Parallel Algorithms for Generating Distinguishing Sequences for Observable Non-deterministic FSMs
- Submitting institution
-
The University of Leicester
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2173
- Type
- D - Journal article
- DOI
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10.1145/3051121
- Title of journal
- ACM Transactions on Software Engineering and Methodology
- Article number
- 5
- First page
- .
- Volume
- 26
- Issue
- 1
- ISSN
- 1049-331X
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
https://doi.org/10.1145/3051121
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
1
- Research group(s)
-
-
- Citation count
- 3
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper is the first paper to offer scalable methods for automating construction of functional tests from software with non-deterministic features (including e.g. safety-critical systems). A group at Edinburgh (Yaneva et al.) have considered the complementary problem of executing large tests generated e.g., by our algorithm. El-Fakih et al. (The Computer Journal 2019) have extended our method by introducing a sequential-heuristic step, and reported it in Salah’s PhD thesis (American U. Sharjah). The research was funded by The Scientific and Technological Research-Council of Turkey (grant-1059B191400424) and NVIDIA corporation (grant-T1754794). TOSEM is ACM’s flagship journal in software engineering.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -