Environmental bugs are bugs caused by limitations of precision or capacity in the environment of a piece of software. These bugs may be difficult to activate and even more difficult to find. This paper reports on an extension to traditional mutation testing that enables testing specifically for environmental bugs involving integer arithmetic. This method is both simple and effective, and provides some insight into other possible extensions of the mutation-testing methodology that can be used to expose environmental bugs.

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Mutation Analysis is an established technique for test data generation and source code testing. Developed systems have concentrated on applying some or all of the possible mutant operators (perturbations) to the submitted code. Recent work tackled the scheduling of mutant program execution on vector processors or a Hypercube as a cost reduction scheme. This paper discusses a logical mechanism of impact driven testing in order to acheive full mutation testing with reduced overheads regardless of implementation. Guiding the mutant generation by block impact together with mutant operator heirarchies and a test data coverage scheme enable an efficient tool to be constructed.

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Mutation analysis is a method for reliable testing of large software systems. It provides a method for assessing the adequacy of test data. Mothra [DeMi87] is a mutation analysis based software testing environment that currently supports the testing of Fortran 77 programs. Work is underway to enhance thsi tool along several dimension. One of these is the addition of multilingual capability. C is one of the languages that we plan to support. This report describes the mutant operators designed for the proposed ANSI C programming language. Mutant operators are categorized using syntactic criteria. Such a classification is expected to be useful for an implementor of mutation based testing system. Another classification, useful for the tester, is based on the nature of tests that can be conducted using mutation analysis. This classification exposes the gen erality and completeness of mutation based testing. Each mutant operator s introduced with illustrative examples. The rationale supporting each operator is also provided. An appendix provides a cross-reference of all mutant operators for ease of referencing. The design described here is a result of long deliberations amongst authors of this report in, which several aspects of the C language and program development in C were examined. We intend this report to srve as a manual for thew C mutant operators fir researchers in software testing.

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Perturbation testing is an approach to software testing which focuses on faults withinarithmetic expressions appearing throughout a program. This approach is expanded to permit analysis of individual test points rather than entire paths, and to concentrate on domain errors. Faults are modeled as perturbing functions drawn from a vector space of potential faults and added to the correct form of an arithmetic expression. Sensitivity measures are derived which limit the possible size of those faults that would go undetected after the execution of a given test set. These measures open up an interesting view of testing, in which attempts are made to reduce the volume of possible faults which, were they present in the program being tested, would have escaped detection on all tests performed so far. The combination of these measures with standard optimization techniques yields a novel test-data-generation method called arithmetic fault detection.