Abstract Programming faults are defined in the framework of a program proof outline. A component C in program P is faulty if P cannot be proved correct with the current implementation of C but it can be proved using the design specification for C, which defines the role of C in the overall design of P. A programming error is a state that violates the implementation specification of C. The error is masked if the design specification is satisfied by the incorrect state. Given a passing test t, the probability of error masking is 1–s(t), where s(t) is the sensitivity of t. Dynamic mutation testing (DMT), a Monte Carlo method, is used to estimate s(t). DMT is extended to estimate the probability of the existence of a hidden fault in C for a passing test suite. That probabillity can be viewed as a metric that measures the quality of the passing test suite.

It is pointed out that a major problem in software maintenance is the revalidation of a modified code. It is economically desirable to restrict that process only to those parts of the program that are affected by the modifications. Towards that goal, a formal method is needed to identify the modifications in an automatic way. Such a method is proposed in the present work. The modifications are localized within clusters in the flow graphs of the original and modified programs. Both flow graphs are transformed into reduced flow graphs, between which an isomorphic correspondence is established. Cluster-nodes in the reduced graphs encapsulate modifications to the original program. An algorithm to derive the reduced flow graphs has been implemented as an extension to the recently developed system for testing and debugging (STAD 1.0) and early experiments with the algorithm are reported. Potential applications in regression testing and reasoning about the program are discussed.>

The language of regular expressions is used for the identification of constructors of definition-use chains. Activation of the chains is essential for all data flow testing strategies. The algorithm is based on the node-elimination method of J.A. Brzozowski and E.J. McCluskey (1963). It generates a regular expression that represents the (possibly infinite) set of all constructors of the chain involved. A particular path can then be derived from that expression. The algorithm has been implemented as an extension to STAD, a recently implemented system for testing and debugging.>

Some properties of a program data flow can be used to guide program testing. The presented approach aims to exercise use-definition chains that appear in the program. Two such data oriented testing strategies are proposed; the first involves checking liveness of every definition of a variable at the point(s) of its possible use; the second deals with liveness of vectors of variables treated as arguments to an instruction or program block. Reliability of these strategies is discussed with respect to a program containing an error.