Precise parameter synthesis for stochastic biochemical systems
- Submitting institution
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Royal Holloway and Bedford New College
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 31309201
- Type
- D - Journal article
- DOI
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10.1007/s00236-016-0265-2
- Title of journal
- Acta Informatica
- Article number
- -
- First page
- 589
- Volume
- 54
- Issue
- -
- ISSN
- 0001-5903
- Open access status
- Out of scope for open access requirements
- Month of publication
- March
- Year of publication
- 2016
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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4
- Research group(s)
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-
- Citation count
- 15
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- It presents an exact method for parameter synthesis of continuous-time Markov chains (CTMCs) from probabilistic temporal logic specifications. While the emphasis is on biological models, CTMCs are very popular in performance and reliability analysis. The method was later applied to computer systems, including a model of Google file system, and extended for GPU acceleration (TACAS 2016, 367-384). This work is one of the most influential in the synthesis of probabilistic models and has been applied in (ICSA 2017 131-140, QEST 2017 304-308, JSS 143 140-158) to multi-objective specifications and used as a benchmark in (TACAS 2018 396-413).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -