Article (Scientific journals)
Combining Genetic Programming and Model Checking to Generate Environment Assumptions
Gaaloul, Khouloud; Menghi, Claudio; Nejati, Shiva et al.
2022In IEEE Transactions on Software Engineering
Peer Reviewed verified by ORBi
 

Files


Full Text
TSEEpicurus.pdf
Author preprint (793.33 kB)
Download

All documents in ORBilu are protected by a user license.

Send to



Details



Keywords :
Environment assumptions; Model checking; Machine learning; Decision trees; Genetic programming; Search-based software testing
Abstract :
[en] Software verification may yield spurious failures when environment assumptions are not accounted for. Environment assumptions are the expectations that a system or a component makes about its operational environment and are often specified in terms of conditions over the inputs of that system or component. In this article, we propose an approach to automatically infer environment assumptions for Cyber-Physical Systems (CPS). Our approach improves the state-of-the-art in three different ways: First, we learn assumptions for complex CPS models involving signal and numeric variables; second, the learned assumptions include arithmetic expressions defined over multiple variables; third, we identify the trade-off between soundness and coverage of environment assumptions and demonstrate the flexibility of our approach in prioritizing either of these criteria. We evaluate our approach using a public domain benchmark of CPS models from Lockheed Martin and a component of a satellite control system from LuxSpace, a satellite system provider. The results show that our approach outperforms state-of-the-art techniques on learning assumptions for CPS models, and further, when applied to our industrial CPS model, our approach is able to learn assumptions that are sufficiently close to the assumptions manually developed by engineers to be of practical value.
Disciplines :
Computer science
Author, co-author :
Gaaloul, Khouloud ;  University of Luxembourg > Faculty of Science, Technology and Medecine (FSTM)
Menghi, Claudio ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV
Nejati, Shiva ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV
Briand, Lionel ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV
Isasi Parache, Yago;  LuxSpace
External co-authors :
no
Language :
English
Title :
Combining Genetic Programming and Model Checking to Generate Environment Assumptions
Publication date :
September 2022
Journal title :
IEEE Transactions on Software Engineering
ISSN :
1939-3520
Publisher :
Institute of Electrical and Electronics Engineers, New-York, United States - New York
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Security, Reliability and Trust
European Projects :
H2020 - 694277 - TUNE - Testing the Untestable: Model Testing of Complex Software-Intensive Systems
FnR Project :
FNR12632261 - Early Quality Assurance Of Critical Systems, 2018 (01/01/2019-31/12/2021) - Mehrdad Sabetzadeh
Funders :
NSERC of Canada under the Discovery and CRC programs
CE - Commission Européenne [BE]
Available on ORBilu :
since 27 July 2021

Statistics


Number of views
384 (100 by Unilu)
Number of downloads
212 (39 by Unilu)

Scopus citations®
 
2
Scopus citations®
without self-citations
1
WoS citations
 
1

Bibliography


Similar publications



Contact ORBilu