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Title: Assessing Test Adequacy for Black Box Systems without Specifications
Authors: Walkinshaw, Neil
First Published: Nov-2011
Presented at: The 23rd International Conference on Testing Software and Systems (ICTSS), Paris, 7-10 November 2011
Publisher: Springer Verlag
Citation: Proceedings of The 23rd IFIP WG 6.1 International Conference on Testing Software and Systems (ICTSS), Lecture Notes in Computer Science, 7019, pp. 209-224
Abstract: Testing a black-box system without recourse to a specification is difficult, because there is no basis for estimating how many tests will be required, or to assess how complete a given test set is. Several researchers have noted that there is a duality between these testing problems and the problem of inductive inference (learning a model of a hidden system from a given set of examples). It is impossible to tell how many examples will be required to infer an accurate model, and there is no basis for telling how complete a given set of examples is. These issues have been addressed in the domain of inductive inference by developing statistical techniques, where the accuracy of an inferred model is subject to a tolerable degree of error. This paper explores the application of these techniques to assess test sets of black-box systems. It shows how they can be used to reason in a statistically justified manner about the number of tests required to fully exercise a system without a specification, and how to provide a valid adequacy measure for black-box test sets in an applied context.
DOI Link: 10.1007/978-3-642-24580-0_15
ISSN: 0302-9743
ISBN: 978-3-642-24579-4
Version: Post-print
Status: Peer-reviewed
Type: Conference Paper
Rights: Copyright © IFIP International Federation for Information Processing 2011. Deposited with reference to the publisher's archiving policy available on the SHERPA/RoMEO website. The original publication is available at
Appears in Collections:Conference Papers & Presentations, Dept. of Computer Science

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