How to Predict Reusability Index of a Standalone Code

Is it possible to predict the reusability index of a block of code in a standalone mode? Meaning, given no information about the code, and just the piece of code, would you be able to predict or tell if the code is highly reusable or not reusable at all?

Before going into this, lets understand the basic fundamentals in relation with code reusability.

One myth I have come across while discussing the code reusability is that code should be made reusable when demanded by requirements. For example, one says that for reusable services, one should write reusable components and thus, reusable piece of code. When asked to many people, I got the answer such as one may need to know more information to tell whether a block of code is reusable or not.

Reusability is very much related with cohesiveness of the code in a way that a block of code, high in cohesion, can be found to be highly reusable and likely to have less coupling or coupling which is based on well defined requirements. And, what can be termed as highly cohesive code? The block of code which adheres to the SOLID principle of Single Responsibility can be termed as code having high cohesion.

Thus, when you are given a standalone block of code, try to read the cohesiveness of the code. Meaning, try to find out if the block of code is serving just one functionality or serving multiple functionality. If you are able to find this, you may be able to determine the cohesiveness of the code. And code reusability is directly proportional to code cohesiveness.

 

Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. For latest updates and blogs, follow us on Twitter. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking. Check out my other blog, Revive-n-Thrive.com

Recent Posts

Linear Regression T-test: Formula, Example

Last updated: 7th May, 2024 Linear regression is a popular statistical method used to model…

13 hours ago

Feature Engineering in Machine Learning: Python Examples

Last updated: 3rd May, 2024 Have you ever wondered why some machine learning models perform…

5 days ago

Feature Selection vs Feature Extraction: Machine Learning

Last updated: 2nd May, 2024 The success of machine learning models often depends on the…

5 days ago

Model Selection by Evaluating Bias & Variance: Example

When working on a machine learning project, one of the key challenges faced by data…

6 days ago

Bias-Variance Trade-off in Machine Learning: Examples

Last updated: 1st May, 2024 The bias-variance trade-off is a fundamental concept in machine learning…

6 days ago

Mean Squared Error vs Cross Entropy Loss Function

Last updated: 1st May, 2024 As a data scientist, understanding the nuances of various cost…

6 days ago