The category-partition method for specifying and generating fuctional tests
Communications of the ACM
Automatic generation of test scripts from formal test specifications
TAV3 Proceedings of the ACM SIGSOFT '89 third symposium on Software testing, analysis, and verification
Object-oriented software engineering
Object-oriented software engineering
Efficient computation of unique input/output sequences in finite-state machines
IEEE/ACM Transactions on Networking (TON)
The AETG System: An Approach to Testing Based on Combinatorial Design
IEEE Transactions on Software Engineering
A visual test development environment for GUI systems
Proceedings of the 1998 ACM SIGSOFT international symposium on Software testing and analysis
Operational Profiles in Software-Reliability Engineering
IEEE Software
Using a model-based test generator to test for standard conformance
IBM Systems Journal
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Multi-panel systems are systems that interact with a user via multiple input panels. The flow through the panels is influenced by the interaction. Multi-panel systems are ubiquitous, and include panel-based legacy applications, automated teller machines, and web-based systems. Finding regression test suites which efficiently cover the functionality of these systems is difficult, because it requires covering interactions between input fields within a panel as well as flows between panels. Previous approaches to covering input field interactions include partitioning methods and combinatorial design methods. State machines and decision tables have been used to cover flow between panels. None of these techniques produce a conceptually simple, unified model that supports both intra- and inter-panel coverage. Our new method for capturing and representing test specifications provides such a model. This model is then used to generate a locally minimal set of test cases which completely covers the model. We applied this technique in a pilot study for regression testing, and this pilot had promising results which we discuss. We conclude by presenting our plans for generalizing the technique beyond multi-panel systems and regression testing.