Measuring the progress of projects using the time dependence of code changes
Bibliographic record
Abstract
Tracking the progress of a project is often done through imprecise manually gathered information, like progress reports, or through automatic metrics such as Lines Of Code (LOC). Such metrics are too coarse-grained and too imprecise to capture all facets of a project. In this paper, we mine the code changes in the source code repository and study the concept of time dependence of code changes. Using this concept, we can track the progress of a software project as the progress of a building. We can examine how changes build on each other over time and determine the impact of these changes on the quality of a project. In particular, we study whether new changes are built just-in-time or if they build on older, stable code. Through a case study on two large open source projects (PostgreSQL and FreeBSD), we show that time dependence varies across projects and throughout the lifetime of each project. We also show that there is a high linear correlation between building on new code and the occurrence of bugs.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".