Static verification of concurrent system design
Bibliographic record
Abstract
Elaborating a correct design of a concurrent system is extremely difficult. In part this is due to the infinite number of possible system runtime behaviors that result from the concurrent (or pseudo-concurrent) execution of interacting processes or threads. Data consistency, deadlock, starvation and fairness issues are the most well-known problems encountered in concurrent systems. Accurate concurrent system design verification approaches require an expensive system runtime behavior analysis and consequently result in prohibitively high development costs (i.e. for testing). In this thesis we try to address this problem by presenting several static approaches that can help the developer of a concurrent system during the design phase. In the first part of the thesis we present an approach that can analyze an existing concurrent system design to detect potential deadlock situations. This is done by mapping object interaction diagrams such as sequence diagrams to System Synchronization Hasse diagrams, which are then analyzed to detect deadlock cycles. Since the approach is static, it is overly pessimistic, meaning that it is possible that the algorithm detects a deadlock that, in reality, cannot occur. On the other hand, if the algorithm cannot detect any deadlocks, the developer can be sure that the design is deadlock-free. In the second part of the thesis we show how a concurrency-enriched specification can be transformed into a system application-level consistent design. The approach starts with concurrency-aware OCL-based operation schemas that describe all system functionality using pre-, rely-, and post-conditions. These schemas are then mapped to Rely diagrams. Based on the rely diagrams, sequence diagrams describing the concurrent system design are elaborated. The approach uses locks to ensure consistency and deadlock freedom. We then further show how these locks can be used to enforce certain fairness policies. The usefulness of our approach is demonstrated
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".