Explainability in Self-Adaptive Systems: A Systematic Literature Review
Paper i proceeding, 2026

Self-adaptive systems (SAS) dynamically adjust their configuration to changes in environment or internal state. These complex and possibly emergent adaptions require explanations. We conducted a systematic literature review to create an overview over existing research concerning explainability in SASs and identify further research directions. Specifically, we focus on approaches that have been empirically evaluated. We show that there is only a small amount of publications in this area, which, nonetheless, are very diverse concerning their approach and focus. We present our findings along the major parts of the explanation process. However, many of the approaches focus only on some specific aspects. A major finding is a disconnect between the stated explanation objectives and the conducted evaluations, especially, concerning user-centered goals like trust and understanding.

SLR

Explainability

Adaptive-System

Författare

Raphael Straub

Universität Ulm

Florian Sihler

Universität Ulm

Ali Torbati

Carl von Ossietzky Universität Oldenburg

Cong Wang

Technische Universität Dresden

Raffaela Groner

Göteborgs universitet

Chalmers, Data- och informationsteknik, Interaktionsdesign och Software Engineering

Verena Klos

Carl von Ossietzky Universität Oldenburg

Matthias Tichy

Universität Ulm

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 16082 LNCS 280-297
9783032041999 (ISBN)

51st Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2025
Salerno, Italy,

Ämneskategorier (SSIF 2025)

Datavetenskap (datalogi)

DOI

10.1007/978-3-032-04200-2_19

Mer information

Senast uppdaterat

2025-11-17