Having just read a short keynote address* by Donald Knuth from 1989 about the development of his typesetting system, TeX, I’m struck by how little the core methodology of computer programming has changed in the last thirty years.

Students and new programmers can struggle with the difference in scale between real-world applications and textbook examples. Knuth feels that his typesetting system, TeX, is a useful illustration to beginners because it is a “medium-size” project: small enough for one person to understand given a reasonable amount of effort, but large enough to draw meaningful architecture and design lessons from.

Here, he outlines a number of lessons he took from the process of writing TeX. There’s nine, and they are only discussed briefly here (this is a summary of a much larger paper he wrote, which is simply called “The Errors of TeX.” I think they’re generally all very good, but for the sake of brevity I’m only going to focus on one of them.

Knuth’s first lesson here, which I think is the most important, is that it is not enough to merely specify a design. The implementation isn’t just physically necessary to create the product, but the actual process of implementing it is where the most important information about the design comes from. This seems maybe so obvious that it’s not worth actually saying, but I think it’s important and easy to lose sight of. Looking back on it, I think that personally, my greatest stumbling block in programming is what I would call overdesign. I would sit down and construct a conceptually perfect model in my head, and then it would fall apart on me as I attempted to implement it without me really understanding why.

At the time, anyway. Looking back now, I have a pretty clear idea, and Knuth expresses a similar idea here. The problem is that I viewed implementation as an externality to the design process rather than as one of the most significant components of it. Fundamentally, the purpose of thinking about software architecture is to minimize difficulty in implementation, and so actually writing the code is the most important source of data in the process. For example, it’s one thing to know, vaguely, that Microsoft’s DirectSound library can provide audio playback functionality to an application. But knowing specifically that it needs a ring buffer and understanding all the small, tedious details in setting it up might push you in the direction of architecting your program a specific way, or using a different audio library if you’d rather not. Granted, I guess it’s possible that you might come to the same conclusions simply looking at the documentation, but my mind doesn’t work that way, and I suspect that experience is generally a better teacher.

*Knuth, Donald E. (1989). “Notes on the Errors of TeX” (PDF).

From the blog CS@Worcester – Tom's Blog by Thomas Clifford and used with permission of the author. All other rights reserved by the author.

Hello everyone,

https://dev.to/6figuredev/episode-207-tech-debt-vs-cruft

This podcast in particular talks about technical debt in detail, as well as how to handle it. It introduced me to a term I had never head before called Cruft. Cruft being not traditional technical debt but specifically a type of debt where the developer who wrote the code did not make the effort to make the code clean and or work well. I never made the distinction in my own mind as to consider the possibility that the lack of best practices or simply writing the code wrong could be considered as that type of technical debt.

Now I don’t mean the developer was malicious or perhaps lazy, while it could be considered a possibility it seems to be not a scenario that happens enough to be something that requires a term like that. I also like having that extra terminology as technical debt as a definition can be left to an intentional design choice that leads to the creation of technical debt that most times are made in consensus rather than specifically one user not knowing how to code it or that user writing poorly designed code.

Cruft also gives a more specific term for a business to focus more on as it has the greater debt value for the company when needing to rework your product. If the code is rushed and written poorly, when errors arise the pressure is greater on the development team and will lead to failure or delays.

With Cruft as the core of that perspective on technical debt, regular technical debt can be just the debt that was planned and agreed upon allowing you to release and work on it later.

This podcast also introduced me to another great term that is separate to legacy code. With legacy code it’s old enough that it doesn’t meet the definition of Code Rot. Code Rot isn’t keeping up with older code so old as to be legacy code, but code that hasn’t been touched in a while and isn’t kept up to date with the newer builds and similar code design.

From this podcast it gave me an interesting mindset when thinking about a production cycle and acknowledging technical debt as kind of being inevitable and something to try to plan before sprints as apart of the team and being prepared for it. Cruft is really what I thought technical debt to actually be, because I was only really reflecting on code being written by one person. I for some reason ignored the aspect of working on the development team and it has changed my idea of development. Cruft really is just a more personal or workspace issue. One being fighting against the urge to take the easy way out and the other being a pressure outside what I as a developer couldn’t control but rather a business forcing the cruft to occur by forcing shortened deadlines.

From the blog CS@Worcester – A Boolean Not An Or by Julion DeVincentis and used with permission of the author. All other rights reserved by the author.

          In a previous post regarding containerization, I briefly mentioned the uses of containers regarding application development and deployment prior to specifically learning how to utilize Docker and its containers. I went on to explain how Docker can handle development of applications through the use of images that contain the dependencies needed to be used for development, as well as how Docker also manages data retention between the local host system and the container file system through the use of volumes and mount binds. My learning of Docker started with a focus on local application development and deployment before moving onto utilizing ports to access the running applications through the network via a port number.

          By default, ports in a Docker container are not published and thus cannot be accessed this way, even if the container itself is up and running. This means that if one needs to access an application from port 5000 of the local host, this would not be possible given that such port may have not been published in the first place. Therefore, an important part for deploying web-based applications through docker involves utilizing the container’s ports. Such concept is referred to as “port mapping”, in which case ports of the localhost are mapped to specific ports in the container. This is a useful concept in the case that, during development, multiple containers that are running may need to use the same ports, therefore different ports of the localhost are mapped to that specific port that needs to be used and directing traffic appropriately, thus avoiding any potential port conflicts between containers.

          As I was researching for resources specifically talking about port mapping and port forwarding on Docker containers, I came across the following article named Understanding Docker Port Mapping to Bind Container Ports on LearnItGuide.Net. In this article, the author goes through the process of explaining how to map docker ports by demonstrating how the process is done through the command line by using a basic application and multiple containers as an example. Moreover, they show the multiple ways a port value can be expressed, which ways include either passing the port number directly (thus needing to access the application through localhost:port_number), by passing the IP of the host along with the specified port number that needs to be mapped, or by using automapping and thus mapping a random host port to the docker container. However, it is important to note that port mapping can also be applied using docker-compose YAML files. In an article named Understanding Docker Port Mappings on Dev-Diaries.Com, the author explains how port mapping works when using docker-compose files while showing examples of the ways we can map host ports to docker ports.

          Although there is more to port handling, such as exposing ports to only be accessible to linked services, it is still important to know how ports work in Docker containers in order to properly utilize them in the process of development and deployment.

Direct links to the resources referenced in the post: https://www.learnitguide.net/2018/09/understanding-docker-port-mapping.html and

Recommended materials/resources reviewed related to Docker port publishing:
1) https://www.dev-diaries.com/social-posts/docker-port-mappings/
2) https://betterprogramming.pub/how-does-docker-port-binding-work-b089f23ca4c8
3) https://www.tutorialspoint.com/docker/docker_managing_ports.htm
4) https://www.ctl.io/developers/blog/post/docker-networking-rules
5) https://nickjanetakis.com/blog/docker-tip-59-difference-between-exposing-and-publishing-ports
6) https://riptutorial.com/docker/example/2266/binding-a-container-port-to-the-host
7) https://www.dev-diaries.com/social-posts/docker-port-mappings/
8) https://www.whitesourcesoftware.com/free-developer-tools/blog/docker-expose-port/
9) https://digitalthoughtdisruption.com/2020/09/28/docker-port-mappings/

From the blog CS@Worcester – CompSci Log by sohoda and used with permission of the author. All other rights reserved by the author.

Semantic versioning is a versioning scheme in three parts; major.minor.patch. Patch is incremented with the addition of a bug fix, minor is incremented with the addition of a new feature, and major is incremented when the changes being made are incompatible with previous versions. Though it is among the most popular versioning schemes, Colin Eberhardt explains in a blog post “Semantic Versioning is not Enough” that it is not without issue.

Eberhardt describes that issues may surface when updating the dependencies of a project. There are two ways to update a dependency within a project; passively or actively. Passively updating allows a computer to update the dependency without human intervention while actively updating requires a human to manually update the dependency.

When adding a library to your project, you may specify a range of acceptable versions of that library. This hands the decision of whether to update a dependency to a new version, provided that the new version is still within range. Eberhardt warns that declaring dependencies like this could create different development environments on different machines, where one machine decides that an update is appropriate and another does not. Applications may function differently after even small bug fixes in their dependencies. In addition, passively updating to a version of a library with new features is nearly pointless. You would need to change your code to be able to use those features.

It seems more useful to actively accept updates to a dependency. This is fine for patch updates since these do not require any alterations to your code. However, updating to either a minor or major update would require you to change your code, whether it be to utilize a new feature or to prevent your project from breaking. Eberhardt argues that, because of this, the distinction between a major and a minor update is not useful.

Eberhardt also points out that a major update can often fail to convey the severity of what was changed. A trivial breaking change would increment the same as a rewrite of an entire library. Eberhardt suggests combining romantic and semantic versioning by giving names to more significant changes.

I selected this article because I thought it would be useful to see another perspective. Eberhardt seems to have a lot of experience, and he draws from that experience to write this critique. I still think that semantic versioning is a useful scheme, but it is interesting to see a critique of something so popular. I think the suggestion of naming significant updates in addition to incrementing the major number is a useful one that I will try adopting in future projects.

From the blog CS@Worcester – Ciampa's Computer Science Blog by graceciampa and used with permission of the author. All other rights reserved by the author.

So I’m going to have to be honest with my readers, and also I’m going out on a limb here: I am not the most experienced with Git. This is especially detrimental when I am taking a course that requires regular usage of Git, and that course is a limited time offer. What am I going to do? In my general theme of learning, I am going to practice over and over again until I finally “git gud” (as the kids would say) at Git.

Git is a version control software used to create different “branches” of a project. These branches can be local or remote; they also can “pull” information from other branches, and “push” or “merge” this information back as well. Other important controls include: rebasing, location arguments (such as HEAD) and “status-checking”. These commands, and many more, are used to ensure that software can be created or polished in separate branches while the “main” branch is still operational. When the changes are tested and ready to be added to the program, they can be “merged” back in.

As a way of “branching off” from my traditional form of blogs, I have decided to link a unique source. Instead of an article or a YouTube video, I have linked an interactive tutorial called “Git-It”. This is because I believe that the best way to learn Git is by practicing it over-and-over; similar to a “traditional” programming language, hands-on experience with Git will take a programmer further than any abstract knowledge will. In a nutshell, this tutorial will teach you all the basics needed to understand Git. These basics include, but are not limited to:

1. Creating, modifying and deleting repositories
2. Pulling and Pushing data from other repositories (both local and remote)
3. How to clone material from a remote repository to a local computer
4. Creating and merging branches

Not only is Git going to be essential for completing homework assignments, but it is practically unavoidable in the software workforce. Similar to Singleton/Strategy refactoring, Git allows for different branches to create different implementations, while all still referring to one “global, main” branch. Branches can also be used for various SemVer levels in a project; should changes need to be made, progressing or regressing a project (through committing or reverting, respectively) can be done.

Most importantly, I feel as though Git is a great tool to help me understand the concept of continuous integration. As mentioned before, Git allows for multiple branches of software; these branches can then be “forked” or “cloned” to private servers or local computers. This gives the programmer a copy of the project to work on, while the actual project is still running for its customers. This “language” combined with Docker containers, emphasizes the class theme of being able to work with software on different platforms, thus maximizing versatility.

Link: http://jlord.us/git-it/challenges/get_git.html

From the blog CS@Worcester – mpekim.code by Mike Morley (mpekim) and used with permission of the author. All other rights reserved by the author.

Dr. Cunningham focuses on integrating security into operations; leveraging advanced security solutions; empowering operations through artificial intelligence and machine learning; and planning for future growth within secure systems.

– https://www.youtube.com/watch?v=VBfTpmEyHy0

This video is the Keynote speaker’s presentation for the Raleigh chapter of the Information Systems Security Association for their 2021 fundraising event called InfoSeCon. I used to be a chapter member before I moved here to Massachusetts and I try to keep up with some of their announcements and events from time to time.

Dr. Cunningham was a previous Keynote speaker and to see him return this week on their Youtube channel was exciting. He’s known for being the creator of the Zero Trust eXtended (ZTX) framework which is a framework of network security protocols that prioritize network isolation and continuous monitoring and validation.

This keynote presentation primarily focuses on network security and serves as a reminder of best practices for operating a corporate network while utilizing a zero-trust framework. He uses horror movies as a theme to tie everything together and make it engaging for his audience and I really appreciate the consideration. InfoSeCon took place back in October so it was topical and showed that it wasn’t some canned presentation that he had been giving all year. It really goes to show that one of the largest hurdles to Network Security is just communicating the importance of simple practices and getting your audience, whether it be clients that hire you on to improve their company’s practices or systems or if they’re users already in your network to follow them.

That’s really one of the main appeals of a Zero-Trust framework. Traditionally, network security is treated as an Us vs Them scenario where it’s always something that is being inflicted upon the company rather than the natural conclusions of risky behaviors. ZTX operates differently; it assumes that you can’t trust the end users to know everything you know about what they should or should not do. It encourages the security professionals to segment everything and isolate as much as possible so that when one person unknowingly invites the vampire into the house, we can shut another door in its face and not have to worry about evacuating everybody.

Specifically, he stresses the importance of maintenance within your systems so that older vulnerabilities aren’t taken advantage of and make life harder in the future, to listen to your users, that moving to the cloud is likely the best solution for people dealing with a “haunted” infrastructure, as well as a lot of other really great advice.

While a lot of the best practices are simple and seem like common sense, I always appreciate a reminder so that I don’t make bone-headed mistakes that can cost either me or my employer great sums of money. It’s important as I learn more and more about Software design and architecture that I keep in mind how I could be unknowingly creating vulnerabilities that could be exploited if ever someone decided to try hard enough to find them.

From the blog CS@Worcester – Jeremy Studley's CS Blog by jstudley95 and used with permission of the author. All other rights reserved by the author.

https://www.bmc.com/blogs/docker-101-introduction/#

In the above blog post by Sudip Sengupta, he introduces Docker and gives us a guide on Docker. The blog post goes over application development today, what docker is, it’s components, it’s benefits, and alternatives to Docker. In today’s application development, a common struggle is managing an application’s dependencies and technology stack across various cloud and development environment. By adopting something like Docker or a containerized framework, it allows for a stable framework without adding complexities, security vulnerabilities, and operational loose ends. Docker also makes application development easier by allowing development teams to save time, effort, and money by dockerizing their applications into single or multiple modules. Testing with Docker is also done independently (each application is in their own container) which allows testing to not impact any other components of the application. Docker also helps keep consistent versions of libraries and packages to use during the development process.

I chose this blog post because I was having a hard time in class understanding Docker. I tried to view it as a virtual machine, which was somewhat right, but is actually more efficient than a virtual machine since you won’t have to run a virtual machine and use a lot more resources than needed. Compare that to a Docker container which contains all dependencies, libraries, and config files, Docker would be the much more viable option to use in the long run in my opinion, virtual machines just take too much resources (they require significant RAM and GPU resources since they run a separate OS and a virtual copy of all the hardware the OS requires) and Docker containers, or application containers in general, are more flexible and portable than a VM.

You can see why Docker is being adopted more, it’s because it’s much more efficient and easier to use while developing an application. With this blog post, I’ve learned a lot more about Docker and why it’s used. I thought this was a good blog post because it helped get a better understanding of why Docker is used in application development and helps me familiarize myself more with technology I’ll most likely be using when I get a professional job and start developing applications with a team. In the future, I expect to have to learn more Docker or application containerization in general for my job as a software developer and having the knowledge of Docker beforehand and why developers use it, is very useful.

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

https://swagger.io/resources/articles/best-practices-in-api-design/

The article I’ve chosen is based on Rest API Design, a topic that we are currently working on in class. Many important parts of Rest API Design are talked about throughout the article some of them being Rest API Design characteristics, collections and their resources, HTTP methods and more. According to the article a good api should be easy to read, complete/concise and hard for a user to misuse which is all important not only for integration of the api but also when using an api with any kind of application that it was designed for. Collections, resources and URLs are also very important to designing an effective Rest API as collections and resources allow the passing of data throughout the API and its functions. Using the proper URL helps you manipulate which data is shown at a specific time whether its the data of a specific user or an error code.

Describing the purpose or function of resources is also very important and it is done through the use of different HTTP methods. The methods listed in the article include get, post, put, patch and delete. Each of these HTTP methods is used to retrieve, create, update or delete resources. ANother way to develop a good rest API according to the article is by providing feedback for users by implementing error codes when the API is used incorrectly whether there is error in an entry by the user or if the user uses the incorrect operation when entering data. The responses you provide or error codes can help users and yourself understand your API better which will also help you when testing the functions of your API so you know how any commands or entries should be formed during use. The author also highlights that using examples in your get methods is important as it shows exactly what the user can expect when they “successfully call the API function”.

I chose this article as I found it helpful with our current class topic and it outlines all the basics of Rest API design and helps student developers like myself and my classmates better understand how to effectively design a Rest API. This article helped me understand the use of HTTP methods further as well as the importance of examples and resources which helps greatly with our current class subject. The article helps put the design of Rest API’s in an easily presentable state for students or other people in general who are interested in developing such an API.

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.

Docker is an open source technology which enables the easy use of containers for software development. Steven J. Vaughan-Nichols, in his article “What is Docker and why is it so darn popular?”, writes that “… over 3.5 million applications have been placed in containers using Docker technology and over 37 billion containerized applications have been downloaded.” Needless to say, Docker is quickly becoming industry standard with “… almost 40 percent market-share growth in 12 months.” For anyone looking to get into software development, it is an absolute requirement to learn how to use Docker or something very similar.

Docker containers attempt to copy a virtual machine setup without actually running an entire virtual machine. The main difference is that Docker containers all run on a single operating system instead of emulating multiple different operating systems. This allows for much more efficient usage of resources, and it is estimated that between four and six times as many applications can be run on a Docker system as opposed to the traditional virtual machine setup.

One major reason why Docker is so versatile is that it allows your project to be packaged with all of its requirements on the container; because of this you would not need to pre-install dependencies on each machine you wish to run your application on. This also allows you to run your applications on cloud services very easily; in fact, Docker is specifically tailored to run on cloud services such as Puppet, Chef, Vagrant, and Ansible.

Since Docker is easily integrated on cloud servers this means that it is also easy to emulate a live server build. When a developer wants to test a change on a live server they can simply run a container which is set up in the same way as a live container. These containers can be tested very fast and safely, and it is reported that developers who used this method had “three times lower rate of change failure”.

Personally, I believe Docker is the future of software development. There are many benefits to using Docker with very few drawbacks, if any. Although Docker may take some time to learn and get used to, it most certainly will make developers’ jobs much easier in the long run. I anticipate that Docker will quickly become industry standard due to the many benefits listed above. Docker is a great software which will allow designers to run more applications, on a multitude of different machines, with quick turnaround on updates and fixes.

From the blog CS@Worcester – Ryan Blog by rtrembley and used with permission of the author. All other rights reserved by the author.