Theory of Relative Dependency:
 Higher Coupling Concentration in Smaller Modules and its Implications for Software Refactoring and Quality
Why this work is in the frame
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Bibliographic record
Abstract
Recent studies have repeatedly found that smaller modules are proportionally more defect-prone. In this article, the authors formulate and test a hypothesis stating that smaller modules are proportionally more coupled, given that dependencies caused by coupling have been consistently associated with defect-proneness. Strong evidence supports this hypothesis. Furthermore, refactoring exacerbates this effect. On the basis of this study's highly consistent results, the authors state the empirically based theory of relative dependency. That is, in large-scale software systems, smaller modules will be proportionally more dependent compared to larger ones. These findings have two implications for practice. First, we now have an empirically supported mechanism explaining the observations that defect concentration is higher in smaller modules. Practitioners can use this mechanism as evidence while seeking resources and support to revise or amend their organizations' quality assurance and quality control practices. Second, particularly for the projects that refactor extensively, such as those using agile methods, focusing defect detection activities on smaller modules will increase their efficiency and effectiveness even more. // NOTE // This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it