Bibliographic record
Abstract
Distributed multithreaded software systems are becoming more and more important in modern networked environment. For these systems, concurrency control and thread synchronization make it much harder to do traditional extensive testing to guarantee the quality of the systems. In contrast to testing, software verification under certain formalisms and methodologies usually gives us higher confidence about the system. In this paper we consider translating some parts of program code that are sensitive to concurrency control into certain formal description so that we can reuse existing verification tools to enhance our confidence in the final code. Java language is gaining increasing popularity in distributed multithreaded system development, and CCS is one of the convenient tools for describing concurrent and multi-process systems. Under a set of reasonable restrictions, we present a general framework on how to translate the threaded control and synchronization portion of distributed multithreaded Java programs into formal specification in CCS. With the translated process terms, we are able to use some model checkers to verify properties expressed in modal /spl mu/-calculus, such as invariance eventualities, fairness etc., which are by nature hard to test.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".