Causality in configurable software systems

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

Abstract

Detecting and understanding reasons for defects and inadvertent behavior in software is challenging due to their increasing complexity. In configurable software systems, the combinatorics that arises from the multitude of features a user might select from adds a further layer of complexity. We introduce the notion of feature causality, which is based on counterfactual reasoning and inspired by the seminal definition of actual causality by Halpern and Pearl. Feature causality operates at the level of system configurations and is capable of identifying features and their interactions that are the reason for emerging functional and non-functional properties. We present various methods to explicate these reasons, in particular well-established notions of responsibility and blame that we extend to the feature-oriented setting. Establishing a close connection of feature causality to prime implicants, we provide algorithms to effectively compute feature causes and causal explications. By means of an evaluation on a wide range of configurable software systems, including community benchmarks and real-world systems, we demonstrate the feasibility of our approach: We illustrate how our notion of causality facilitates to identify root causes, estimate the effects of features, and detect feature interactions.

Details

OriginalspracheEnglisch
TitelProceedings - 2022 ACM/IEEE 44th International Conference on Software Engineering, ICSE 2022
Herausgeber (Verlag)Association for Computing Machinery (ACM), New York
Seiten325-337
Seitenumfang13
ISBN (elektronisch)9781450392211
ISBN (Print)978-1-4503-9221-1
PublikationsstatusVeröffentlicht - 5 Juli 2022
Peer-Review-StatusJa

Konferenz

TitelInternational Conference on Software Engineering
KurztitelICSE'2022
Veranstaltungsnummer
Dauer8 - 27 Mai 2022
Webseite
BekanntheitsgradInternationale Veranstaltung
Ort
StadtPittsburgh
LandUSA/Vereinigte Staaten

Externe IDs

Scopus 85133510076
Mendeley 53ca13c6-4b19-360f-b399-839effcb1272

Schlagworte

Forschungsprofillinien der TU Dresden

DFG-Fachsystematik nach Fachkollegium

Fächergruppen, Lehr- und Forschungsbereiche, Fachgebiete nach Destatis

Schlagwörter

  • causality, configurable systems, software analysis, software product lines