Accurate QBF-based test pattern generation in presence of unknown values
Proceedings of the Conference on Design, Automation and Test in Europe
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All test generation algorithms make use of symbolic algebra. The symbolic value that most test generators use is 'X', to denote the unknown/do not care logic value. The other end of the spectrum is to shade each X differently to fully exploit the information contained in them. This is impractical due to combinatorial explosion that results from such coloring. In this paper, we explore use of limited symbolic evaluation in test generation. The symbolic evaluation greatly improves test generation compared with the usual 5-valued simulation. Also, and in contrast with other established techniques in test pattern generation such as static learning and dynamic learning, it requires no preprocessing and almost no additional memory.