Following is a quick way to identify code with low testability and hence low maintainability:

  • Take any specific public method of the class
  • Count for number of decision points such as following:

– If
– For
– While
– Switch
– Inline ifs

  • If the number of decision points in a method is more than 15 or so, it could be taken as indication that it may get difficult to write unit tests covering all possible flows. Thus, the code will have lower testability.

The number of decision points in a method is also used to define/measure cyclomatic complexity of the method, or more specifically, McCabe Cyclomatic Complexity. Thus, mathematically speaking, testability can be represented as following:

Testability, T of a method is inversely proportional to No. of Decision Points, D, found in the method.

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. 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.

Recent Posts

Agentic Reasoning Design Patterns in AI: Examples

In recent years, artificial intelligence (AI) has evolved to include more sophisticated and capable agents,…

3 weeks ago

LLMs for Adaptive Learning & Personalized Education

Adaptive learning helps in tailoring learning experiences to fit the unique needs of each student.…

4 weeks ago

Sparse Mixture of Experts (MoE) Models: Examples

With the increasing demand for more powerful machine learning (ML) systems that can handle diverse…

1 month ago

Anxiety Disorder Detection & Machine Learning Techniques

Anxiety is a common mental health condition that affects millions of people around the world.…

1 month ago

Confounder Features & Machine Learning Models: Examples

In machine learning, confounder features or variables can significantly affect the accuracy and validity of…

1 month ago

Credit Card Fraud Detection & Machine Learning

Last updated: 26 Sept, 2024 Credit card fraud detection is a major concern for credit…

1 month ago