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Increasing, not Diminishing: Investigating the Returns of Highly Maintainable Code

Markus Borg, Ilyana Pruvost, Enys Mones, Adam Tornhill

TL;DR

This study analyzes the business value of code maintainability by merging two public datasets to examine how Code Health (CH) relates to defect proneness and Time-in-Development (Time-in-Dev). It employs polynomial regression to capture non-linear CH effects and introduces a simple value-creation model, v = c × (1 − u), with capacity c ∝ 1/t and unplanned work u ∝ d, to discuss relative changes in organizational value. Results show strong non-linearities at CH extremes, including amplified returns when CH is high, and support a zero-tolerance stance toward code smells in high-churn files under a broken-windows lens. The work highlights the potential ROI of refactoring and provides a framework to engage leadership in debt trade-off discussions, while acknowledging limitations and calling for causal, project-level extensions and practical decision-support tools.

Abstract

Understanding and effectively managing Technical Debt (TD) remains a vital challenge in software engineering. While many studies on code-level TD have been published, few illustrate the business impact of low-quality source code. In this study, we combine two publicly available datasets to study the association between code quality on the one hand, and defect count and implementation time on the other hand. We introduce a value-creation model, derived from regression analyses, to explore relative changes from a baseline. Our results show that the associations vary across different intervals of code quality. Furthermore, the value model suggests strong non-linearities at the extremes of the code quality spectrum. Most importantly, the model suggests amplified returns on investment in the upper end. We discuss the findings within the context of the "broken windows" theory and recommend organizations to diligently prevent the introduction of code smells in files with high churn. Finally, we argue that the value-creation model can be used to initiate discussions regarding the return on investment in refactoring efforts.

Increasing, not Diminishing: Investigating the Returns of Highly Maintainable Code

TL;DR

This study analyzes the business value of code maintainability by merging two public datasets to examine how Code Health (CH) relates to defect proneness and Time-in-Development (Time-in-Dev). It employs polynomial regression to capture non-linear CH effects and introduces a simple value-creation model, v = c × (1 − u), with capacity c ∝ 1/t and unplanned work u ∝ d, to discuss relative changes in organizational value. Results show strong non-linearities at CH extremes, including amplified returns when CH is high, and support a zero-tolerance stance toward code smells in high-churn files under a broken-windows lens. The work highlights the potential ROI of refactoring and provides a framework to engage leadership in debt trade-off discussions, while acknowledging limitations and calling for causal, project-level extensions and practical decision-support tools.

Abstract

Understanding and effectively managing Technical Debt (TD) remains a vital challenge in software engineering. While many studies on code-level TD have been published, few illustrate the business impact of low-quality source code. In this study, we combine two publicly available datasets to study the association between code quality on the one hand, and defect count and implementation time on the other hand. We introduce a value-creation model, derived from regression analyses, to explore relative changes from a baseline. Our results show that the associations vary across different intervals of code quality. Furthermore, the value model suggests strong non-linearities at the extremes of the code quality spectrum. Most importantly, the model suggests amplified returns on investment in the upper end. We discuss the findings within the context of the "broken windows" theory and recommend organizations to diligently prevent the introduction of code smells in files with high churn. Finally, we argue that the value-creation model can be used to initiate discussions regarding the return on investment in refactoring efforts.
Paper Structure (18 sections, 3 equations, 4 figures, 2 tables)

This paper contains 18 sections, 3 equations, 4 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Background
  3. Code Health and Time-in-Development
  4. The Broken Windows Theory
  5. Related Work
  6. Code Smells and Defect Count
  7. Code Smells and Maintenance Effort
  8. Method
  9. Data Collection and Preprocessing
  10. Data Analysis
  11. Regression Models
  12. Value-creation Model
  13. Results and Discussion
  14. Regression models (RQ1)
  15. Value creation (RQ2)
  16. ...and 3 more sections

Figures (4)

  • Figure 1: Top-10 programming languages in the dataset.
  • Figure 2: Average defect count per file for different CH.
  • Figure 3: Average Time-in-Dev for resolving issues.
  • Figure 4: Relative changes of value creation for six different starting points.