code friendly

Clean Code Principles

9 October 2017 @ 10:24pm by erik

In this blog post, Marcus Biel gives his thoughts on clean code, what that is, how to implement, estimate, and accurately design good software that does exactly what it should and nothing more. What is clean code? The author writes,

“It’s the idea that your code should be precise and as close to perfect as possible. If you have more code than you need, it shouldn’t be there.”

This concept relates to YAGNI (you ain’t gunna need it), and is an essential part of having clean and readable code. Adding features that might be needed later is a good way to bloat your code and run into bugs. Clean code requires time to fully understand the problem, this is sometimes tough when working in an environment where you are being pushed by those who don’t understand what goes into software design. Sometimes you will be asked to meet deadlines that will make you rush, in turn you can end up with poorly written code. The language and wording in code is also very important, using variables and names that are clear and make sense help others read and understand what is going on in your code. I selected this resource because having clean code is a huge part of being a good programmer, along with tips on clean code, the author has tips on designing code by running tests first, working with co-workers and clients to understand what features are most important, and what features are not beneficial.

“To me, being a software craftsman is about having a focused attitude and about taking responsibility for your code, your job, and your time. So, from beginning discussions to end results, your one focus should be on maintaining your own high standards and creating the best possible product for your client.” – Marcus Biel

This post had a good amount of information and insight on clean code, and being a good developer in general. Important aspects from the post I think are being clear when naming variables, methods, and classes, leaving out code that is not needed (YAGNI), and making accurate timelines for projects. Rushing to write code before you fully understand the problem can lead to more problems down the road. I expect to use concepts of clean code in my professional career, I believe it’s very important to make a good product that will benefit you, your company, or your client.


Singletons: Bill Pugh Solution or Enum

9 October 2017 @ 08:25pm by erik

In this blog post, Harinath Kuntamukkala discusses different approaches to the Singleton pattern. The first implementation he goes over is the Bill Pugh Solution, which is similar to the implementation we learned in class except it uses a static inner helper class as in the example below:

public class Logger {
    private Logger() {
        // private constructor
    // static inner class - inner classes are not loaded until they are
    // referenced.
    private static class LoggerHolder {
        private static Logger logger = new Logger();
    // global access point
    public static Logger getInstance() {
        return LoggerHolder.logger;
    //Other methods

This would be the best approach, but it’s possible for more than one instance to be created with the use of Java reflection. For example:

public class LoggerReflection {
    public static void main(String[] args) {
        Logger instance1 = Logger.getInstance();
        Logger instance2 = null;
        try {
            Constructor[] cstr = Logger.class.getDeclaredConstructors();
            for (Constructor constructor: cstr) {
                //Setting constructor accessible
                    = (Logger) constructor.newInstance();
        } catch (Exception e) {

The solution to the problem suggested by Joshua Bloch, is to use Enum. The reason we use Enum is because Java ensures that any Enum value is instantiated only once. Using Enum, this is what the Logger class would look like

public enum Logger {
    //other methods

It’s still possible for more than once instance to be created if a singleton object is serialized, then deserialized more than once. In order to avoid this you can implement a readResolve() method in the Logger Singleton class:

public class Logger implements Serializable {
    //other code related to Singleton
    //call this method immediately after De-serialization
    //it returns an instance of singleton
    protected Object readResolve() {
        return getInstance();

The reason I chose this resource is because we are currently learning about design patterns and just reviewed the singleton pattern. This post goes into the best implementations of the singleton pattern and why that is, I would like to stay up to date on the most effective, clean and efficient implementations of design patterns. I think this is a useful post, and learned about the Bill Pugh Solution and the Enum solution to ensure there’s only one instance of a singleton object. The author concluded that the Enum approach is the best solution as it is

“functionally equivalent to the public field approach, except that it is more concise, provides the serialization machinery for free, and provides an ironclad guarantee against multiple instantiations, even in the face of sophisticated serialization or reflection attacks.”

I expect to take what I learned in this article and use it whenever implementing the singleton design pattern, and I might rework the code I have now to make use of the Enum approach talked about in the article.