Automatic Generation of Floating-Point Test Data
Abstract
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.
- Publication:
-
IEEE Transactions on Software Engineering
- Pub Date:
- September 1976
- DOI:
- Bibcode:
- 1976ITSEn...2..223M
- Keywords:
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- Automatic testing;
- Computer science;
- Algorithms;
- Software testing;
- System testing;
- Software systems;
- Roundoff errors;
- Sorting;
- Arithmetic;
- Iterative methods;
- Automatic test data generation;
- branching;
- data constraints;
- execution path;
- software evaluation systems