Defining Code Complexity Beyond Big O Notation

Sofia Fischer examines different types of code complexity beyond traditional computational complexity. She compares insertion sort (O(n²)) with counting sort (O(n)), noting that while counting sort is computationally faster, it introduces readability challenges and constraints like inability to handle negative numbers. The article discusses cyclomatic complexity for measuring code paths, Halstead complexity metrics for program vocabulary and difficulty, and introduces linguistic complexity - applying natural language processing concepts to code. Fischer argues that choosing algorithms solely based on computational efficiency may introduce other forms of complexity, requiring more time for understanding, documentation, and debugging. The piece emphasizes that for business domain code, readability and maintainability often outweigh pure computational performance.