Entropyx: A Longitudinal Entropy-Based Framework for Measuring Code Drift and Technical Debt in Modern Software Systems

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Authors: Espen Sande-Larsen
Cited by: 0

Abstract

Entropyx computes per-file badness using weighted, min-max normalized metrics, including log-scaled source lines of code, complexity density, smells per KLOC, coupling proxies, and maintainability indices. Files with negligible badness (≤ 10⁻⁹) are excluded to reduce floating-point noise. Shannon entropy (base-2) is computed over the distribution of per-file badness values and normalized by log₂(N), where N is the number of non-negligible files. The final Entropyx Score is defined as normalized entropy multiplied by mean badness, capturing both diffusion and magnitude of structural degradation. The framework is language-agnostic and designed for cross-platform CLI implementation.

Fields of Study & Subjects

Software Engineering Research Software Engineering Techniques and Practices Software System Performance and Reliability

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
26 February 2026
Language
EN
Document type
Preprint