Constraint-Based Automatic Test Data Generation
IEEE Transactions on Software Engineering
Applying design of experiments to software testing: experience report
ICSE '97 Proceedings of the 19th international conference on Software engineering
The AETG System: An Approach to Testing Based on Combinatorial Design
IEEE Transactions on Software Engineering
QuickCheck: a lightweight tool for random testing of Haskell programs
ICFP '00 Proceedings of the fifth ACM SIGPLAN international conference on Functional programming
An Investigation of the Applicability of Design of Experiments to Software Testing
SEW '02 Proceedings of the 27th Annual NASA Goddard Software Engineering Workshop (SEW-27'02)
GAST: generic automated software testing
IFL'02 Proceedings of the 14th international conference on Implementation of functional languages
A logic-based approach to combinatorial testing with constraints
TAP'08 Proceedings of the 2nd international conference on Tests and proofs
Testing continuous double auctions with a constraint-based oracle
CP'10 Proceedings of the 16th international conference on Principles and practice of constraint programming
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We present an approach for modeling and testing transformational systems in an industrial context. The systems are modeled as a set of boolean formulas. Each formula is called a clause and is an expression for an expected output value. To manage complexities of the models, we employ a modeling trick for handling dependencies, by using some output values from the system under test to verify other output values. To avoid circular dependencies, the clauses are arranged in a hierarchy, where each clause depends on the outputs of its children. This modeling trick enables us to model and test complex systems, using relatively simple models. Pairwise testing is used for test case generation. This manages the number of test cases for complex systems. The approach is developed based on a case study for testing printer controllers in professional printers at Océ. The model-based testing approach results in increased maintainability and gives better understanding of test cases and their produced output. Using pairwise testing resulted in measurable coverage, with a test set smaller than the manually created test set. To illustrate the applicability of the approach, we show how the approach can be used to model and test parts of a controller for ventilation in livestock stables.