A verified and optimized Stream X‐Machine testing method, with application to cloud service certification
- Submitting institution
-
The University of Bradford
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 37
- Type
- D - Journal article
- DOI
-
10.1002/stvr.1729
- Title of journal
- Software Testing, Verification and Reliability
- Article number
- -
- First page
- 1
- Volume
- 30
- Issue
- 3
- ISSN
- 0960-0833
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2020
- URL
-
https://onlinelibrary.wiley.com/doi/full/10.1002/stvr.1729
- Supplementary information
-
-
- 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
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This article presents a novel Stream X-Machine (SXM) verification and testing method, with supporting tools. It proves that the optimisations proposed reduce the size of test suites considerably, without fault-detection loss. It is the first complete tool-suite for SXM-testing providing concrete grounding to executable tests (JUnit and 2 web-services formats) and the first SXM-tool to verify specifications before test generation. The research was funded by the EU project Broker@Cloud (https://cordis.europa.eu/project/id/318392), which was conducted with industrial partners SAP, CAS (Karlsruhe), SingularLogic (Athens) and academic collaborators SEERC (Thessaloniki), who provided the case studies and adopted the tool and testing methodology.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
