Category Archives: Technology

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.

Code Reviews: Writing Better Software Through Collaboration and Feedback

Hello everyone, and welcome to my third blog entry of the semester!

For this week’s self-directed professional development, I read the article “Best Practices for Peer Code Review” from SmartBear Software (smartbear.com). This article provides practical guidelines and research-backed insights on how to conduct effective code reviews in a professional setting. Reading it gave me a new appreciation for how structured review processes can transform not only the quality of code but also team communication and learning.

Summary of the Article

The article begins by explaining that code review is one of the most powerful tools for improving software quality. It cites studies showing that even small, well-structured reviews can significantly reduce bugs and improve maintainability.

Some key practices stood out to me:

  • Keep reviews small: Review no more than 400 lines of code at a time.
  • Limit review sessions: Spend no more than 60 minutes per review to stay focused.
  • Encourage collaboration: Authors should add comments and explanations to help reviewers understand their changes.
  • Focus on learning, not blame: Code review is most effective when it fosters shared ownership and continuous improvement.

The article also introduces metrics like inspection rate and defect rate, which can be used to measure how effective a review process is. Overall, the main message is that a good review culture combines process discipline with respect, clarity, and open communication.

Why I Selected This Resource

I chose this article because it connects directly to my real-world experience at The Hanover Insurance Group, where I worked as a PL Automation Developer intern. During my time there, code reviews were a core part of our workflow. Every piece of automation code had to go through review before deployment. I noticed that following consistent guidelines, like those mentioned in the SmartBear article, made a huge difference in maintaining quality and avoiding errors.

Since we’ve been focusing on software design and collaboration in class, this article helped me bridge what I’ve learned in theory with what professionals practice daily.

Personal Reflections: What I Learned and Connections to Class

Reading this article helped me connect classroom concepts like clean design, modularity, and readability with the real-world practice of peer review. At Hanover, I experienced firsthand how detailed feedback from senior developers helped me understand why small changes, like naming conventions or modularizing functions, mattered in the long run.

This article reminded me that code review isn’t just about technical correctness, it’s also about communication. Explaining your decisions helps others understand your design thinking, just like how UML diagrams or documentation clarify structure in class projects.

Application to Future Practice

Going forward, I plan to adopt SmartBear’s recommendations in both academic and professional work. I’ll keep my commits small, make my code clear and documented before review, and always focus on learning from feedback rather than defending my work. I’ve learned that humility and collaboration are just as essential to great software as technical skill.

Citation / Link
SmartBear Software. “Best Practices for Peer Code Review.” SmartBear, 2024. Available online: https://smartbear.com/learn/code-review/best-practices-for-peer-code-review/

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.

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.

Scrum On

Software Development Methods

Wow, look at us, huh? Almost a month later, another post appears! This month (I guess I’ve moved to monthly blogging… We’ll tighten it up, I promise) has been mostly about the different ways to go about developing something. Neat, huh?

So far, we’ve talked about waterfall, agile, and the latest, scrum!

SCRUM

Scrum builds upon each previous development methodology, and is a natural extension of Agile. It is not, however, ‘better’ than agile, but simply different. No one methodology is the best, but some perform better than other in certain circumstances. Scrum is the latest methodology that my class has been learning about, and as such I decided to take some time to further look into it.

Scrum in 20 minutes is a video I came upon while looking for examples. It explains the process of scrum, why it is used, and how it is different to other methodologies. As well as this, the video contains a few examples of how using scrum has been beneficial.

One of the reasons that I decided to watch this video was that it simply looked professional. It was well polished, and felt like a finished product. A lot of the times, when I go looking for academic supplemental material, I’m presented with a sea of the same animated characters, slideshows, and whiteboard-style videos, so this one was a VERY nice change of pace. More of these, please! (I have some words with whoever invented PowToon).

This video really helped me to see how Scrum is applied to a real life example. I also appreciated the refresher on the process as a whole, but having real-life examples of a full sprint, planning, and what each of the team members’ roles contribute was really helpful in better understanding Scrum as a whole.

Something that I realized while watching the video, was that Scrum does not have to be software development specific. I play a lot of optimization games, and something like scrum just feels extremely organized, and is something that I feel is worth applying, at least in terms of concept, to more of my life than just this one small facet. Organization and goal setting is important in almost everything we do, and Scrum is just one way to do that, but it has been refined over multiple years of trial and error.

I am excited to apply scrum to future projects, and look forward to the increased organization that a solid planning methodology will bring to the table.

This concludes my mandatory blog post of Quarter 2 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.

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.

Working in Agile and Scrum Teams

Source: Hapticmedia and The Scrum Guide

Agile is a methodology that allows for iterative development that is constantly being improved upon for the best product and efficiency. Those who use Agile follow the manifesto, consisting of 4 values and 12 principles of best practices. 

The values are: 

  1. Individuals and Interactions Over Processes and Tools
  2. Working Software Over Comprehensive Documentation
  3. Customer Collaboration Over Contract Negotiation
  4. Responding to Change Over Following a Plan

The first value relates to prioritizing how the team is working as a whole rather than following a strict set of protocols that may hinder productivity. The second value focuses on getting a working product to show the customer over spending too much time on documentation that does not progress the project. The third value involves the customer in the development process, allowing for constant feedback and a product the customer will love. The fourth value is similar to the first, reacting to changes the team needs to make to be more efficient and create a working product is more important than sticking to a plan created in the beginning. 

A type of the Agile methodology is called Scrum. Scrum breaks down a project into small “sprints” where the team works on a small increment of the whole project. In each team there are the Developers, a Product Owner, and a Scrum Master. The Product Owner acts as the communicator between the developers and the customer and maintains a priority list of what needs to be done. The Scrum Master oversees the developers and ensures they are being as effective as they can be. During each sprint, there are 4 main components, the planning meeting, the daily scrum, the sprint review, and the sprint retrospective. The planning meeting happens at the beginning of the sprint and is where the team decides what they will accomplish this sprint. The daily scrum is a daily meeting where everyone decides what they will do that day and what they will do better from the day before. The sprint review is a meeting with the customers/stakeholders where everything that was accomplished is presented. The sprint retrospective is a meeting between the scrum team where they discuss what went well overall and what needs to change for the next sprint. 

Agile is a very effective methodology for software development. Over 85% of developers use it and it improves delivery time and team morale. It also allows for all team members to be on the same level where everyone is important and always making valuable progress. I hope to be in a team that uses Agile because it is the most effective compared to other methods of software development, like Waterfall. I am looking forward to experiencing the Scrum process first-hand in the Software Development Capstone next semester and I have high hopes of what it will do for my long term career.

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

Development Environment

Development Environments in Software Process ManagementDownload

From the blog CS@Worcester – dipeshbhattaprofile by Dipesh Bhatta and used with permission of the author. All other rights reserved by the author.

Bridging Structure and Flexibility: Understanding Software Design Methodologies and Agile

Hello everyone, and welcome to my blog entry for this week!For this week’s self-directed professional development, I explored the topic of Software Design Methodologies and Agile Practices. I used several online resources, including tutorials from Atlassian Agile Coach and readings from GeeksforGeeks. Even though the focus was on understanding Agile methodologies, I found that many of the ideas connected directly to our discussions in class about the software development life cycle (SDLC) and software design principles.

Summary of the Resource

Software design methodologies provide structured approaches to building and maintaining software systems. They define how development teams plan, design, implement, test, and deliver software. Traditional methodologies like the Waterfall Model, V-Model, and Spiral Model follow a sequential or plan-driven approach — where each stage must be completed before the next begins. These models emphasize documentation, predictability, and control.

On the other hand, Agile methodologies such as Scrum, Kanban, and Extreme Programming (XP) prioritize adaptability, collaboration, and continuous feedback. Agile breaks development into small iterations or “sprints,” allowing teams to quickly adjust to changes in requirements or user needs. Instead of rigidly following a plan, Agile embraces flexibility — delivering functional software early and improving it continuously.

The Agile Manifesto summarizes this philosophy in four values:

  • Individuals and interactions over processes and tools
  • Working software over comprehensive documentation
  • Customer collaboration over contract negotiation
  • Responding to change over following a plan

Why I Selected This Resource

I chose to focus on Agile methodologies because I wanted to understand how modern development teams manage complexity in real-world projects. We often hear about Agile in professional settings, but I wanted to explore why it has become so widely adopted. After learning about structured models like Waterfall, I was curious to see how Agile differs in terms of flexibility, teamwork, and iterative design.

This topic also connects closely to our class discussions on object-oriented design and project management, where adaptability and maintainability are key. Understanding these methodologies helps bridge the gap between theoretical design principles and practical implementation in team environments.

Personal Reflections: What I Learned and Connections to Class

Exploring Agile helped me see how methodology shapes not only the process but also the culture of software development. Here are a few takeaways that stood out to me:

  • Iteration mirrors refinement in design. Just like UML diagrams evolve as designs improve, Agile projects evolve through sprint cycles that incorporate feedback.
  • Communication is central. In Agile, daily stand-ups and retrospectives ensure the entire team stays aligned, similar to how collaboration in object-oriented design ensures consistent architecture.
  • Adaptability is a strength, not a weakness. While traditional models aim for stability, Agile embraces change — which is essential when building modern, user-driven applications.

In class, we often focus on designing systems that can evolve. Agile reinforces that same mindset at the project management level software design should anticipate growth, not resist it.

Application to Future Practice

Moving forward, I plan to apply Agile thinking to my future software projects, especially in group work or larger systems. Instead of trying to perfect a design from the start, I’ll focus on building incrementally, testing continuously, and welcoming feedback early in the process.

For example, in future programming projects, I could organize development into short milestones, use version control branches to represent sprints, and hold mini “retrospectives” after each stage. These habits will not only improve collaboration but also help me develop adaptable, high-quality code.

Citation / Link

Atlassian Agile Coach. “What is Agile?” Atlassian. Accessed October 2025. https://www.atlassian.com/agile
GeeksforGeeks. “Software Development Life Cycle (SDLC) and its Models.” 2025. https://www.geeksforgeeks.org

This exploration helped me connect the structured approaches of traditional methodologies with the flexibility and innovation of Agile. It reinforced that software design isn’t just about code — it’s about creating systems and processes that can evolve as technology and user needs change.

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

From UML to Design Patterns: Refactoring the Duck Simulator

Hello everyone, welcome back to my blog! In my previous post, I explored object-oriented design basics and the importance of UML diagrams for understanding class relationships. This week, I applied that knowledge to a practical assignment by refactoring the Duck Simulator project using several design patterns, and I want to share what I learned from the process.

Introduction

UML diagrams provide a visual blueprint for software systems, helping developers understand relationships, dependencies, and responsibilities of different classes. While useful on their own, combining UML with design patterns allows us to translate those visual models into flexible, reusable, and maintainable code. In the Duck Simulator project, I used UML to identify repetitive behavior and then applied Strategy, Singleton, and Factory patterns to improve the system’s design.

Using UML to Identify Problems

Originally, the Duck Simulator consisted of an abstract Duck class and subclasses like MallardDuck, RedHeadDuck, RubberDuck, and DecoyDuck. Each duck implemented its own fly and quack methods. My UML class diagram made it clear that this design was repetitive: multiple subclasses had similar or identical behaviors. This repetition violates the DRY (Don’t Repeat Yourself) principle and makes the system harder to maintain or extend. The diagrams highlighted the exact areas where behavior abstraction could be applied, providing a clear roadmap for refactoring.

Applying the Strategy Pattern

The first refactor I implemented was the Strategy Pattern, which separates the fly and quack behaviors into FlyBehavior and QuackBehavior interfaces. Each duck is assigned a behavior object rather than hard-coding methods. Using UML, I could visualize how Duck classes now depend on behavior interfaces, not concrete implementations. For example, RubberDuck now uses the Squeak behavior, and DecoyDuck uses MuteQuack. This change made it easy to swap behaviors dynamically and reduced duplicated code across subclasses.

Using the Singleton Pattern

Next, I noticed that all ducks shared identical behaviors like FlyWithWings and Quack. To avoid creating multiple unnecessary instances, I applied the Singleton Pattern. UML helped illustrate that each behavior class has a static instance and a getInstance() method. This ensured that ducks reused the same behavior object, saving memory and improving consistency.

Implementing the Simple Factory Pattern

Finally, I created a DuckFactory to centralize the creation of ducks with their associated behaviors. UML shows a clear dependency from the simulator to the factory, encapsulating construction logic and removing manual behavior assignments in the simulator. This simplified code maintenance and improved readability, while maintaining all Strategy and Singleton benefits.

Reflection

This assignment reinforced how UML and design patterns complement each other. The diagrams helped me see problems in the design, and patterns provided proven solutions. After completing the refactor, the Duck Simulator is now modular, maintainable, and extensible. I can confidently add new duck types or behaviors without touching existing code. Personally, I learned that UML isn’t just documentation, it’s a tool that guides better design and code structure.

Resources

While exploring this assignment, I also reviewed a great resource that breaks down the concepts from Head First Design Patterns in a clear and structured way. You can find it here on GitHub. It helped me connect UML representations with real-world code implementations, especially when applying the Strategy Pattern in my Duck Simulator project.

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.

Blog post 1

The first quarter of the semester has come to a close. In CM-348 we have gone through a number of Git and GitHub features. Learning about pushing and pulling data, as well as doing some data cleaning was a great learning opportunity. As I finish my last year of school, I am trying to look at these processes in an analytical sense because that’s what I want to do moving forward.

In my free time over the past few weeks I have watched a lot of Alex The Analyst videos on YouTube. He has provided free knowledge on what it takes to become a data analyst. From interviews, to Git, to data visualization he provides a lot on his channel for people who want to learn. This week I watched his “2 Hour Data Analyst Masterclass” video. In this video, Alex breaks down what a data analyst interview process looks like from start to finish. He discusses what kinds of technical questions to expect, the importance of storytelling with data, and how to demonstrate value through projects or case studies. He also covers common interview mistakes, like not being able to explain one’s own projects clearly or failing to connect technical skills to business outcomes. This video was very insightful, he showed his viewers what skills you really need to get into the field, and it personally showed me some things I might need to work on.

I chose this resource because it’s directly relevant to where I am in my career path, as well as in my learning. I’m starting to build my portfolio and think seriously about interviews and job readiness. Alex’s advice helped me see how important communication is in data roles, it is more than being technically skilled, also being able to explain how your work impacts decisions. This connects to CM-348 because version control, documentation, and communication are key parts of the Git workflow. I am doing a bit of projecting here, but I look forward to watching more of his videos.

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