Category Archives: Week-15

Coupling and Cohesion

This week I wanted to learn more about coupling. The article I found happened to be about both coupling and cohesion.

Coupling and cohesion are both terms that refer to the modularity in a system. They help measure how complex the design of an object-oriented system is. Good knowledge of both is needed to build scalable systems that can be extended and maintained over time.

Coupling is how interdependent software modules are. With high coupling, software modules are very independent, and they need each other to run. There are several types of coupling:

  • Content coupling — this is a type of coupling in which a module can access or modify the content of any other module. When a component passes parameters to control the activity of some other component, there is a control coupling amongst the two components.
  • Common coupling — this is a type of coupling in which you have multiple modules having access to a shared global data
  • Stamp coupling — this is a type of coupling in which data structure is used to pass information from one component in the system to another
  • Control coupling — this is a type of coupling in which one module can change the flow of execution of another module
  • Data coupling — in this type of coupling, two modules interact by exchanging or passing data as a parameter

Cohesion is how intra-dependent a software module is. High cohesion is a software module that forms its own meaningful unit. There are also different types of cohesion:

  • Co-incidental cohesion — this is an unplanned random cohesion that might be a result of breaking a module into smaller modules.
  • Logical cohesion — this is a type of cohesion in which multiple logically related functions or data elements are placed in the same component
  • Temporal cohesion — this is a type of cohesion in which elements of a module are grouped in a manner in which they are processed at the same point of time. An example could be a component that is used to initialize a set of objects.
  • Procedural cohesion — this is a type of cohesion in which the functions in a component are grouped in a way to enable them to be executed sequentially and make them procedurally cohesive
  • Communicational cohesion — in this type of cohesion the elements of a module are logically grouped together in a way that they execute sequentially and they work on the same data
  • Sequential cohesion — in this type of cohesion the elements of a module are grouped in such a manner that the output of one of them becomes the input of the next — they all execute sequentially. In essence, if the output of one part of a component is the input of another, we say that the component has sequential cohesion.
  • Functional cohesion — this is the best and the most preferred type of cohesion in which the degree of cohesion is the highest. In this type of cohesion, the elements of a module are functionally grouped into a logical unit and they work together as a logical unit — this also promotes flexibility and reusability.

Tight coupling makes maintenance difficult as all the components depend on each other.

This article was helpful in explaining these two concepts. As we develop increasingly complicated software in our courses and careers it is important to learn more abstract concepts. These were things I have never really thought about before. Usually I write code just so that it works. If I am going a step further I might try to make it “look good” and be neatly indented with as few lines as possible. Especially going into the capstone course, I will have to evaluate my code for things like low coupling and high cohesion.

https://www.infoworld.com/article/2949579/design-for-change-coupling-and-cohesion-in-object-oriented-systems.html

From the blog CS@Worcester – Half-Cooked Coding by alexmle1999 and used with permission of the author. All other rights reserved by the author.

Code Smells

For this post, I wanted to talk about code smells. I picked this topic since it was related to my software construction course, and I believe I could benefit from diving into it some more. In my course, I feel like I learned much more about design smells, but not as much relating to code smells. A code smell is a characteristic or surface indication that shows there may be a deeper underlying problem with a code. Typically, they’re easy to spot, but I wanted to learn more techniques to look for these problems. In the past, I’ve discussed refactoring, and this ties into that nicely. Learning more about code smells will allow me to become better at refactoring. In order to learn some more about code smells, I listened to episode 88 of the Complete Developer Podcast which was all about code smells.

In the podcast, the hosts discuss what code smells are, as well as methods and techniques to find code smells. I was already familiar with some of the smells mentioned in the podcast, which makes sense. I’ve been guilty of many of these as I first started learning code. Naturally, as you learn to code, refactor, and improve, you start picking up on some code smells, even if you don’t have an exact word or phrase for what the code smell is. I was much more interested in the podcast when they started discussing object-oriented smells, since this is much more relevant to what I’ve been studying most recently.

The most interesting smell I thought the hosts discussed was the Refused Bequest smell. Simply stated, refused bequest can occur when a subclass only uses a portion of properties and methods inherited from its parents. Unneeded methods can go completely unused or in some cases, give off exceptions. This is something I had never given much thought to, but it makes sense after hearing the hosts discuss it. I usually try to reuse my code as often as I can, so I could see myself making this type of error where I try to tie classes together through inheritance just to reuse my code. I’ve learned about delegation and using it rather than inheritance, but it’s not something I’m as comfortable with as I’d like. This segment in the podcast led me to go back and study delegation some more to improve my grasp on it.

Code Smells Part 1

From the blog CS@Worcester – Derek's Design by dereksspace and used with permission of the author. All other rights reserved by the author.

SOLID Design Principles

This semester, I spent a lot of time learning about object-oriented design. As my interest grew, naturally I wanted to learn more. In order to better my understanding of object-oriented programing, I listened to episode 142 of the Complete Developer Podcast on SOLID Principles. This podcast talks about about each of the 5 core principles of SOLID and how they’re implemented. The focus of SOLID is to make maintaining and extending code easier as a project grows. Proper use of SOLID design principles attributes to low coupling, high cohesion, and high encapsulation. It also helps to cut back on the need of refactoring, as well as avoiding code smells. SOLID stands for Single Responsibility Principle, Open-closed Principle, Liskov Substitution Principle, Interface Segregation Principle, and Dependency Inversion Principle.

The podcast reflects that SOLID design principles aren’t mandatory law, but rather should be utilized whenever they can to help improve code. The allow the code to be more flexible, but increase the complexity of the overall code. Personally, I felt that the Single Responsibility Principle was the most significant principle discussed in the podcast. To simply describe this principle, SOLID founder Robert C. Martin describes it as “A class should have one, and only one, reason to change.” In turn, following this principle can make software easier to understand and implement. Personally, this is something I tend to follow most of the time. However, there are times that I’ve tried to fit too many functions or responsibilities in a class. It doesn’t necessarily break the code, but I understand how it could make it harder to build off as the project grows.

I felt that many of these design principles tied into one another nicely in one way or another. For example, I could see a clear correlation between the Open-Closed Principle and the Single Responsibility Principle. The main idea behind the Open-Closed Principle is that objects and entities should be open for extension but closed for modification using object-oriented features such as interfaces, subclasses, and inheritance. While Single Responsibility Principle allows for modification to fix bugs, it explains how code can still be extended so long as each class has one sole responsibility. In this regard, I felt both design principles key emphasis is to avoid needless complexity. I think having this understanding now would have been beneficial for some of my prior classes, but I’m excited to have further knowledge of these tools to use in the future.

SOLID Principles

From the blog CS@Worcester – Derek's Design by dereksspace and used with permission of the author. All other rights reserved by the author.

MongoDB and NoSQL Databases

            In our practice with REST API backends, multiple times we ran into MongoDB usage, as the database we were using for the API was MongoDB. My only previous experience had been SQL/SQLite, so I wanted to know what the difference was. I came to find out there is a world of difference, in fact MongoDB is a NoSQL database (NoSQL meaning… well exactly what you would expect it to mean). I found an article – part of a MongoDB tutorial – from Guru99 called Types of NoSQL Databases, What is & Example which dove into the differences and usefulness of MongoDB and other NoSQL databases. Chiefly, NoSQL DB’s do not require fixed schemas, avoid joins, and are easy to scale, which is perfect for distributed data storage and “scaling out”, which is becoming increasingly essential in the CS world. The lack of schema is convenient too, as it allows for “heterogeneous structures of data in the same domain,” providing for great versatility. The other essential parts of NoSQL include it being non-relational and having a relatively simple API. The four kinds are Key-value pair based, column-oriented graph, graph based, and document oriented. Key-value pair based means data is stored in pairs (with a key and a value), which is optimal for large datasets and heavy loads. Column-based means that work is done on separated columns with values in single columns being stored contiguously, performing well with aggregation queries. Document-oriented DB’s (MongoDB is one) also function as a key/value pair, but in this, a value is stored as a document, which is stored in JSON or XML. It is not optimal for high performance or aggregate structures, like Key Value or Column Based. Graph based stores entities and relationships between them. Each entity is a node and each relationships is an edge, defining the relationship. This is different from relational DB’s inn that Graph DB’s are “multi-relational.” NoSQL DB’s commonly query with a key and a GET request. The CAP theorem is also important to NoSQL because it guarantees at most two out of the following three: consistency, availability, and partition tolerance. This is a key limitation of NoSQL DB’s. The last key to NoSQL falls on the concept of eventual consistency, meaning that changes to data on one machine must be reflected on other replicas eventually. Where the standard for RDBMS is ACID, NoSQL is BASE: Basically Available, Soft state, Eventual consistency. The article goes on the list advantages, disadvantages, and summarize itself before coming to a close. I thought this was very interesting to learn, as I can see how different DB styles can reflect the needs of a project or client story. I wasn’t sure why we were using MongoDB; I kind of took it as a given. But this reading broadened knowledge, so now, if I am able to build a REST API of my own over the upcoming break, perhaps I can find the optimal DB for my needs, or help me better understand future projects once I join the workforce.

From the blog CS@Worcester – Marcos Felipe's CS Blog by mfelipe98 and used with permission of the author. All other rights reserved by the author.

Code Smells

https://blog.codinghorror.com/code-smells/

This blog post will center on code smells which was a topic covered in class fairly early on. The reason why I’m going back to it is mainly to refamiliarize myself with the subject since it wasn’t a major topic in class. Code smells are defined by the blog post linked above as general warning signs in code, hence the name. There are different types of code smells that signify different coding problems. For example, long comments, long methods, overly large classes, duplicate code, dead code, inconsistent naming, uncommunicative naming, et cetera. Keep in mind that these issues won’t necessarily stop a program from running, rather they negatively effect on the performance and design levels. Also, all of these different types of code smells share the common trait of not quite looking right when looking at a larger scale. So at first glance the code might seem fine, but given a closer look the flaws whether it be dead code, inconsistent naming, or whatever become readily apparent.

A code smell isn’t something concrete like a detailed recipe, it’s more abstract than that. It similar to a suggestion or a tip and can lead to improving code both on a functional level and a design level. Take for example, noticing the code smells of long comments and dead code which suggest removing the useless code and either simplifying or outright deleting the comments. This will make the code more readable which also improves it on a design level. On the other hand, noticing the code smells of duplicate code and long methods and correcting each issue accordingly will improve the code on a performance level top of the possible design improvements. All of the types of code smells that I listed earlier still hold true but they act as more of a general guideline. There are some scenarios in which some smell types blend together such as long methods and overly large classes to name one. Detecting code smells isn’t going to always be the same in that what someone is looking for will differ every time and the outcome will also differ every time. This process is kind of like trying to find freshly spoiled food; sometimes it looks fine and sometimes you won’t know what exactly you’re looking for. But what you do know is that something smells off and you probably don’t want to risk the chance of getting sick.

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

REST API Design Practices

What is REST API? - Seobility Wiki

For many assignments in a recent class, I had the opportunity to use and learn about REST (Representational State Transfer) API in relation to simple web applications. In working with REST, I was unsure about some of the syntax and conventions used with the API, namely the difference between different response types (JSON vs String response for instance).

I looked into finding some more information on good practices for REST API projects, and according to a helpful blog post I found on Stack Overflow (https://stackoverflow.blog/2020/03/02/best-practices-for-rest-api-design/), REST APIs should generally both request and send responses with JSON (JavaScript Object Notation). I had a number of issues with sending and receiving data which was not in this format (needed to send/receive strings in POST methods within an endpoint). This was causing problems such as information not being sent and received properly (name field of an item not being sent or received in the right places) as well as issues with the functioning of the web application itself (endpoints belonging to unrelated services would cease to function properly if the requests and responses were not JSON.

Furthermore, according to the author, JavaScript has baked-in methods to handle interacting with JSON entities, which makes it easier to use overall especially if there are other JavaScript based technologies being used within the structure of the project, so it makes sense to use JSON within requests/responses. So in future projects involving REST, I will attempt to primarily use JSON objects for responses and requests to ensure compatibility and easy access through JavaScript.

Another point which was discussed was the importance of using nouns in naming conventions, rather than verbs (specifically nouns which are highly representative of the destination or object being affected) when naming endpoint paths. IE: instead of POST: /orderPizza/, use POST /order/ when trying to create a new order. This makes sense, as the HTTP methods typically describe the action or verb being enacted on an object, so you needn’t describe that within the endpoint path.

Finally, I want to discuss the topic of HTTP status codes; the author of this article describes the meaning of many common error codes and why you might return them as a response. This was especially helpful for me as I had been using these codes within a REST project, but had no idea what the majority of them actually meant. According to the article, a code of 400 indicates a client-side validation error, 401 represents an authorization or permissions error, and 404 represents an inability to find a particular resource. Out of all of these errors, 404 is definitely the most common from my experience. I have frequently seen this while using the internet whenever a page would couldn’t be found on a website/web application, it was pretty neat to learn more about.

What is a 404 Page? - Learn to code in 30 Days
Example of a common 404 not found error page

Overall, after reading this article I feel more informed about the way REST API services work, and will be more prepared for the next project I work which makes use of the framework.

Post Referenced: https://stackoverflow.blog/2020/03/02/best-practices-for-rest-api-design/

From the blog CS@Worcester – CodeRoad by toomeymatt1515 and used with permission of the author. All other rights reserved by the author.

AngularJS

This post today is about AngularJS based off of the article AngularJS-Overview by TutorialPoint. AngularJS is a structural framework for dynamic web applications that was developed in 2009 by Misko Hevery and Adam Abrons. Its latest version 1.2.21 is now maintained by Google. AngularJS lets you use HTML as a template language and then allows you extend the the syntax to express application components. It is a framework used to build large scale and high performing applications that are easy to maintain. General features include that it is open source and licensed under Apache license version 2.0, it is an efficient framework able to create Rich Internet Applications (Web apps that are able to perform the normal features and functions of normal applications), provides an option to write client side applications using Javascript under an efficient Model View Controller method, and AngularJS is cross-browser compliant so that it automatically handles JavaScript for each browser. The advantages of AngularJS are that it has the ability to make single page applications in a clean way, provides data binding capabilities to HTML giving it a responsive experience, it is unit testable, uses dependency injection, gives the ability to provide more functionality with less code, and it can run on all major browsers and smartphones. The disadvantages are that it is not secure and not degradable. Since it is a framework that is JavaScript only, it is not safe so server side authentication is a must. Also since it is all JavaScript, if the user disables it, the webpage would show nothing but the basic page.

This relates to class because we were looking at the process and components that go into web applications. I selected TutorialsPoint because I have used it before for overviews, tutorials, and references. It has proven to be a reliable source to me so I do not have to worry about getting the wrong information. Their reviews online are typically very well rated with key words such as reliable, useful and helpful. I have found those three keywords to be true with this article. I had learned many things since I did not know much about AngularJS prior to reading the article. Some of these things include that it is very useful for single page applications and that it is not very secure. This is very useful for me to learn about because I am currently planning a single page web application project so it is an option for me to utilize.

Source: https://www.tutorialspoint.com/angularjs/angularjs_overview.htm

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

Maven Overview

Today I will be writing about Maven using information from the article Maven-Overview by TutorialsPoint. Maven is a project management tool giving a complete build process framework. Mavens objective is to provide a comprehensive, reusable and maintainable model for projects and to provide plugins and tools to interact with this model. Since Maven uses a standard directory layout and default build lifecycle, development teams can quickly set up their project builds. When you have multiple development teams Maven can create a standard build structure for all teams to use. This promotes consistency across the project while developers create reports, builds and testing automation setups. Maven gives a way for developers to manage builds, documentation, reporting, dependencies, SCMs, releases, distribution and mailing lists. Mavens project structure is declared in in the pom.xml file. POM stands for Project Object Model and contains the fundamentals of the entire Maven system. This pom.xml file is similar to the build.gradle file we have seen/used in class. Some features of Maven include its ability to generate a website or PDF including complete documentation, backwards compatibility, automatic parent versioning so that there is no need to specify in the sub module, parallel builds achieving performance improvements of up to 50%, and improved error reporting.

This topic relates to class because it is a software project management tool, which can be very useful to developers. We often used Gradle in class which is a similar concept. I selected this article from TutorialsPoint because it is a useful website for quick references, overviews and tutorials. It is similar to w3schools which is another website I use often for quick tutorials, references, etc.. I would say that the information is reliable, just more shallow as it does not dive deep into topics. I would not use it as the only source when trying to learn a certain subject in depth as you will not get a deep understanding of the material. As an overview though, I would say it is perfect. I personally had an okay understanding of Maven as I had used it a couple of times but never knew the finer details as to how it is different from other project management tools. Some things I had learned from this article are its many features including its use for reporting and documentation. I plan to use project management tools for future projects, so it is good to know the differences and know which one is the right one to use.

Source: https://www.tutorialspoint.com/maven/maven_overview.htm

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

Blog #6: Design Patterns

The class that I am taking right now goes over database design patterns, so it is only right that I research even more about them for this most recent blog post. I found an incredible website that discusses all sorts of designs, some which that I have never heard of before this. I will attach the link to the website but it was from sourcemaking.com. The examples that the website describes all fall under three different categories: creational, structural, and behavioral design patterns. The creational design patterns are defined as being all about instantiation. There are other subclasses of this design pattern group like class-creational and object-creational patterns. Some examples from the website of patterns in this larger group are builder, singleton, factory method, and more. In contrast, the structural group of patterns are all about class and object composition. Some examples of patterns from this group are adaptor, composite, bridge, decorator method, and more. The last group, behavioral, is defined as patterns for Class’s objects communication. These patterns are mostly concerned with communicating with objects. Some examples of this design pattern group are command, iterator, observer, visitor method, and more. I am very happy that I went back and revisited this topic from my class, especially since I am about to take the final in this class. I recommend taking a look at the same website that I used to research for this blog post, and I genuinely wish I found it earlier in this semester!

https://sourcemaking.com/design_patterns

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

Blog #5: Database Design

As I near graduation, many of my courses become more specialized towards my actual major and concentration. This semester, I have been enrolled in two computer science classes that, despite being very different, have help emphasize each other with their abstract similarities. Software Construction, Design, and Architecture repeatedly proved the value and worth of Database Design and Applications time and time again. The same could be easily claimed with the roles reversed. The reason I want to share this in my blog is not to say they are similar classes, but to express how important it is to me that my courses relate. If a class I take relates to something I do in real life or something I want to do later in life, it is easier for me to put effort into getting the most out of the class as I possibly can. Furthermore, I have already stated in previous posts that knowing that something I am learning is usable in real life is very motivating, while not being sure if I will ever use the information I study can be the opposite. So why does this all relate back to my two separate courses in this semester? It is because both classes are for different concentrations of my major but still share conceptual similarities. I chose to be a software development student which relates to Software Construction, Design, and Architecture directly, while Database Design and Applications is geared more toward Big Data Analytics. Seeing the similarities between these two classes helped show me that what I am studying is very worth it and can be used regularly in my life. I was able to use what I learned in one class directly on something I would practice in the other… at similar time periods in the semester no less. I definitely believe that this was somewhat intentional by my school to have classes like these be on similar timeframes, and I am glad to say that it does actually motivate me a bit and validates the concepts in each course. I do not have a source or link for this post, but I did feel like sharing this because of how adamant I am about this being a great and useful tactic of teaching/learning.

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