Code Coverage Criteria for Asynchronous Programs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Asynchronous software often exhibits complex and error-prone behaviors that should be tested thoroughly. Code coverage has been the most popular metric to assess test suite quality. However, traditional code coverage criteria do not adequately reflect completion, interactions, and error handling of asynchronous operations. This paper proposes novel test adequacy criteria for measuring: (i) completion of asynchronous operations in terms of both successful and exceptional execution, (ii) registration of reactions for handling both possible outcomes, and (iii) execution of said reactions through tests. We implement JScope, a tool for automatically measuring coverage according to these criteria in JavaScript applications, as an interactive plug-in for Visual Studio Code. An evaluation of JScope on 20 JavaScript applications shows that the proposed criteria can help improve assessment of test adequacy, complementing traditional criteria. According to our investigation of 15 real GitHub issues concerned with asynchrony, the new criteria can help reveal faulty asynchronous behaviors that are untested yet are deemed covered by traditional coverage criteria. We also report on a controlled experiment with 12 participants to investigate the usefulness of JScope in realistic settings, demonstrating its effectiveness in improving programmers’ ability to assess test adequacy and detect untested behavior of asynchronous code.
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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 | 0.000 | 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 | 0.000 | 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