Mutation Operators for Concurrent Java (J2SE 5.0)
Bibliographic record
Abstract
The current version of Java (J2SE 5.0) provides a high level of support for concurreny in comparison to previous versions. For example, programmers using J2SE 5.0 can now achieve synchronization between concurrent threads using explicit locks, semaphores, barriers, latches, or exchangers. Furthermore, built-in concurrent data structures such as hash maps and queues, built-in thread pools, and atomic variables are all at the programmer's disposal. We are interested in using mutation analysis to evaluate, compare and improve quality assurance techniques for concurrent Java programs. Furthermore, we believe that the current set of method mutation operators and class operators proposed in the literature are insufficient to evaluate concurrent Java source code because the majority of operators do not directly mutate the portions of code responsible for synchronization. In this paper we will provide an overview of concurrency constructs in J2SE 5.0 and a new set of concurrent mutation operators. We will justify the operators by categorizing them with an existing bug pattern taxonomy for concurrency. Most of the bug patterns in the taxonomy have been used to classify real bugs in a benchmark of concurrent Java applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".