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Automatic Generation of Floating-Point Test Data

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2 Author(s)
Miller, W. ; Department of Computer Science, Pennsylvania State University ; Spooner, D.L.

For numerical programs, or more generally for programs with floating-point data, it may be that large savings of time and storage are made possible by using numerical maximization methods instead of symbolic execution to generate test data. Two examples, a matrix factorization subroutine and a sorting method, illustrate the types of data generation problems that can be successfully treated with such maximization techniques.

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Software Engineering, IEEE Transactions on  (Volume:SE-2 ,  Issue: 3 )