In keeping with my recent learning about Java Design Patterns, as outlined by the Gang of Four, I have recently been doing research on the State Design Pattern. I came across an extremely useful article which details the Design Pattern logic, implementation, upsides and downsides, as well as giving an overall evaluation. The article is titled “State Design Pattern in Java,” by Denis Szczukocki, and starts by explaining that the main usage for the State pattern is “to allow the object for changing its behavior without changing its class.” It is also cleaner than a project cluttered with if/else statements for controlling object behavior. The basis is that an object who’s behavior is dependent on a specific state can easily change states and therefore change behaviors without the creation of a new object and the classes responsible for this behavior will be “tightly coupled.” Within the pattern, there will be 2 essential classes and a number of extra classes dependent on the number of states required. The first is the context class. The context class delegates object behavior to the other class, the state class, but the context class is the one used by the client. The state class is usually an interface, with the concrete state classes implementing this interface and dictating behavior. The article gives the example of a package with 3 states: ordered, delivered, and received. There is a package class, which is the context class, and contains methods to move to the next/previous states and print the status as well. When an instance of the package class is created, really what happens is that an instance of the first state (ordered is created). When ready, the package object can move to the delivered state, and then the received state, all of which have different behaviors. The three behaviors in the PackageState interface common to all concrete states are next, previous, and printStatus, each which has a different behavior depending on the concrete class of the package. The article then notes that a possible downside to the State design pattern is that, “the state becomes hardcoded, which is a bad practice in general.” This taught me how to use the State Design Pattern and why it is good practice. I plan to use this in future projects when I can in order to practice, as well as to implement good project design practice. It is understandable and not terribly difficult to implement, so I know this can help me in my future work.
As I progress more in my CS studies, I’m starting to move beyond learning how to write the code for a project to how the project should be designed overall. In fact, this is one of the main purposes of two of my current CS classes. This has lead me to learning about TDD, or Test Driven Development. I’ve come across a fantastic article by Andrea Koutifaris which outlines the concept well called Test Driven Development: what it is, and what it is not.
In this article, I’ve learned the purpose of writing test driven code and what the plan for doing it should be. In TDD, tests come first in the process while writing production code comes second. This is in order to almost put oneself in a user’s shoes. If I myself in the user, what do I want my code to do? This is where the tests come in. Once the goals are clear and defined, the production code can be written.
The rules for TDD can be broken down to two essential parts:
- “Write only enough of a unit test to fail”
- “Write only enough production code to make the failing unit test pass”
Tests must be written to be very specific and achieve the ultimate application goals. Analysis of your tests can help you determine a method to writing your production code. They often not only outline what need to be achieved, but how it needs to be achieved.
The next part of TDD would be writing production code. As outlined before, the second essential rule of TDD is to “Write only enough production code to make the failing test unit pass.” Had production code been written first, output may not match user goals and unnecessary code may be written, which comes with its own set of problems. The focus is on writing clean code and limiting the amount which you write.
The last part of TDD would be the “refractor phase.” This is where code can be changed to be better, but what is stressed here is removing all duplicate code and consolidating.
The result of TDD should be efficient, clean code which serves its purpose. Although it can seem long-winded and like extra work, it’s mostly just inverting the process which we usually work by, so once the process is learned and practiced, it can help with writing better code more coherently and more focused on user goals, which is the ultimate goal as a programmer.