This week, I am going to provide some insights/opinions regarding the practicality of some clean code principles, along with an example of when over-optimization for the sake of readability might actually be counterproductive. The resource I will be referencing this week can be found here. This article documents many of the same clean-code principles we discussed in class, plus or minus a few. For each principle, it provides an explanation as well as a coded example to demonstrate the principle and/or the difference between good and bad code according to the principle. I chose this article because I felt it was comprehensive enough to cover the key points for clean coding, and because I tend to use many of the principles outlined in the article in my own code.

I am currently involved in a project where the Single Responsibility Principle (SRP) might actually be counterproductive to my primary objective. In general, I tend to agree with this principle, and I understand its benefits well. It makes code far easier to read and follow, and, as we discussed in class, modern compilers can optimize functions to where there is almost no difference in execution time by offloading logic into its own function.

My program runs an ultra-fast search on a set of numbers (speaking very loosely), and needs to update numbers around 250 times per second. Thus, my time to find what I am searching for and act on it is ~4ms before all the data is useless (think: cracking Enigma in The Imitation Game). Now, factor in that I need the majority of the ~4ms to actually execute based on my search result, and one arrives at the conclusion that the search needs to take <1ms (or as little time as possible). Now to my point: sometimes, to accomplish this, I found that I had to violate the SRP. This means that I call search(), and search() immediately calls execute() if it finds what it’s looking for, eliminating the time it would have taken to return the value to main() and then pass the value back to execute(). This is obviously a miniscule difference, but in my testing and gathering data, I found that when multiplied out to larger and larger numbers, this little hack shaved off a noticeable amount of time.
This might all be more related to Command-Query Separation or the “No Side Effects Principle” than it is to the SRP, but my points still stand. What I am getting at in the big picture is that these principles, while applicable and preferable a massive portion of the time, are not always the right way to go. Sometimes, you have to sacrifice one or more in pursuit of your primary objective. All this said, my largest takeaway going forward is that I should remember and implement clean code principles whenever/wherever possible, but I will always try to remember that they are not law, and sometimes variance is necessary.

From the blog CS@Worcester – Mr. Lancer 987&#039;s Blog by Mr. Lancer 987 and used with permission of the author. All other rights reserved by the author.

This week, I am going to be chatting about the benefits of Humanitarian Free and Open-Source Software (HFOSS). Prior to class this week, I was familiar with open-source software, as I have previously integrated some open-source projects into personal projects, but I had never heard of HFOSS specifically, and had not given thought to the potential benefits of popularizing HFOSS development in an educational environment. Instead of referencing a blog this week, I am going to look at an actual HFOSS project that can be found here.

Crisis Cleanup is a platform designed to connect volunteers with individuals affected by disasters, particularly during and after events like hurricanes. This project is a perfect example of HFOSS, demonstrating how collaborative, community-driven software can make a meaningful and real impact.

One of the coolest parts of this HFOSS project is its emphasis on community engagement. Crisis Cleanup operates on the principle that local volunteers can provide the most relevant and timely assistance to those in need. By facilitating connections between volunteers and those affected, the platform enables random people to help in ways they probably otherwise couldn’t. Combine this with the fact that anybody can contribute, and now there is a unique opportunity to create a learning environment for students. Contributors can gain practical experience in software development, project management, and user interface design while working on real-world challenges. Students can also witness the immediate impact of their contributions, reinforcing the idea that their work can lead to tangible change. As we discussed in class, this seems to raise interest/appeal in computer science in groups that are otherwise generally less interested in it, which is an awesome way to get more people involved in the field.

Crisis Cleanup also highlights the importance of adaptability in software development. During a disaster, the needs of affected individuals can change rapidly. HFOSS allows for quick iterations and updates based on feedback from users and volunteers on the ground. This agile approach to software development ensures that the platform remains relevant and effective, which is crucial for a disaster relief program in particular. I think another really cool thing about this HFOSS project (and HFOSS in general) is that the Agile methodology is generally used. It makes sense; Agile is not exclusive to professional software development teams, but to see it used or even suggested for an open-source project is not what I would have guessed at first.

Personally, I have always had an interest in Computer Science, regardless of my awareness (or lack thereof) of HFOSS. I have not yet contributed to any projects of that nature. Moving forward, maybe I will find one to contribute to on my own, now that I know how much they can help people. Overall, I think they are an excellent way to learn/enter the field of Computer Science, and I would love to see more educational environments centered around HFOSS development and projects like the Crisis Cleanup project.

From the blog CS@Worcester – Mr. Lancer 987&#039;s Blog by Mr. Lancer 987 and used with permission of the author. All other rights reserved by the author.

The part of the “Apprenticeship Patterns” textbook by David H. Hoover and Adewale Oshineye that I find myself flipping back and forth through the most is the fifth chapter, titled Perpetual Learning. I’m planning to depend on my skills in software craftsmanship to establish a stable career and earn enough money to finance my other pursuits in life, and consequently I need to think seriously about nurturing my foundational skills and refining my learning process.

I’m taking a course this semester that has me relearning C++, a language that I haven’t used in several years. I had been programming almost entirely in Java since beginning Worcester State University’s Computer Science program, and the material of this course is requiring me to jump right back into the deep end of C++. I find myself unsure whether my approaches to certain challenges are correct or not, as well as feeling more concerned with whether my code will compile instead of whether I am learning the tools of the C++ language effectively.

When I want to truly absorb some kind of knowledge, I’ve realized that I learn something best when I receive positive feedback when I demonstrate my skills properly and correctly. When I wanted to learn how to play the guitar when I was younger, the first thing I tried to learn was the start of “Breaking The Law” by Judas Priest. The positive feedback I got from learning that part was hearing sounds from the guitar that I was playing that sounded a lot like actual music! After that, I couldn’t stop myself from learning how to be a better guitar player because of how much I wanted to keep myself in that positive feedback loop. I kept learning, I sounded better, and the feedback loop has been growing more rewarding as time goes on. I’m confident that lots of other people can relate to this experience, even if the thing that they were trying to learn wasn’t music or playing an instrument. Being able to gauge your own progress through positive feedback benefits the learning process dramatically.

This pattern is concerned with creating that same kind of positive feedback loop within the context of software craftsmanship. Seeing the quality of your output increase in proportion to your effort in learning can be the fuel that keeps a programmer engaged in refining their craft. The pattern is introduced with a quote from Jerry Weinberg’s “Project Retrospectives”:

“We in the software industry are working with a more or less invisible product, yet this very invisibility only heightens our need for feedback.”

It feels difficult for me to decide “where I am” as a programmer without comparing myself to the people around me. That approach takes my focus away from my own growth however, and I want to avoid it. So instead, the solutions proposed by this development pattern include researching test-driven development and using interactive interpreters that can let the programmer catch errors and see outputs as they write code. The programmer also has the option to intentionally reach out and seek feedback on their coding process from peers and mentors, or by participating in pair programming. A given example of applying this pattern in the real world is asking the interviewer for a position that you were not accepted for why the company didn’t want to bring you on board. This is a more positive framing of what could be a rather upsetting situation, and an outside perspective can also give you insight into aspects of your work and yourself you hadn’t paid attention to.

The key to collecting all this data is to construct useful and actionable feedback for yourself. The pattern defines “useful feedback” as feedback that you can do something in response to that informs you whether to do more or less of a certain behavior. The textbook challenges the reader to put this pattern into action by identifying a metric in their working environment that they have the capacity to change and measure. Then, use the measurements of that metric to try and understand how your actions have changed your “working environment”.

Reflecting on this pattern has made me realize that I have rarely, if ever, sought out external feedback for projects that I’ve worked on outside of school. I’ll write code, compile it, and push it to my Github, but I’ve never made the effort to construct testing suites or seek external criticism from other programmers. These habits have enabled a feeling of doubt to sprout within me about whether my code could be adapted to perform a useful task, or whether I’m actually making any progress in my learning. I’ve started thinking about the advice proposed by this development pattern, and I’m going to take the time to read “Test-Driven Development: By Example” by Kent Beck, the reading material sourced in this pattern. I’m also going to research the features of Visual Studio, my preferred text editor, to see if there are any extensions that allow for the features offered by interactive interpreters.

I’m not sure that I understand the pattern’s advice about “gathering metrics to understand the effects of your changes to your working environment”, but the practical advice of using software tools to provide feedback as you work as well as inviting constructive criticism from others makes perfect sense to me. The pattern also urges the learner to put themselves in situations conducive to building these feedback loops. I think that some of the strongest fuel for those feedback loops are the relationships we create with others along our learning journey, and in the online realm of software development, I don’t think it would be hard to find a community of developers eager to forge and fully energize those feedback loops.

From the blog CS@Worcester – Michael&#039;s Programming Blog by mikesprogrammingblog and used with permission of the author. All other rights reserved by the author.

Summary:

The pattern “Nurture Your Passion” addresses the struggle faced by software developers whose passion for their craft is hindered by the work environment. Often kept to “simple” tasks or faced with demoralizing conditions like corporate hierarchies or project death marches, developers find it difficult to maintain their enthusiasm. However, the pattern suggests several strategies to protect and grow this passion.

Reaction:

The pattern could be related to deeply with many software developers who have found themselves in similar situations. It highlights the importance of preserving one’s love for the craft amongst challenging circumstances. What’s really interesting is the acknowledgment that not everyone has the privilege to earn a living through their passion, making it important to safeguard and nurture it.

What’s Interesting and Useful:

The emphasis on working on tasks that align with personal interests stands out as a practical approach. By dedicating time to activities that spark joy, developers can reignite their passion and find fulfillment in their work. Additionally, the idea of seeking out like-minded individuals and immersing yourself in the classics of the field serves as a reminder of the rich heritage and community support available in software development.

Impact on Professional Outlook:

The pattern encourages a reevaluation of how someone approaches their career in software development. It makes individuals prioritize environments that support their growth and passion, even if it means diverging from conventional career paths. Setting clear boundaries and maintaining a sense of wonder about programming, as said by Paul Graham, becomes essential for long-term satisfaction and success in the field.

Disagreements and Reflections:

While the pattern offers valuable insights, some may find it challenging to implement certain suggestions, especially in highly demanding work environments. Setting boundaries and steering conversations towards positive topics require courage and confidence, which may not always be feasible depending on organizational culture and power dynamics. However, the underlying message about the importance of preserving one’s passion remains relevant.

In conclusion, “Nurture Your Passion” serves as a reminder that maintaining enthusiasm for software development is a deliberate effort, especially in the face of adversity. By embracing strategies outlined in the pattern and staying true to their passion, developers can navigate challenges and thrive in their careers.

From the blog CS@Worcester – Site Title by rkaranja1002 and used with permission of the author. All other rights reserved by the author.

In this week’s blog post, I will be discussing the “Long Road” pattern discussed in chapter 3 of “Apprenticeship Patterns: Guidance for the Aspiring Software Craftsman” by Dave Hoover and Adewale Oshineye. This week, I chose this topic for my blog post because I often worry about not being able to learn or grow more in my field, becoming stagnant because there is nothing else I can learn. Thankfully, this pattern dissuaded those fears of mine and inspired great confidence in my future endeavors.

The quote that this pattern opens with immediately puts much of my concerns about the limits of what I would be able to learn to rest. “‘How long will it take to master aikido?’ a prospective student asks. ‘How long do you expect to live?’ is the only respectable response.” In comparing computer science to Aikido, it implies that no one can possibly learn all that there is to know in computer science. Another quote from this section that makes me even more excited to be a part of this field mentions that for every step you make, the finish line is two steps further away. “For every step you take toward mastery, your destination moves two steps further away. Embrace mastery as a lifelong endeavor. Learn to love the journey.” While this may seem like a disappointing aspect of our field for many, the limitless opportunity for me to grow is why I love this field of knowledge.

I did not think it was possible, but further reading in this section made me even more excited and proud to be in computer science. “Close your eyes and imagine the strangest possible role you could be playing in 10 years’ time. Have fun thinking of the wackiest possible future for yourself. Then think about 20, 30, and 40 years from now. What kinds of experiences do you want to have tried? Imagine that 40 years from now, you are asked to write a short description of your professional history and the biggest influences on your path. Use the output from that thought experiment to help you plan your future career choices.” This quote had me thinking about incredible and outlandish possibilities in this field, which made me even more eager and excited to be in this field than I thought possible.

From the blog CS@Worcester – P. McManus Worcester State CS Blog by patrickmcmanus1 and used with permission of the author. All other rights reserved by the author.

As my journey to becoming a full stack developer continues, I have begun to encounter the need for front-end testing. When finding an article, I realized that I did not have very much knowledge on what front-end testing entailed or how to implement it into my coding. I found the blog “Front End Testing: A Comprehensive Overview” by Kiruthika Devaraj (https://testsigma.com/blog/front-end-testing/) on my search for information on this topic.

The blog starts off by explaining that front-end testing is focused on the user’s experience. While past experiences have taught me that back-end testing specifically tests the functionality of the code, front-end, also known as the user-facing end of a website, testing has a higher focus on the user’s interactions. The author also delves into eight different types of front-end testing and the elements that make up these different types:

• Unit Testing is the analysis and testing of the individual components to ensure they each work as intended. 
• Acceptance Testing involves testing to ensure permissions, such as account accesses, are working properly. 
• Visual Regression Testing tests for visual changes in the front-end by comparing a reference picture to a baseline image. This can typically create brittle tests that can fail due to the slightest changes in an element’s location on a page.
• Performance Testing measures an applications stability and responsiveness under different levels of simulated stress and traffic.
• Accessibility Testing ensures that individuals with visual impairments or other additional needs can still use and access the application to the fullest of their capabilities.
• End-to-End (E2E) Testing involves testing the application from start to finish while testing all components and systems for how they work together.
• Integration Testing is when each individual module is tested to ensure it has been implemented correctly.
• Cross-Browser Testing tests that the application works correctly across multiple browsers and confirms compatibility.

Devarj also provides tips for better front-end testing, the first tip is to always use a testing framework. These frameworks, also called front-end tools, are what actually run the tests. Although countless front-end tools exist, the blog provides information to 3 popular options; Testsigma, Selenium, and Ranorex. Testsigma and Selenium are both open-source front-end testing frameworks that may be worth investigating further, while Ranorexis a commercial framework that may be more than what I am currently looking for. 

Front-End Testing Moving Forward

As I move to implement automated front-end testing into my projects, it is important to remember that the front-end testing is focused on ensuring the project is user-friendly, responsive, and visually appealing by testing the layout, design, and functionality across multiple browsers. Doing so will provide users with the best possible experience.

From the blog CS@Worcester – CS Learning by kbourassa18 and used with permission of the author. All other rights reserved by the author.

The ‘sustainable motivations’ pattern is all about development in the real world and how it can be very challenging as an apprentice to get used to the reality of software development. Development of your own technical skills is very important as you gain more experience working with customers and with a different variety of products. As it is described you may have a different reason which motivates you to continue in your programming job whether it be that you are motivated for the money, motivated to build reputation or motivated by your own enjoyment of programming. THis pattern is a part of the “long road” chapter which is characterized as being a part of the “long road” from apprentice to journeyman to master within the software development field.

The solution to this proposed problem is to not get “trapped by your motivations” and a way to do that is to write down things you are motivated by and be able to separate the things that motivate you from the things that are what others see or think. Motivation is something that is important in any career but software development requires a lot of motivation as times when developing is strenuous or when you have a long project ahead of you.

I find this pattern to be important as I feel that a lot of people struggle to maintain motivation in all careers worldwide, not just software development. So having a strategy to combat low levels of motivation and also try not to burn yourself out by being too motivated is very important. Many situations will present you with long projects where you need to be able to ‘sustain motivation’ this is especially important to software development as many times you will be faced with longer projects which will need your full attention throughout. Reading about this pattern makes me realize that it is ok to not always be fully motivated whether that is because of the length of a project or if it is due to your working environment, you shouldn’t expect to always be fully motivated but you need to be willing to persevere even when a project takes a lot out of you as it will further you within your craft.

From the blog CS@Worcester – Dylan Brown Computer Science by dylanbrowncs and used with permission of the author. All other rights reserved by the author.

https://testsigma.com/blog/levels-of-testing/#:~:text=The%20most%20common%20types%20of,system%20testing%2C%20and%20acceptance%20testing.

Different levels of testing software is very important when it comes to quality assurance and each of the different levels is based on different combinations of things that help ensure the best conditions and functionality of your software. The four different levels of testing are as follows: “Unit Test” which tests an individual component, “Integration Test” which tests an integrated component, “system Test” which tests the entire system and “acceptance Test” which tests the final system otherwise known as the final product.

Unit Testing is used to outline the expectations of a program or outline its functionality which in essence makes sure that certain parts of the program function as intended. Integration testing allows you to test groups of functions to make sure that they interact properly with each other which is a step above unit testing. System testing is similar to integration testing as it tests a ‘group’ of functions but this group is now comprised of every part of the program/application. Acceptance testing then tests all functional and non functional aspects of the program in order to ensure proper functionality, security, etc.

I selected the levels of testing as a topic as it directly relates to the types of testing we have been doing in class. We have been testing functionality of different bodies of code so far during this semester and we have used different techniques including but not limited to equivalence class testing, edge case testing, worst case testing, boundary value testing, etc. I would say that most if not all of these testing types would fall under the unit testing level of software testing as we have for the most part testing individual system components being able to learn about the different levels of testing makes me excited to continue on through the levels of testing.

This source was very helpful when it came to learning about the other levels of testing we have not used during class yet and I would recommend this article to any of my fellow students although this article does not go extremely in depth when it comes to the different levels of testing it does give you a good general understanding of each level so that you can go on to learn more without getting confused between the different levels of testing. The diagrams and explanations of the software sequence are valuable resources for a software testing course.

From the blog CS@Worcester – Dylan Brown Computer Science by dylanbrowncs and used with permission of the author. All other rights reserved by the author.

Boundary testing is a technique that “involves evaluating data based on boundary values… such as minimums and maximums.” It involves testing the lower and upper limits of a domain of inputs, as well as values just inside and outside those limits. This technique helps improve software quality by detecting defects early in the development process, which ultimately saves time and resources. This is due to the fact that “the number of defects at the boundaries of an input domain tends to be higher than in other areas of the domain.” 

Going back to how it saves time and resources, it helps developers choose more efficient test cases, which cuts down on time and how much they have to do, especially with large sets of data and number of inputs to consider. Furthermore, this technique “allows for a lot of uniformity and the test cases are much smaller” meaning that it can be automated. This would save more time, possibly result in less errors than if a person were to write the test cases, and allow for developers to put their focus on other tests or somewhere else, resulting in increased productivity. 

Boundary testing involves determining the input value range, which is whatever values the system accepts. Values inside that range are valid while those outside are invalid. Test cases are then created based on the values at the extreme ends, end values, and values just before and after the end values. For example, with a range of 0 to 100, we test values less than 0 (-50), greater than 100 (150), values around and at 0 and 100 (-1, 1, 99, 101). 

Another example the article shares is one that allows users to create a password. The password has to be 5 digits meaning that the range is 10000 at minimum and 99999 at maximum. Any combination of numbers is valid as long as it is 5 digits long, meaning that 4 digit long and 6 digit long passwords are outside the range and are invalid. 

Boundary testing seems like a very useful testing technique with very little downsides. It’s a black-box testing technique which usually means that testers don’t need extensive knowledge of coding, computer science, or the system at hand. It also seems very easy to do as long as all the necessary knowledge for testing is provided. Seeing as how it can also be easily automated, it may be more efficient to focus on more complex or time-consuming testing techniques while this test is running in the background or on the backburner.

https://www.indeed.com/career-advice/career-development/what-is-boundary-testing

From the blog CS@Worcester – Kyler&#039;s Blog by kylerlai and used with permission of the author. All other rights reserved by the author.