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An analysis of test data selection criteria using the RELAY model of error detection

Abstract

RELAY, a model for error detection, defines revealing conditions that guarantee that a fault originates an error during execution and that the error transfers through computations and data flow until it is revealed. This model of error detection provides a framework within which the capabilities of other testing criteria can be evaluated. In this paper, we analyze three test data selection criteria that attempt to detect faults in six fault classes. This analysis shows that none of these criteria is capable of guaranteeing error detection for these fault classes and points out two major weaknesses of these criteria. The first weakness is that the criteria do not consider the potential unsatisfiability of their rules; each criterion includes rules that are sufficient to cause errors for some fault classes, yet when such rules are unsatisfiable, many errors may remain undetected. Their second weakness is failure to integrate their proposed rules; although a criterion may cause a subexpression to take on an erroneous value, there is no effort made to guarantee that the enclosing expression evaluates incorrectly. This paper shows how the test data selection criterion defined by RELAY overcomes these weaknesses.

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