The category-partition method for specifying and generating fuctional tests
Communications of the ACM
A plan-based intelligent assistant that supports the software development
SDE 3 Proceedings of the third ACM SIGSOFT/SIGPLAN software engineering symposium on Practical software development environments
Approaches to specification-based testing
TAV3 Proceedings of the ACM SIGSOFT '89 third symposium on Software testing, analysis, and verification
Test Selection Based on Finite State Models
IEEE Transactions on Software Engineering
Knowledge Representation and Reasoning in the Design of Composite Systems
IEEE Transactions on Software Engineering - Special issue on knowledge representation and reasoning in software development
Automating requirements engineering using artificial intelligence planning techniques
Automating requirements engineering using artificial intelligence planning techniques
An experimental determination of sufficient mutant operators
ACM Transactions on Software Engineering and Methodology (TOSEM)
Toward automatic generation of novice user test scripts
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A Framework for Specification-Based Testing
IEEE Transactions on Software Engineering
Using a goal-driven approach to generate test cases for GUIs
Proceedings of the 21st international conference on Software engineering
Test Case Generation as an AI Planning Problem
Automated Software Engineering
Generating Test Data with Enhanced Context-Free Grammars
IEEE Software
Using Model Checking to Generate Tests from Specifications
ICFEM '98 Proceedings of the Second IEEE International Conference on Formal Engineering Methods
An Automatic Generator for Compiler Testing
IEEE Transactions on Software Engineering
AI Planner Assisted Test Generation
Software Quality Control
Rapid goal-oriented automated software testing using MEA-graph planning
Software Quality Control
AIana: an AI planning system for test data generation
Proceedings of the 1st Workshop on Testing Object-Oriented Systems
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Error recovery testing is an important part of software testing, especially for safety-critical systems. We show how an AI planning system and concepts of mutation testing can be combined to generate error recovery tests for software. We identify a set of mutation operations on the representation that the planner uses when generating test cases. These mutations cause error recovery test cases to be generated. The paper applies these concepts to the testing of a large tape storage system.