Documents

  • paper

    Accepted author manuscript, 1.53 MB, PDF document

DOI

In the past years, several automated repair strategies have been proposed to fix bugs in individual software programs without any human intervention. There has been, however, little work on how automated repair techniques can resolve failures that arise at the system-level and are caused by undesired interactions among different system components or functions. Feature interaction failures are common in complex systems such as autonomous cars that are typically built as a composition of independent features (i.e., units of functionality). In this paper, we propose a repair technique to automatically resolve undesired feature interaction failures in automated driving systems (ADS) that lead to the violation of system safety requirements. Our repair strategy achieves its goal by (1) localizing faults spanning several lines of code, (2) simultaneously resolving multiple interaction failures caused by independent faults, (3) scaling repair strategies from the unit-level to the system-level, and (4) resolving failures based on their order of severity. We have evaluated our approach using two industrial ADS containing four features. Our results show that our repair strategy resolves the undesired interaction failures in these two systems in less than 16h and outperforms existing automated repair techniques.

Original languageEnglish
Title of host publicationThe ACM SIGSOFT International Symposium on Software Testing and Analysis
PublisherAssociation for Computing Machinery (ACM)
Pages88-100
Number of pages13
ISBN (Electronic)978-1-4503-8008-9
DOIs
Publication statusPublished - 2020
EventISSTA 2020 - Los Angeles, United States
Duration: 18 Jul 202022 Jul 2020

Conference

ConferenceISSTA 2020
Abbreviated titleISSTA 2020
CountryUnited States
CityLos Angeles
Period18/07/2022/07/20

    Research areas

  • Automated Driving Systems, Automated Software Repair, Feature Interaction Problem, Search-based Software Testing

ID: 73375947