligns perfectly with our classwork over the past couple of weeks learning to manage Git properly.  

One large part of Vessels job as a code reviewer is having an open discussion with the author of the code posing questions that may have not yet been considered. The phrase two sets of eyes are better than one comes to mind here as we can very frequently catch other’s coding mishaps, but we might miss our own. The writer stresses that acting as a reviewer for another teammate benefits both parties as the reviewer is constantly seeing someone else’s logic and new code, while the author of the code is gaining a new perspective – this exchange of knowledge is extremely valuable. 

This blog also provides tips and tricks of how to manage a queue of pull requests properly providing simple Slack queries to organize new requests by team or outstanding requests that require attention. Another tip from the writer is ensuring the reviewer team stays small – this benefits the development team overall as there is clear accountability for who is to review the changes. Vessels also commented on the benefit of specifying code review requirements/frameworks to ensure a seamless, consistent review process amongst teams.  

The writer also provides samples of good code review feedback and poor code review feedback to highlight the main differences between them. Good feedback should include specific details, references to specific issues/lines, provides a possible solution, and provides reasoning. This blog post also offers vital information related to how to give a good code review. Some of the tips seem like common sense like offering affirmations and asking questions, but an important tip Vessels shares is to be aware of biases and assumptions. The writer highlights that even the most-senior programmers can make mistakes so only you (as the reviewer) have the opportunity to validate the work and catch any issues before deployment.  

GitHub Engineer Sarah Vessels shares her invaluable experience with code review through this blog post which discusses fine-tuning the review process, good vs bad reviews, how to give good reviews, and how to get the most out of a review. As a student, it is often my own code that I must turn back to and review to enhance, but after this reading I am feeling encouraged to seek opportunities to study others code with a focus on the exchange of knowledge and getting experience on my own for how to review code for a development team in the future. 

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