Category Archives: Programming

Development Environments

For this blog, I decided to do some research about development environments. When looking for sources to reference, I came across the article: “Comparison of Development Environments” on Coder’s blog. This blog post goes from simple development environments to more complicated ones.

The article starts off by going into depth about what development environments are. Integrated development environments or IDEs are the center of where developers navigate and edit code. However, the IDE are just one of the components in the development environment. There are the build tools, package managers, system dependencies, and configurations. There are also many development environment architectures as well.

  • Pure local environments: used for single developers or small development teams since it is purely local. Low cost since everything is stored locally
  • Virtual Desktop Infrastructures: the development environment is on a separate remote virtual desktop. Allows better storage across bigger teams and saving in a separate place.
  • Dev Containers: The development environment is packaged into a container . Provides a way to precisely specify the development environment once so everyone can have the same versions and controls on launch every time. I know in class we were able to build our own dev containers and such to match java version and java compiler version.
  • Cloud Development Environment: dedicates, manages, and monitors dev environments.

This blog really helped me to better dive into the deeper areas of development environments. Often when it comes to where code is stored and not just writing it, I get lost and tend to get confused. Seeing the images the article used helped to show what does what and where things are held. Also, as with most things, there are pro and cons to the usages of these environments. An example being Pure local environments being used for single developers or small development teams since it is purely local. This is good because it is low cost but it is hard to work in big development teams since everything is stored locally.

I haven’t had much experience with using different environments and instead have mostly focus on coding itself, but knowing these aspects is crucial when working on projects and software. Knowing to use cloud development environments for big groups and setting up dev containers is very important in proper workflow and to make sure everyone in the team is on the same page. I hope to understand these things pushing forward into my career.

From the blog CS@Worcester – Works for Me by Seth Boudreau and used with permission of the author. All other rights reserved by the author.

Rest API Design

One of the topics we have been looking at in class have been rest APIs. Since we were working with APIs for some time I wanted to dive deeper into what they are and what makes a good one. The blog that I saw seemed perfect for this : “Everything I know about good API design” on SeanGoedecke.com.

One of the major topics that the post touched upon was that a good API design should be familiar and flexible. This mean that for developers who make them, APIs are complex products where lots of effort is put into designing them and polishing them. However, for the people who use them, the API should be familiar so that they know how to use it without lots of documentation. Even reading this makes it seem complicated. I guess I haven’t yet broken into this world of API creation. Basically, it seems like to me it would be a mix of building a simple API design but also make it be as useful as possible. Keeping it simple is not always the best solution but also making things too complicated will make things hard for the team to use.

Another Key topic the article goes over is changing APIs without breaking userspace. Basically what this is saying is that once an API is released and public, making any small change could break everything. Instead the article suggests to use versioning. I know I have working with versioning in class and looking at the different types of changes based on version numbers. For example, we used version with three different numbers as such: 2.4.0 from left to right being more breaking changes to smaller patches. Versioning is a useful way of updating APIs while also maintaining backwards compatibility. Now I really take notice in versions of applications I use and understand what kind of change has been implemented.

These aspects really helped me understand what makes a good API design. Building an API is not only making it functional but also flexible for developers and users. Being able to design APIs in two completely different ways and finding a happy medium is the key to making a good one. Also, being able to and understand versioning and how to not completely destroy your system when making changes. Going forward i hope ill be able to keep these things in mind to make thing predictable while also making the functions complex and useful.

From the blog CS@Worcester – Works for Me by Seth Boudreau and used with permission of the author. All other rights reserved by the author.

7 Essential Design Patterns

Design patterns are important for developers to use in their code. They make your programs easy to read and implement and they are able to be adapted to many situations. There are 3 kinds of design patterns: creational, structural, and behavioral. 

Creational patterns are used for creating objects. They give flexibility to change the creation process and allow for many types of objects to be created using the same method. The singleton pattern is used when there should only be one instance of an object. Instead of creating a new object every time you need to call it, you call a method that will call an instance of the object. The builder pattern is used when an object has a lot of optional parameters that make it difficult to know what is being applied when it is created. Using a builder pattern creates an empty or default object and then calls set methods to add each parameter you want to use. The factory pattern is for when there are a lot of objects of a certain type, but with different forms. Instead of creating many new objects, you call a factory to create the objects with the specifications hidden in the factory code. 

Structural patterns are used for how objects relate to each other. These patterns allow for high level code to be readable and simple, while keeping the intricacies hidden below the surface. The facade pattern is used when there are many operations and calculations behind the scenes of a process and those are all hidden with encapsulation. On a high level, one method will, for example, purchase a product, but deeper, there is a payment being processed, shipping calculations, inventory checks, etc. The adapter pattern is for when a program needs to be adapted to fit your code. It can be used for implementing public libraries where their units do not match what your program expects, and each time you use the public library, it calls the adapter to modify the output. 

Behavioral patterns are used for how objects interact with each other. The strategy pattern is used when you have multiple ways of doing a process. Instead of using a lot of if else statements, you can define several strategies and set each object to have a strategy. The observer pattern is used for objects that watch for something. It works by “subscribing” to receive a notification of an event. If a program is watching for errors, it would be automatically notified of any errors so it can add it to a log. 

In class, we went over the strategy, factory, and singleton patterns for the Duck example. These 7 patterns are common practice in the software development field and it’s important to know how to implement them. I watched a video explaining these patterns and now I have a deeper understanding of the three we learned and the four that were new to me. I feel confident I can expand on these in a professional setting.

From the blog ALIDA NORDQUIST by alidanordquist and used with permission of the author. All other rights reserved by the author.

Choosing the Right Open Source License

Choose an open source license

For this week’s self-directed professional development, I explored the topic of choosing open source licenses, which is a fundamental but often overlooked part of releasing software. I based my reading on ChooseALicense.com and supporting resources that explain how permissive licenses, copyleft licenses, and public domain-style licenses differ. What I found most interesting is how a license doesn’t just define legal rules — it reflects the values, intentions, and goals of a developer or a team. Software licensing shapes how a project evolves, how a community forms, and how contributions are handled over time.

Open source licenses fall into a few broad categories. Permissive licenses like MIT or Apache 2.0 give users almost complete freedom to reuse the code, even in closed-source commercial products. Copyleft licenses like GPL ensure that any derivative work must remain open source under the same license. And options like the Unlicense or CC0 place code essentially in the public domain, allowing anyone to use it with zero restrictions. Before this week, I assumed licensing was just a legal formality, but now I understand how strongly each license type influences collaboration and long-term project direction.

I chose this topic because licensing is directly connected to the work we do in Software Process, especially when we talk about transparency, collaboration, and project ownership. As future developers, we will eventually publish our own tools, libraries, or contributions. Knowing how to license our work is part of being a responsible member of the open source community. Many people assume that posting code publicly means anyone can use it, but without a license, nobody can legally copy, modify, or reuse it. That detail alone made this topic worth exploring, and it helped me rethink how important explicit permissions are.

One thing I learned is that choosing a license is really about choosing a philosophy. If a developer wants to share knowledge broadly, enable commercial use, and reduce friction for adoption, a permissive license makes sense. If the goal is to ensure the code stays free for everyone and cannot be closed off by others, a copyleft license protects that intention. The reading made me think carefully about what I would want if I released a personal project. Personally, I lean toward permissive licenses because I want people to build on my work without worrying about legal constraints. But I also understand why larger community-focused projects might choose GPL to preserve openness.

Going forward, I expect licensing to be something I pay more attention to in both school projects and professional work. As software engineers, we’re not just writing code; we’re shaping how others can interact with it. Licensing is part of that responsibility. This topic helped me better appreciate the intersection between technology, ethics, creativity, and law — and it reminded me that releasing software is more than just pushing code to GitHub; it’s about defining how that code fits into the larger ecosystem of open source development.

From the blog CS@Worcester – Life of Chris by Christian Oboh and used with permission of the author. All other rights reserved by the author.

Refactoring Code

When looking for some ideas with what to write about for this blog post, I settled in on refactoring code. For starters I know what it is and why we do it, but I wanted to go more in depth by looking at other resources and what they have to say about it. One of the first sources I came across was a blog post called “How to create a culture of continuously refactoring code?” by Stas Wishnevetsky. This post from Medium revealed something that for some reasons wasn’t so obvious to me and this was that refactoring isn’t a one and done kind of thing. Instead, it is more of a routine and should be done as one to keep code maintained properly and to make sure it remains easy to use.

The first thing that really struck me when reading this article was talking about code like it is something physical and biological. This comparison was made to show how code can “decay” and “rot”. While the code itself doesn’t break down and fall apart with time, there are multiple reasons that make it seem like it does. These reasons include: coding abilities improving over time, business needs and scale fluctuating, and deliberate tech debt. The article then goes on to explain why we should refactor and the end goal of maintaining stability and creating improvement.

I guess I have never had the need to deal with refactoring my code since most the time I program one time assignments and never had the need to upkeep some kind of program. I have, however experience my abilities improving while creating a project and have had some parts be sloppy while later improvements are better done. I suppose I should have gone back and refactored those early parts but the bottom line is that I’ve never had the need to. I would also run into problems trying to make small changes which would be risky in my program. This is one of the many pains explained in the article I read and makes lots of sense.

I know going forward in my career refactoring will become very prominent in my work and understanding it more now makes me feel better about it. This also really shows the amount of effort that is put into big programs we use on a day to day basis. Starting the practice of constantly and consistently refactoring my code, even simple projects, will be super beneficial for me going forward.

From the blog CS@Worcester – Works for Me by Seth Boudreau and used with permission of the author. All other rights reserved by the author.

Version Control: Why It Matters in Software Development

Version control is something I’ve used before in classes, but I never fully understood its importance until I read the Atlassian article, “What is Version Control?” (https://www.atlassian.com/git/tutorials/what-is-version-control). I selected this resource because Atlassian explains technical concepts in a way that feels practical and industry-focused, which fits perfectly with what we are learning in CS-348. Since this course emphasizes collaboration, documentation, project organization, and professional tools, I wanted to learn more about how version control actually supports real-world software development.

The article defines version control as the practice of tracking and managing changes to code. What stood out to me is that version control isn’t just for “saving work”, it’s a full system that captures every change, who made it, when it was made, and why. Atlassian highlights how this creates a long-term project history that developers can search through, compare, or revert. This directly connects to our CS-348 topics like software maintenance, project management, documentation standards, and team collaboration, because version control supports all of these practices behind the scenes.

The resource also explains how version control allows teams to work on separate branches, make experimental changes, fix bugs, or build features without interfering with one another. This connected with my experience in this course because when we work on group projects or assignments, version control prevents us from overwriting each other’s work. The article also discusses merge conflicts, and reading about it made me feel better about the moments when I’ve run into conflicts myself. Instead of seeing them as mistakes, the article made me realize they are a normal part of teamwork and software development.

One major takeaway for me was the idea of traceability. Every commit tells a story, not just about the code, but about decisions, goals, and teamwork. This encouraged me to treat commit messages more seriously so that my future teammates (or even future me) can understand the purpose behind changes. The article made me realize that version control isn’t just a technical tool; it is a communication tool. This is something I didn’t appreciate before reading it.

This resource affected how I view my future practice because version control is required in almost every professional software environment. Reading about how teams rely on it to avoid lost work, manage parallel development, and maintain high-quality software helped me understand why CS-348 emphasizes collaboration tools, project organization, and documentation. Going forward, I plan to use branching more intentionally, commit more frequently, and write clearer commit messages. I also want to apply what I learned outside of class by using version control for my personal and club-related tech projects.

Overall, this article helped me connect the technical skills we practice in CS-348 to how real development teams work. It showed me that version control supports not just code, but communication, teamwork, and professionalism — all skills I want to continue developing.

Source

Atlassian. What is version control. Retrieved from https://www.atlassian.com/git/tutorials/what-is-version-control

From the blog CS@Worcester – Circuit Star | Tech & Business Insights by Queenstar Kyere Gyamfi and used with permission of the author. All other rights reserved by the author.

Code Can be Dirty?

Unfortunately, yes

The above code is positively awful to look at, read, try to understand, and generally poor practice. Recently, in this semesters Software Development class, we have moved away from project structures, and into clean code. What makes it clean, why is it important, and related topics.

Why clean?

Clean code provides an easy reading experience for anyone looking at it. This include people later working on something released years ago, as well as the person writing completely new code for the first time. Every example of code can benefit from being clean. Coding cleanly enables readers to understand what the code is doing, and makes it easy to follow mentally. As well as this, clean code can make better code, as spotting mistakes is made easier when you know where everything should be.

What makes code clean?

Clean code is code that is easy to read, understand, and modify because it expresses its intent clearly and avoids unnecessary complexity. It uses meaningful names, small and focused functions, and consistent structure so that another developer can quickly grasp what it does without confusion. Clean code avoids duplication, hides internal details, and keeps responsibilities separated so each block does one thing well. It favors simplicity over cleverness, documents why decisions were made, and is organized in a way that makes future changes safe, predictable, and maintainable.

In the wild

This video is a perfect example of how clean code, and specifically refraining from nesting your code too much, is a good habit to form. The video explains that multiple layers of if statements, loops, and conditional branches make code harder to read, maintain, test, and debug. The creator argues that nesting increases cognitive load because developers must track several scopes at once, and it often signals that a function is trying to do too many things. The video recommends techniques such as using early returns, inverting conditions, and extracting complex inner blocks into smaller, well-named functions so the main “happy path” remains flat and easy to follow. Overall, reducing nesting leads to cleaner, more understandable, and more maintainable code.

I chose this resource as it was a fun video that I found ‘in the wild’ while simply scrolling, and felt that it closely aligned with principles we have been learning in class.

In conjunction with in class learning, I have been swayed to become a ‘never-nester’. I would like to put into practice this behavior, and am excited to maintain clean, readable code in future projects.

This concludes my mandatory blog post of Quarter 3 for the semester.

— Will Crosby

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

REST API Parameters and Filters

This past week in class, we were working on a homework assignment on REST APIs. In the first part of the homework, we had to create new endpoints for the inventory path. The part I struggled with was writing the query parameters. I was pretty confused and felt like I was going in headfirst to something I didn’t understand. I found a site that explains the API’s parameter syntax to help. 

For path parameters, the name of the parameter is the same as the one in the path.

For query parameters, the name is not in the path and can be anything. 

The body of the parameter is the exact same. It needs a name, a declaration of if it’s a path or query parameter, if it’s required, a description, and the format of the input. 

After reading through the site, I realized I was over-complicating it, and all I had to do was use the same format as the already created parameter bodies and alter it to what I needed. 

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The next part of the homework assignment was to use GET methods to filter for results. I did not end up completing this part of the assignment, but I was still curious on how it worked. I found a site that explains all the ways you can filter for results, like having an attribute be equal, less than, or greater than a value. 

To filter for an attribute with a specific value, use this line: 

GET /path-name?attribute=value 

You can link filters with an &:

GET /path-name-1?attribute-1=value-1&attribute-2=value-2

Less than, less than or equal to, greater than, and greater than or equal to is achieved by the shorthand lt, lte, gt, and gte, respectively. Greater than would be shown like this:

GET /path-name?attribute_gt=number-value

The homework asks us to filter for guest age in the right path, using equal to, less than, less than or equal to, greater than, and greater than or equal to. To solve this, I would use the GET method with the guests path and the appropriate ending, like:

GET /guests?age=40
GET /guests?age_gt=40

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Understanding the format and syntax of REST APIs will be very useful for the Software Development Capstone next semester. I understand parameters, how to create schemas, how to reference the schemas and error codes, which are all extremely useful for future projects and in a job setting. As we continue to learn how to use REST APIs and expand our knowledge, I feel comfortable adding REST API design and implementation into my skillset.

From the blog CS@Worcester – ALIDA NORDQUIST by alidanordquist and used with permission of the author. All other rights reserved by the author.

Understanding Design Patterns: Creational, Structural, and Behavioral

Hello everyone, and welcome to my blog entry for this week! Technically, not a blog entry since I am just re-doing the one, I previously posted.

Last weekend, I listened to the podcast from the Coding Blocks Podcast (codingblocks.net). I’ve always been curious about how experienced developers structure their code to make it easier to maintain and scale, so this seemed like the perfect topic to explore. The episode focused on design patterns, specifically the three main categories: Creational, Structural, and Behavioral. Listening to it gave me a new appreciation for how these patterns help solve common software design problems and make codebases more adaptable over time.

Summary of the Podcast

The episode, which runs for about 50 minutes, features developers Michael Outlaw, Joe Zack, and Allen Underwood discussing how design patterns provide reusable solutions to recurring challenges in software development. They describe Creational patterns as those that handle object creation in a flexible way, Structural patterns as those that organize and relate classes and objects, and Behavioral patterns as those that define how objects communicate and share responsibilities.

They shared several examples, such as the Factory Method (a Creational pattern used to create objects without specifying exact classes), the Adapter (a Structural pattern that allows incompatible interfaces to work together), and the Observer (a Behavioral pattern that lets one object notify others when its state changes). What I liked most was how the hosts emphasized that patterns aren’t rigid rules, they’re practical tools developers use to make their code more consistent and easier to maintain.

Why I Selected This Resource

I chose this podcast because I wanted to deepen my understanding of how large software systems are organized. I’ve often heard about design patterns being essential for professional software engineering, but I never had a clear idea of how they were actually applied. The podcast stood out because it explained patterns in an approachable way, connecting them to real-world examples like GUI systems, game engines, and web frameworks. It helped me see that these patterns appear everywhere from database connections to event handling, and that learning them is key to writing scalable, professional-grade code.

Personal Reflections: What I Learned

After listening, I realized that design patterns are really about thinking ahead.

  • Creational patterns reminded me that object creation should be flexible, not hard-coded.
  • Structural patterns showed me how organizing relationships properly can make systems easier to extend.
  • Behavioral patterns highlighted the importance of communication between objects and how good design reduces dependencies.

What stood out to me most was how design patterns encourage better decision-making. They don’t just make code work, they make it work better over time.

Application to Future Practice

Moving forward, I plan to start identifying patterns in the code I write. I want to experiment with the Singleton pattern for managing shared resources, like configuration files, and use the Strategy pattern when implementing algorithms that can be swapped dynamically. Understanding these patterns will help me approach programming challenges with more structure and confidence, and will prepare me for real-world software development where scalability and design quality matter most.

Citation / Link

Outlaw, Michael; Zack, Joe; and Underwood, Allen. Design Patterns Explained. Coding Blocks Podcast, 2019. Available online at codingblocks.net.

This podcast helped me see how Creational, Structural, and Behavioral design patterns provide a common language for building better software. Listening to it last weekend gave me new insights into how thoughtful design decisions can make a project more flexible, maintainable, and ready for growth.

From the blog CS@Worcester – Rick’s Software Journal by RickDjouwe1 and used with permission of the author. All other rights reserved by the author.

Testing Smarter, Not Harder: What I Learned About Software Testing

by: Queenstar Kyere Gyamfi

For my second self-directed professional development blog, I read an article from freeCodeCamp titled What is Software Testing? A Beginner’s Guide. The post explains what software testing really is, why it’s essential in the development process, and breaks down the different types of testing that developers use to make sure software works as intended.

The article starts with a simple but powerful definition: testing is the process of making sure your software works the way it should. It then describes several types of testing like unit, integration, system, and acceptance testing and explains how each one focuses on different levels of a program. It also introduces core testing principles such as “testing shows the presence of defects, not their absence” and “exhaustive testing is impossible.” Those ideas really stood out to me because they show that testing isn’t about proving perfection it’s about discovering what still needs to be improved.

I chose this article because, as a computer science student and IT/helpdesk worker, I deal with troubleshooting and debugging almost daily. I’ve always seen testing as something that happens after coding, but this article completely changed that mindset. It made me realize that testing is an ongoing part of development, not a one-time task before deployment. It’s a process that ensures software is not only functional but also reliable for real users.

What I found most interesting was how the author connected testing to collaboration and communication. Writing good test cases is like writing good documentation, it helps other developers understand what the software should do. The idea of “testing early and often” also makes a lot of sense. By catching issues early in the process, developers can save time, reduce costs, and prevent bigger headaches later on.

Reading this made me reflect on my own coding habits. I’ve had moments in class where my code worked “most of the time,” but I didn’t always test for edge cases or unexpected inputs. Moving forward, I plan to write more tests for my own projects, even simple ones. Whether it’s a class assignment, a group project, or a personal program, I now see testing as a chance to build confidence in my work and improve how I think about quality.

Overall, this article helped me understand that software testing isn’t just about finding bugs it’s about building better software. It’s a mindset that values curiosity, patience, and teamwork. By applying these lessons, I’ll be better prepared not only to write code that works but to deliver software that lasts.

***The link to the article is in the first paragraph***

From the blog CS@Worcester – Circuit Star | Tech & Business Insights by Queenstar Kyere Gyamfi and used with permission of the author. All other rights reserved by the author.