2000
DOI: 10.1007/10722167_30
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Prioritized Traversal: Efficient Reachability Analysis for Verification and Falsification

Abstract: Our experience with semi-exhaustive verification shows a severe degradation in usability for the corner-case bugs, where the tuning effort becomes much higher and recovery from dead-ends is more and more difficult. Moreover, when there are no bugs at all, shifting semi-exhaustive traversal to exhaustive traversal is very expensive, if not impossible. This makes the output of semi-exhaustive verification on non-buggy designs very ambiguous. Furthermore, since after the design fixes each falsification task needs… Show more

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Cited by 27 publications
(17 citation statements)
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“…We used FORECAST [13] for this purpose. FORECAST is an industrial strength highperformance implementation of a BDD-based model checker developed at Intel, Haifa.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…We used FORECAST [13] for this purpose. FORECAST is an industrial strength highperformance implementation of a BDD-based model checker developed at Intel, Haifa.…”
Section: Resultsmentioning
confidence: 99%
“…Other papers suggest reducing the space requirements for sequential symbolic reachability analysis by partitioning the work into several tasks [25,7,13]. However, these schemes use a single machine to sequentially handle one task at a time, while the other tasks are kept in external memory.…”
Section: Introductionmentioning
confidence: 99%
“…The first step is to verify that the reference model satisfies a higher-level specification. This problem is addressed by mainstream FV and is documented in a rich collection of papers both from academia and industry [1,2,7,8,12,13,15,16]. The second step is to verify that the reference model, in the presence of environmental constraints, does imply the RTL design implementation.…”
Section: Figure 1 Reference Model For Rtl Verificationmentioning
confidence: 99%
“…If no adequate slicer is found, it gradually applies more precise computations. We compare our hybrid algorithm with the fast estimating algorithm Est [5]. We show that our algorithm produces far fewer duplications.…”
Section: Introductionmentioning
confidence: 99%
“…In the first phase the algorithm employs the method Est [5] to search for an effective slicer. This method initially computes an estimate of the size of f ∧v and f ∧v, for each variable v in the support of f .…”
Section: Introductionmentioning
confidence: 99%