Mutation analysis involves mutations of software artefacts that are then used to evaluate the quality of software verification tools and techniques. It is considered the premier technique for evaluating the fault revealing effectiveness of test suites, test generation techniques, and other testing approaches.
Ideas derived from mutation analysis have also been used to test artefacts at different levels of abstraction, including requirements, formal specifications, models, architectural design notations and even informal descriptions. Recently, mutation has played an important role in software engineering for AI, such as in verifying trained models and behaviours. Furthermore, researchers and practitioners have investigated diverse forms of mutation, such as training or test data mutation, in combination with metamorphic testing to evaluate model performance in machine learning and detecting adversarial examples.
To be the premier forum for practitioners and researchers to discuss recent advances in the area of mutation analysis and propose new research directions, Mutation 2027 will feature keynote and invited talks followed by presentations given by the authors of accepted papers.
Important Dates
- Submission deadline: TBD
- Notification of acceptance: TBD
- Camera-ready: TBD
Call for Papers
Mutation analysis involves mutation of software artefacts that are then used to evaluate the quality of software verification tools and techniques. It is considered the premier technique for evaluating the fault revealing effectiveness of test suites, test generation techniques and other testing approaches. Ideas derived from mutation analysis have also been used to test artefacts at different levels of abstraction, including requirements, formal specifications, models, architectural design notations and even informal descriptions. Recently, mutation has played an important role in software engineering for AI, such as in verifying learned models and behaviours. Furthermore, researchers and practitioners have investigated diverse forms of mutation, such as training data or test data mutation, in combination with metamorphic testing to evaluate model performance in machine learning and detecting adversarial examples. Mutation 2027 aims to be the premier forum for practitioners and researchers to discuss recent advances in the area of mutation analysis and propose new research directions. We invite submissions of both full-length and short-length research papers and especially encourage the submission of industry practice papers.
Topics of Interest
Topics of interest include, but are not limited to, the following:
- Evaluation of mutation-based test adequacy criteria, and comparative studies with other test adequacy criteria.
- Formal theoretical analysis of mutation testing.
- Empirical studies on any aspects of mutation testing.
- Mutation based generation of program variants.
- Higher-order mutation testing.
- Mutation testing tools.
- Mutation for mobile, internet, and cloud based systems (e.g., addressing QoS, power consumption, stress testing, performance, etc.).
- Mutation for security and reliability.
- Novel mutation testing applications, and mutation testing in novel domains.
- Industrial experience with mutation testing.
- Mutation for Deep Learning (e.g., data mutation, model mutation, mutation-based test data generation, etc.).
- Use of Large Language Models (LLMs) for mutation analysis (e.g. generation of mutants).
- Mutation for LLMs.
Types of Submissions
Five types of papers can be submitted to the workshop:
- Full papers (10 pages): Research, case studies.
- Short papers (6 pages): Research in progress, tools.
- Full industrial papers (6 pages): Applications and lessons learned in industry.
- Short industrial papers (2 pages): Mutation testing in practice reports.
- Hot Off the Press (1 page abstract): presentation of work recently published in other venues
Each paper must conform to the two-column IEEE conference publication format (please use the letter format template and conference option). The text, figures, tables and appendices should not exceed 10 pages. Two additional pages containing only references are permitted.
Submissions will be evaluated according to the relevance and originality of the work and to their ability to generate discussions between the participants of the workshop. Each submission will be reviewed by three reviewers, and all accepted papers will be published as part of the ICST proceedings (except for Hot Off the Press submissions). Mutation 2027 will employ a double-anonymous review process (except for Hot Off the Press and industry submissions). Authors must make every effort to anonymise their papers to hide their identities throughout the review process.
Industry papers
Industry papers should be given the keyword “industry” and are not subject to the double anonymity policy.
Hot Off the Press
Hot Off the Press submissions should contain 1) a short summary of the paper’s contribution, 2) an explanation of why those results are particularly interesting for MUTATION attendees, 3) a link to the paper. Their title should start with “HOP:” The original paper should be published no earlier than May 1st 2026.
Important Dates
- Submission deadline: TBD
- Notification of acceptance: TBD
- Camera-ready: TBD
Organization
Zalán Lévai, University of Sheffield, United Kingdom
Laura Plein, CISPA Helmholtz Center for Information Security, Germany
Jeongju Sohn, Kyungpook National University, Republic of Korea