Testing concurrent programs using value schedules
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
Concurrent programs are difficult to debug and verify because of the nondeterministic nature of concurrent executions. A particular concurrency-related bug may only show up under certain rarely-executed thread interleavings. Therefore, commonly used debugging methodologies, such as inserting print statements, are no longer sufficient for uncovering concurrency-related bugs. However, many existing bug detection methods, such as dynamic analysis and model checking, have a very high computational cost. In this paper, we introduce a new technique for uncovering concurrency-related bugs from multithreaded Java programs. Our technique uncovers concurrency-related bugs by generating and testing read-write assignment sequences, referred to as value schedules, of a multithreaded Java program. Our value-schedule-based technique distinguishes itself in its ability to avoid exploring superfluous program state space caused by speculative permutation on transitions. Therefore, our technique can achieve a higher degree of POR (Partial Order Reduction) than existing methods. We demonstrate our technique using some programs, with an implementation built using an explicit state model checker called JPF
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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 | 0.000 |
| 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