Explainability in Self-Adaptive Systems: A Systematic Literature Review
Paper in 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

Author

Raphael Straub

University of Ulm

Florian Sihler

University of Ulm

Ali Torbati

The Carl von Ossietzky University of Oldenburg

Cong Wang

Technische Universität Dresden

Raffaela Groner

University of Gothenburg

Chalmers, Computer Science and Engineering (Chalmers), Interaction Design and Software Engineering

Verena Klos

The Carl von Ossietzky University of Oldenburg

Matthias Tichy

University of 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,

Subject Categories (SSIF 2025)

Computer Sciences

DOI

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

More information

Latest update

11/17/2025