Combining Genetic Programming and Model Checking to Generate Environment Assumptions

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Gaaloul:TSE,

• author = "Khouloud Gaaloul and Claudio Menghi and Shiva Nejati and Lionel Briand and Yago {Isasi Parache}",
• title = "Combining Genetic Programming and Model Checking to Generate Environment Assumptions",
• journal = "IEEE Transactions on Software Engineering",
• year = "2022",
• volume = "48",
• number = "9",
• pages = "3664--3685",
• keywords = "genetic algorithms, genetic programming",
• URL = "http://hdl.handle.net/10993/47740",
• DOI = "doi:10.1109/TSE.2021.3101818",
• ISSN = "1939-3520",
• abstract = "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.",
• notes = "Also known as \cite{9507379}",

}

Genetic Programming entries for Khouloud Gaaloul Claudio Menghi Shiva Nejati Lionel C Briand Yago Isasi Parache

Citations