Category Archives: ai

Mastering Backend Development: A Comprehensive Guide

Backend development is where the real magic happens. While users interact with the front end of an application, the backend is responsible for everything from data storage to user authentication, ensuring smooth communication between services. Mastering backend development goes beyond learning a single language or framework it’s about understanding how to build scalable, secure, and maintainable systems. In this overview, Im going to talk about the article written by DEV COMMUNITY on mastering backend development

Choosing the Right Language

Choosing the right language is the first step in backend development. Your choice depends on the project’s requirements and your long-term goals. JavaScript (Node.js) is popular for event-driven servers, while Python is great for data-centric applications. Java is ideal for enterprise solutions, and Go is well-suited for high-performance services. Each language has its strengths, so pick one that aligns with your project needs.

Understanding HTTP and Networking

Since backend services communicate over the internet, understanding HTTP is crucial. Knowing how HTTP methods like GET, POST, PUT, and DELETE work, along with concepts such as DNS, will help you design efficient and secure APIs. A solid understanding of these concepts allows smooth communication between services and ensures reliable system integration.

Working with Databases

Databases are fundamental to backend development. Whether you’re using relational databases like PostgreSQL or NoSQL databases like MongoDB, it’s essential to know when to use each. A solid understanding of database management enables you to store and retrieve data efficiently, which is crucial for building fast and scalable systems.

API Design and Development

APIs are the backbone of communication between system components. Designing an efficient and secure API is key to building scalable systems. Whether you’re using REST, GraphQL, or gRPC, consider factors like versioning, security, and documentation to make integration easy for other developers.

Security Practices

Security is essential in backend development. Implementing robust authentication methods like OAuth and JWT ensures that only authorized users can access your services. Understanding common security threats and mitigation strategies is key to protecting your system from unauthorized access and data breaches.

Caching and Performance

To optimize performance, caching is a must. Using tools like Redis or Memcached can help reduce database load and speed up response times by temporarily storing frequently accessed data. Proper caching strategies can drastically improve your system’s performance and scalability.

Scalability and Load Balancing

As your application grows, scaling becomes crucial. Load balancing tools like Nginx or HAProxy ensure that traffic is evenly distributed across servers, helping handle increased traffic without sacrificing performance. Understanding scaling strategies, such as horizontal and vertical scaling, is essential for building resilient systems.

Continuous Learning

Backend development is always evolving. Keep up with new tools, frameworks, and best practices by reading blogs, contributing to open-source projects, and experimenting with new technologies. Continuous learning is essential to becoming a skilled backend developer.

By mastering these concepts, you’ll be on your way to building robust, scalable, and secure backend systems.

Reference
https://dev.to/roadmapsh/mastering-backend-development-mpb

From the blog CS@Worcester – The Bits & Bytes Universe by skarkonan and used with permission of the author. All other rights reserved by the author.

Week 15

Working inside the backend made me curious about people’s real-life experiences working in their company’s backend. I found articles about the backend but have yet to gain experience working inside it. It would be helpful to get insight into someone’s real-life experiences. By seeing others’ experiences you can learn from them and avoid any mistakes they made starting. Many beginner mistakes are big headaches when they happen, but if someone else can stop you from making them, it will be a huge lifesaver. We learn sometimes the hard way but the biggest help to prevent this is to learn from other paths. Some may think it better to go in blind I think differently. Being prepared for me is always the better option

Blessings James starts the article by advising readers that starting it may be difficult but to trust the process because the feeling after you accomplish your task is another feeling entirely. Her favorite project was working on a to-do list application with a backend using Python. It was difficult for her to work while also being data efficient. By doing research she was able to find a scalable model that worked. She also discovered some libraries including Flask-login that would do a lot of the heavy lifting. This was key for security which is often overlooked. Debugging is always a problem that comes up but she was able to gracefully fix them. API design was also a key feature wired on but swagger made it a lot easier. 

Reading this article gave me a lot of insight into someone working in the backend for a real company. There were some similarities to what were doing now including swagger. Swagger seems like the for the API design. We haven’t used all the features of Swagger but using Swagger Preview did help when doing assignments and homework. Our code was automatically able to be seen updated. One thing that interested me was Flask-login. I didn’t know you could use outside libraries but it makes sense if it is open to the public anyone can use it. It can save time by being able to use different libraries and cut your workload by half. Reading that article there was a big emphasis on security and I feel at times is overlooked. You have seen with a lot of companies when it is overlooked the outcomes are drastic. It becoming a bigger issue every day and security should be the first task on everyone’s list.

article
https://medium.com/@blessingjames1047/an-article-on-backend-ff90312c05b2

From the blog CS@Worcester – DCO by dcastillo360 and used with permission of the author. All other rights reserved by the author.

Week 14

We have collaborated on the backend for the last few weeks. It is the central workload of our work, so I wanted to find an article about it. It very much intertwined with what were doing in class and outside of class with the homework. It is a great opportunity to see other people’s experiences working in the back end and real-life experiences. You can understand more things that we didn’t dive into the class by doing research and expanding our knowledge. That is why this week I found an article that specifically goes into detail about backend development.

The article starts by mentioning the importance of the backend and how it’s often overlooked because most of the spotlight is on the front end. The back end is like what is under the hood of a car you are happy when it works without having to open the hood. That being said the front end and back end work in tandem it’s not always necessary but for this scenario yes. The front is more the user-facing elements of a website. Like the text that is being displayed, graphics, buttons, and or anything the user interacts with.While the backend focuses on the behind-the-scenes work to make the website function. Outside of a car is the front end and its engine and other components are the back end. The backend is important to complete any user request by being safe and efficient. Security and efficiency are key processes of the backend for the user experience. This is why both backend and frontend developers must work in unison to create successful applications. The main importance backend developers should go for is innovation. Technology is always evolving and people must adapt to it becoming stagnant won’t be successful in this field.

Reading this article made me understand more about backend development. Backend development has so much more to it with data and security. It makes sense because security is often overlooked at times. The more information is stored online the more we have to make the effort to secure people’s data. Nobody will want to use your application if there is a breach of security. My main takeaway was their statement about innovation. Their final message to the reader was a hopeful one stating that a developer must change with the times because they are in the epicenter of it. Technology goes far out including healthcare solutions that might not be important to some but are highly integral to a lot of people.  

https://www.ciat.edu/blog/understanding-backend-development/

From the blog CS@Worcester – DCO by dcastillo360 and used with permission of the author. All other rights reserved by the author.

A License to Develop Software

I read a blog titled “Software License Management” by Samantha Rohn of Whatfix. It dives into the complexities of software licensing, explaining the different types of licenses and their implications. Since I’ve been learning about open-source projects and legal considerations in software development, this blog felt like an essential read. I picked this blog because software licensing is a topic that many developers, including myself, often overlook or misunderstand. In my coursework, we’ve briefly touched on the importance of licenses, but I never fully grasped the differences between them or their real-world applications. As I start working on team projects and open-source contributions, understanding how to navigate licensing is crucial to avoiding legal issues and contributing responsibly to the developer community.

The blog provides an overview of software licensing, emphasizing why it’s critical for both developers and organizations. It categorizes licenses into two main types:

  • Permissive Licenses: These allow more flexibility. Developers can modify, distribute, and use the software with minimal restrictions, often without the need to release their modifications.
  • Copyleft Licenses: These require derivative works to retain the original license terms. For example, modifications to a product under a copyleft license must also be distributed with the same license attached.

The post also introduces the concept of software license management, highlighting the need for organizations to track, organize, and comply with licenses to avoid legal and financial risks. It concludes with best practices for effective license management, such as inventorying all software assets and ensuring compliance with usage terms.

This blog was an eye-opener for me. One thing that stood out was the explanation of copyleft licensing. Before reading this, I didn’t realize how restrictive some licenses could be in terms of sharing modifications. For instance, if I modify software with a copyleft license, I’d have to release my work under the same license, which might limit its use in proprietary projects. This insight made me rethink how I approach licensing for my own projects.

I also found the section on license management practices especially relevant. As developers, we tend to focus solely on the technical aspects of coding and ignore legal considerations. However, knowing how to choose and manage licenses is equally important, especially as I start collaborating on larger projects.

This blog gave me a clearer understanding of how to responsibly use and share code. Moving forward, I’ll make sure to read and understand the terms of any license attached to the libraries and frameworks I use. Additionally, when I create software, I’ll carefully select a license that aligns with my goals, whether for open-source contribution or proprietary use. If you’re new to software licensing or want to understand how to manage licenses effectively, I recommend reading thisblog. It’s a straightforward guide to a topic every developer should know.

Resource:

https://whatfix.com/blog/software-license-management/#:~:text=For%20the%20most%20part%2C%20copyleft%20licensing%20is,with%20the%20source%20product’s%20copyleft%20license%20attached.

From the blog Computer Science From a Basketball Fan by Brandon Njuguna and used with permission of the author. All other rights reserved by the author.

Connecting “Copyrights in AI” to Copyright and Licensing Homework

In the rapidly advancing world of artificial intelligence (AI), the intersection of technology and law has become increasingly complex. One of the most pressing legal issues is how copyright laws apply to AI-generated content. This is exactly what the article, “Copyrights in AI: Legal Overview” from HackerNoon offers, the author discusses the implications of copyright laws in the context of AI, focusing on whether AI can be considered an author of creative works, and how this impacts the rights of those who use AI to create content.

The article provides a clear overview of the current state of copyright law as it pertains to AI. Traditionally, copyright laws have protected works created by human authors, but with the rise of AI-generated content, it led me to ask: “can an AI be considered an author in its own right, or does the copyright belong to the human who programmed the AI, or the user who directed its output?” I learned that, under current law, AI cannot be considered an author in its own right, and the copyright typically belongs to the human creator or the user of the AI. This reflects a fundamental principle that we explore in our class, especially when considering software licenses. For example, when choosing a license for a software project, it is essential to understand the ownership of contributions and the rights of the contributors.

I selected this resource because the legal implications of AI are an area of particular interest to me, especially as AI continues to grow in influence and application across various industries. In one of my other classes, Computing Ethics, we talked about the ethical responsibilities and legal dilemmas surrounding the use of AI. The context being medical fields or business, how would the use of AI affect the users using it. This article connects those themes by highlighting the legal aspects of AI usage and authorship, which I had not fully considered before. It helped me understand that as AI technology becomes more sophisticated, the law may need to adapt to address new challenges.

By exploring “Copyrights in AI: Legal Overview” and reflecting on the licensing aspects discussed in my homework, I have gained a deeper understanding of how AI-related legal issues intersect with software licensing. In our Copyright and Licensing Homework, we focus on understanding different licensing models and the implications they have on the use and distribution of software so understanding who owns the rights to AI-generated works is critical to deciding how those works can be shared, modified, or distributed.

I expect to apply this knowledge when working with software projects, ensuring that the terms and conditions of any AI tools or systems used are clearly defined. As AI continues to grow in capabilities and its integration into software development increases, I believe this knowledge will be essential to navigating the complex legal landscape.

Link to the resource: HackerNoon article: Copyrights in AI: Legal Overview

From the blog SoftwareDiary by Oanh Nguyen and used with permission of the author. All other rights reserved by the author.

Workflow for a Developer


This week, I came across an post titled “Improving Developer Workflow” on Vercel’s blog, and it caught my attention because I’ve been trying to figure out how developers stay productive while coding. The article dives into different ways to make workflows more efficient, focusing on tools and practices that help developers ship better code faster. Since I’m new to computer science and still figuring out how to work effectively, this post felt super relevant to my learning journey.

The post highlights key aspects of improving developer workflows. It starts by discussing the importance of having fast feedback loops, meaning developers should quickly see the results of their code changes. This post introduces tools like Vercel’s platform, which makes it easy to preview, test, and deploy changes almost instantly. Another focus is on collaboration, emphasizing how tools like GitHub help teams share work and review code seamlessly. It wraps up by stressing the value of automation, like setting up CI/CD pipelines, to reduce repetitive tasks and ensure consistent quality in the codebase.

I chose this post because workflow optimization feels like an essential skill for any developer, even beginners. Sometimes I get stuck on repetitive tasks or wait too long to test my code changes, which can be frustrating. This post seemed like a good way to learn how experienced developers streamline their processes. Also, tools like GitHub and CI/CD were mentioned in class, so I wanted to understand them better.

The main thing I learned is how fast feedback loops can save a lot of time and frustration. For example, using tools like Vercel lets developers instantly preview their changes in a live environment, so they don’t have to guess if their code works. I also learned how CI/CD pipelines automate testing and deployment, which not only saves time but also reduces the risk of errors. I realized that these tools make a developer’s life easier, but they also require some setup and understanding, which I’m excited to learn more about. Another cool takeaway was how much collaboration matters in a developer’s workflow. I’ve used GitHub for simple projects, but the blog post made me realize how powerful it can be when teams use it for pull requests, code reviews, and tracking changes.

This blog post made me want to improve my own workflow by setting up faster feedback systems, even for small projects. I also plan to explore tools like GitHub Actions to try basic automation for testing. In the future, I hope to use these techniques to work more effectively on team projects and avoid common frustrations like repetitive tasks.

Resource:

https://vercel.com/blog/improving-developer-workflow

From the blog Computer Science From a Basketball Fan by Brandon Njuguna and used with permission of the author. All other rights reserved by the author.

AI Is Not A Software Engineer

In this blog, the author discusses how much the times have changed for new CS graduates. Reminiscing about how little they knew and how easily they got a job. Then talks about how much more prerequisite knowledge is needed to even sniff a job. The topic of the article is how now more than ever it is easier to get code that works. Thanks to AI, code is now more plentiful than it ever was before. However, all code is not good code. This leads to them discussing how despite how much code there is these days. Having people capable of understanding and able to build software are still very necessary. 

Although AI can now code for us, the coding wasn’t the hard part in the first place. The hard part was building software, and making good software. It’s easy to throw a bunch of code snippets together that accomplish something. But it is something entirely different to build specialized software that fills certain functions and meets certain criteria. AI cannot replace people, even though it may take away some jobs. At its heart, AI cannot build unique software. Teams of capable developers are still needed. The nature of how people code is changing. It’s becoming more important to be able to harness AI, but still oversee and build functional software.

I chose this article because I think it relates to team building. Like the article said, you need people who can understand code, not so much write it. Writing code is easier than ever, but finding people who understand how to build software is harder than ever. When using these tools it’s important not to rely on them too much. Discerning who can actually code these days is probably one of the most important skills for employers these days.  I think it’s important for me and everyone to keep in mind that AI is a tool. Tools dont make up for lack of knowledge. Tools are used best by people who know how to use them and maximize their use. One tool can’t solve every single problem. At the end of the day, knowledge is the most important part of being a software developer. 

Citations

https://stackoverflow.blog/2024/06/10/generative-ai-is-not-going-to-build-your-engineering-team-for-you/

By Charity Majors

From the blog CS@Worcester – Code Craft by Kyle Tucker and used with permission of the author. All other rights reserved by the author.

How AI Tools Separate Us From Information

It is no secret that ChatGPT has blown up recently. It is not just used by CS people, but everyone from all walks of life. It has become a common tool used to help people with a wide range of problems. Offering a quick way to get answers without needing to look for answers by yourself. However, these AI tools are not just a catch all solution for every problem. In this blog from Stack Overflow called “Knowledge-as-a-service: The Future of Community Business Models” discusses how these recent developments have affected how we access information.

In just the last twenty years alone, the way of searching for knowledge has changed. Going from books, to search engines, and cloud technology allowing for farther reach. In recent times we have seen the rise of AI tools that help guide us to the answers we seek. These AI tools however, create a separation between knowledge and the people who make it. AI does the searching and synthesizing for us. Although convenient, it raises the question if that is the best way for people to learn.

Some common concerns held by people are that ChatGPT offers answers. It often does provide context as to why solutions work. What works for one dev environment might not work in another. AI is also reliant on humans for new consumption knowledge. If humans are not creating new knowledge, AI cannot create new information. The credibility of these tools often comes under scrutiny as well. Many developers mention how much variance there is to answers. Although these are certainly draw-backs, developers are learning that community created content is more needed than ever.

I choose this topic because I believe that most students use ChatGPT or some other tool to help us. I myself use it often to help with pretty much every single class I take. But I definitely rely on it the most for CS. I ask how something works or what is the best course of action. I think it is a common concern for many employers cause many don’t know how to actually code. Many people just copy and paste without learning. I am guilty of this myself. But I have been working on trying to actually understand every bit of code. And learning of where and when to apply these code snippets I use. I believe it is still very important to learn from sources outside of chatGPT. Like from classes or other websites composed of trustworthy data. It’s good to learn how to do things yourself without relying on outside sources.

Citations

https://stackoverflow.blog/2024/09/30/knowledge-as-a-service-the-future-of-community-business-models/

By Ryan Polk and Ellen Bradenberger

From the blog CS@Worcester – Code Craft by Kyle Tucker and used with permission of the author. All other rights reserved by the author.

Software Maintenance

Source: https://www.geeksforgeeks.org/software-engineering-software-maintenance/

This article is titled “Software Maintenance – Software Engineering.” Software maintenance “refers to the process of modifying and updating a software system after it has been delivered to the customer.” There are many different aspects involved in this including: fixing bugs, adding new features, and keeping up with new hardware and software requirements. Maintenance is very important for ensuring that software is able to last long. This process can be expensive and complex, so these factors must be taken into account during the planning of a software development project. The important tasks in regard to software maintenance are: bug fixing, enhancements, performance optimization, porting and migration, re-engineering, and documentation. Summarizing these tasks, it is important to find and fix errors quickly, add new features/improve existing ones, improve the performance of the software, adapt the software to run on different hardware, improve the design, and maintain accurate documentation of all of these processes. There are quite a few different types of software maintenance, but they can be categorized into proactive and reactive types. “Proactive maintenance involves taking preventive measures to avoid problems from occurring, while reactive maintenance involves addressing problems that have already occurred.” Maintenance can be done by stakeholders, the development team, a third-party, and they can be both planned or unplanned. Planned maintenance can be described as regular maintenance (bug fixes) while unplanned maintenance can be described as reactive maintenance that occurs when something unexpected happens. Maintenance can fall into these different categories: corrective maintenance, adaptive maintenance,  perfective maintenance, and preventive maintenance. Corrective refers to fixing bugs and enhancing performance of the system. Adaptive refers to modifications being made when a customer needs the software to run on a different system. Perfective refers to the adaption of the software when a customer has a demand. Lastly, preventive maintenance refers to modifications that focus on the prevention of future issues with the software. Software maintenance is important but there are some things to consider: the cost, complexity, possibility of new bugs, users not updating the software, compatibility, technical debt, and end-of-life (where maintenance isn’t possible anymore or cost-effective).

I chose this article because I found it in the syllabus and thought the topic to be interesting. We are always learning about the development of software, but the idea of maintaining it over the long term isn’t as heavily considered. A large part of the work of a software development team is to obviously develop software but it is also important to learn about how it can maintain a sense of longevity free from error and customer complaints. I will keep the information I learned from this article in mind in future projects and when I’m working with a team to ensure that I’m developing software all the while keeping maintenance in mind. If it is considered during the development process, the maintenance process will be much easier.

From the blog CS@Worcester – Shawn In Tech by Shawn Budzinski and used with permission of the author. All other rights reserved by the author.

Anti-Patterns

Source: https://www.freecodecamp.org/news/antipatterns-to-avoid-in-code/

This article is titled “Anti-patterns You Should Avoid in Your Code.” It specifically mentions six of them, being: Spaghetti Code, Golden Hammer, Boat Anchor, Dead Code, Proliferation of Code, and the God Object. An anti-pattern, in regards to software development, is an example of how not to solve a problem in a codebase. They are not a positive thing, they are examples of practices to avoid in the development process. Anti-patterns lead to technical debt, code that you have to eventually come back to and properly fix later. Spaghetti Code is the most common, it is code that doesn’t have much structure. It is called Spaghetti Code because everything is difficult to follow, files are located in random places, and when visualized in a diagram, it appears to be a jumbled mess, much like spaghetti. Golden Hammer references a scenario where you follow a certain process that doesn’t necessarily align perfectly with the project but still works well enough. This may not seem like a large issue, but is obviously not the best practice to follow because it’ll cause performance issues in the long run. You should always use a process that is the best fit for your project, even if you need to teach yourself or learn something new. Boat Anchor is when developers leave code in the codebase that isn’t actively being used in the hopes of it being needed later and thus not requiring much effort to implement when it is eventually needed. The main problem with this is when it comes to maintaining the code. It leads to the question of what code in the codebase is unused and what is being actively used. Trying to fix a bug in the system on code that isn’t even being used is a time waster. Dead code is code that doesn’t look like it’s really doing anything, but it is being called from many different places. This leads to problems when trying to modify the code because no one is unsure what is actually dead. Proliferation of Code is about objects that have the purpose of invoking a more important object, meaning it doesn’t really do anything on its own. The action of invoking the more important object should be set to the calling object. Lastly, the God Object is an example of an object that does too much. Objects should only be responsible for doing one thing, referencing the Single Responsibility principle in SOLID. 

I chose this particular source because I appreciated the way examples were clearly given along with the 6 examples of anti-patterns, and upon reviewing the syllabus the topic “anti-patterns” seemed interesting. When you’re learning computer science a lot of the time you’re learning about things that you should do and not about things that you shouldn’t do. I really enjoyed reading about these 6 examples of common mistakes that developers make in industry. It’s important to both recognize good and bad practices to ensure that your projects are properly optimized. I can definitely see myself referencing anti-patterns when designing code in the future so my code can easily be maintained. 

From the blog CS@Worcester – Shawn In Tech by Shawn Budzinski and used with permission of the author. All other rights reserved by the author.