Chronological fault-based mutation processes for WS-BPEL 2.0 programs
Bibliographic record
Abstract
Business Process Execution Language for Web Services (WS-BPEL) is a powerful language developed to capture the semantics of business processes and to describe the interactions between involved systems. Limited research has been undertaken in the area of identifying faults manifested in WS-BPEL-based systems. In this paper, we propose an approach to assist in testing WS-BPEL programs, specifically with regard to chronological-oriented faults. This approach employs mutation testing to identify and detect mutants introduced into WS-BPEL programs. We describe the steps to generate such mutants for WS-BPEL programs. To reduce the mutant specification into a minimal set of generic mutant specifications, we work directly with the workflow patterns that exist in this language. Further, we utilise an extended version of Backus-Naur Form (BNF) to represent a simple subset of communicating sequential processes (CSP) notations, adapted to fit the descriptive needs of WS-BPEL-based systems, to provide a complete and minimal set of mutants of chronological-oriented faults that can exist in WS-BPEL systems of the future.
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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 | 0.003 | 0.011 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".