Automatic Generation of Floating-Point Test Data 论文
1976IEEE Transactions on Software Engineering引用 253
Numerical Methods and AlgorithmsParallel Computing and Optimization TechniquesComputational Physics and Python Applications
摘要
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.