Title
Synthesis of probabilistic models for quality-of-service software engineering.
Abstract
An increasingly used method for the engineering of software systems with strict quality-of-service (QoS) requirements involves the synthesis and verification of probabilistic models for many alternative architectures and instantiations of system parameters. Using manual trial-and-error or simple heuristics for this task often produces suboptimal models, while the exhaustive synthesis of all possible models is typically intractable. The EvoChecker search-based software engineering approach presented in our paper addresses these limitations by employing evolutionary algorithms to automate the model synthesis process and to significantly improve its outcome. EvoChecker can be used to synthesise the Pareto-optimal set of probabilistic models associated with the QoS requirements of a system under design, and to support the selection of a suitable system architecture and configuration. EvoChecker can also be used at runtime, to drive the efficient reconfiguration of a self-adaptive software system. We evaluate EvoChecker on several variants of three systems from different application domains, and show its effectiveness and applicability.
Year
DOI
Venue
2018
10.1007/s10515-018-0235-8
Autom. Softw. Eng.
Keywords
Field
DocType
Search-based software engineering, Probabilistic model checking, Evolutionary algorithms, QoS requirements
Software engineering,Evolutionary algorithm,Computer science,Quality of service,Software system,Heuristics,Systems architecture,Probabilistic logic,Control reconfiguration,Search-based software engineering
Journal
Volume
Issue
ISSN
25
4
0928-8910
Citations 
PageRank 
References 
9
0.45
73
Authors
3
Name
Order
Citations
PageRank
Simos Gerasimou111014.31
Radu Calinescu290563.01
Giordano Tamburrelli396536.04