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2025 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW), March 31 – April 4, 2025,
Naples, Italy
Frontmatter
Title Page
Article: icstcomp25foreword-fm000-p doi:
5th International Workshop on Artificial Intelligence in Software Testing (AIST 2025)
Session 1: AI/ML for Software Testing Applications
Session 2: LLMs for Test Case Generation
21th International Workshop on Advances in Model Based Testing (A-MOST 2025)
Coverage and Path-Based Testing
Model and Machine Learning
Mutating Skeletons: Learning Timed Automata via Domain Knowledge
Felix Wallner,
Bernhard K. Aichernig,
Florian Lorber, and
Martin Tappler
(Graz University of Technology and Silicon Austria Labs, TU Graz - SAL DES Lab, Austria; Graz University of Technology, Austria; Silicon Austria Labs, Austria; TU Wien, Austria)
Article: icstcomp25amost-id204-p doi:
AI and Testing
16th International Workshop on Automated Testing (A-TEST)
AI-Driven Testing Automation
Automated Testing in Critical Systems
A Workflow for Automated Testing of a Safety-Critical Embedded Subsystem
Michele Ignarra,
Maria Guarino,
Andrea Aiello,
Vincenzo Tonziello,
Giovanni De Donato,
Emanuele Pascale,
Renato De Guglielmo,
Antonio Costa, and
Cosimo Affuso
(Hitachi Rail, Italy; Alten, Italy)
Article: icstcomp25atest-id147-p doi:
5th International CI/CD Industry Workshop (CCIW 2025)
The Purpose of CI
CI at Scale
Multi-architecture Testing at Google
Tim A. D. Henderson,
Sushmita Azad,
Avi Kondareddy, and
Abhay Singh
(Google, USA; Google LLC, USA; Google LLC, UK)
Article: icstcomp25cciw-id6-p doi:
Centralized, ML-Based, CI Optimizations
12th International Workshop on Software Test Architecture (InSTA 2025)
Research Papers
Industry Reports and Emgerging Ideas
9th International Workshop on Testing Extra-Functional Properties and Quality Characteristics of Software Systems (ITEQS 2025)
AI and Testing
Cyber-Physical Systems
14th International Workshop on Combinatorial Testing (IWCT 2025)
Theoretical Aspects of CT
Combinatorial Testing and ML/AI
A Combinatorial Approach to Reduce Machine Learning Dataset Size
Megan Olsen,
M S Raunak,
Rick Kuhn,
Fenrir Badorf,
Hans van Lierop, and
Francis Durso
(Loyola University Maryland, USA; National Institute of Standards and Technology, USA; Natl Institute of Standards & Technology, USA; Johns Hopkins University, USA)
Article: icstcomp25iwct-id157-p doi:
Data Frequency Coverage Impact on AI Performance
Erin Lanus,
Brian Lee,
Jaganmohan Chandrasekaran,
Laura Freeman,
M S Raunak,
Raghu Kacker, and
Rick Kuhn
(Virginia Tech, USA; Virginia Polytechnic Institute and State University (Virginia Tech), USA; National Institute of Standards and Technology, USA; Natl Institute of Standards & Technology, USA)
Article: icstcomp25iwct-id210-p doi:
Combinatorial Testing Tools
Applications of CT
International Workshop on Mutation Testing (Mutation 2025)
Session 1
Session 2
8th International IEEE Workshop on Next Level of Test Automation (NextA 2025)
Testing and LLMs
Fault Localization
1st International Workshop on Secure, Accountable, and Verifiable Machine Learning (SAFE-ML 2025)
Robustness, Verification, and Security in AI Systems
Security and Privacy in Fedetated Learning Systems
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