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The University of Texas at Austin

MuAlloy : an automated mutation system for alloy

Abstract

dc:description.abstract

Mutation is a powerful technique that researchers have studied for several decades in the context of imperative code. For example, mutation testing is commonly considered a '"gold standard"' for test suite quality. Mutation in the context of declarative languages is a less studied problem. This thesis introduces a foundation for mutation-driven analyses for Alloy, a first-order, declarative language based on relations. Specifically, we introduce a family of mutation operators for Alloy models and define algorithms for applying the operators on different parts of the models. We embody these operators and algorithms in our prototype tool MuAlloy that provides a GUI-based front-end for customizing the application of mutation operators. To demonstrate the potential of our approach, we illustrate the use of MuAlloy in two application scenarios: (1) mutation testing for Alloy (in the spirit of traditional mutation testing for imperative languages); and (2) program repair for Alloy using mutation.

Degree

thesis:*
Name thesis:degree_name
Master of Science in Engineering
Level thesis:degree_level
Masters
Discipline thesis:degree_discipline
Electrical and Computer Engineering
Grantor
The University of Texas at Austin
Year dc:date.issued
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Wang, Kaiyuan
Advisor dc:contributor.advisor
  • Khurshid, Sarfraz
Committee member dc:contributor.committeemember
  • Perry, Dewayne E.

Subjects

dc:subject × 5

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
Identifier
doi:10.15781/T2S31M
OAI identifier oai:identifier
oai:repositories.lib.utexas.edu:2152/31865

Chain of custody

source
Harvested from
University of Texas
Base URL
repositories.lib.utexas.edu/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Wang, Kaiyuan. MuAlloy : an automated mutation system for alloy. Masters thesis, The University of Texas at Austin, 2015. http://hdl.handle.net/2152/31865