Semantic Mutation Testing for Multi-Agent Systems

Zhan Huang*, Rob Alexander

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper introduces semantic mutation testing (SMT) into multiagent
systems. SMT is a test assessment technique that makes changes to the interpretation of a program and then examines whether a given test set has the ability to detect each change to the original interpretation. These changes represent possible misunderstandings of how the program is interpreted. SMT is also a technique for assessing the robustness of a program to semantic changes. This paper applies SMT to three rule-based agent programming languages, namely Jason, GOAL and 2APL, provides several contexts in which SMT for these languages is useful, and proposes three sets of semantic mutation operators (i.e.,
rules to make semantic changes) for these languages respectively, and a set of semantic mutation operator classes for rule-based agent languages. This paper then shows, through preliminary evaluation of our semantic mutation operators for Jason, that SMT has some potential to assess tests and program robustness.
Original languageEnglish
Title of host publicationEngineering Multi-Agent Systems
Subtitle of host publicationThird International Workshop, EMAS 2015
EditorsMatteo Baldoni, Luciano Baresi, Mehdi Dastani
Place of PublicationSwitzerland
Pages131 to 152
ISBN (Electronic)978-3-319-26184-3
ISBN (Print)978-3-319-26183-6
Publication statusPublished - 20 May 2015

Publication series

NameLecture Notes in Computer Science (LNCS)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameLecture Notes in Artificial Intelligence

Bibliographical note

© 2015, The Author(s).

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