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| ASCII Text | x | ||
| W. Miller, D.L. Spooner, "Automatic Generation of Floating-Point Test Data," IEEE Transactions on Software Engineering, vol. 2, no. 3, pp. 223-226, September, 1976. | |||
| BibTex | x | ||
| @article{ 10.1109/TSE.1976.233818, author = {W. Miller and D.L. Spooner}, title = {Automatic Generation of Floating-Point Test Data}, journal ={IEEE Transactions on Software Engineering}, volume = {2}, number = {3}, issn = {0098-5589}, year = {1976}, pages = {223-226}, doi = {http://doi.ieeecomputersociety.org/10.1109/TSE.1976.233818}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Software Engineering TI - Automatic Generation of Floating-Point Test Data IS - 3 SN - 0098-5589 SP223 EP226 EPD - 223-226 A1 - W. Miller, A1 - D.L. Spooner, PY - 1976 KW - software evaluation systems KW - Automatic test data generation KW - branching KW - data constraints KW - execution path VL - 2 JA - IEEE Transactions on Software Engineering ER - | |||
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.
Index Terms:
software evaluation systems, Automatic test data generation, branching, data constraints, execution path
Citation:
W. Miller, D.L. Spooner, "Automatic Generation of Floating-Point Test Data," IEEE Transactions on Software Engineering, vol. 2, no. 3, pp. 223-226, Sept. 1976, doi:10.1109/TSE.1976.233818
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