About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
DAC 2016
Conference paper
Probabilistic bug-masking analysis for post-silicon tests in microprocessor verification
Abstract
Post-silicon validation has become essential in catching hard-to-detect, rarely-occurring bugs that have slipped through pre-silicon verification. Post-silicon validation flows, however, are challenged by limited signal observability, which impacts their ability of diagnosing and detecting bugs. Indeed, bug manifestations during the execution of constrained-random tests may be masked and be unobservable from the test's outputs. The ability to evaluate the bug-masking rate of a test provides great value in generating and/or selecting effective tests for high coverage regressions. To this end, we propose an efficient, static bug-masking analysis solution, called BugMAPI. BugMAPI tracks the information flow in a test program, and it estimates the probability that bugs go undetected by the checking mechanisms in place in the post-silicon platform. To achieve this goal, we leverage static code analysis and a novel, lightweight, probability estimation algorithm. We evaluated BugMAPI on a range of industrial constrained-random tests and a range of bug injection models, and we found that it can estimate bug-masking rates with an accuracy of 77% in 3 orders-of-magnitude less time, compared to an ideal dynamic analysis solution.