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Decision Ordering Based Learning Techniques

  • Mingsong Chen
  • Xiaoke Qin
  • Heon-Mo Koo
  • Prabhat Mishra
Chapter

Abstract

The test generation performance using SAT-based BMC mainly depends on the efficiency of SAT search heuristics which can find satisfying assignments quickly. Since similar properties and SAT instances describe correlated functional scenarios, their significant overlap on the counterexample assignments can be used as learnings for the SAT search. This chapter explores such learnings within a SAT stance and among similar SAT instances. The proposed intra- and inter-property learnings based on decision ordering heuristics and conflict clause forwarding techniques can be used to improve the overall test generation time for a single property as well as a cluster of similar properties.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Mingsong Chen
    • 1
  • Xiaoke Qin
    • 2
  • Heon-Mo Koo
    • 3
  • Prabhat Mishra
    • 2
  1. 1.Software Engineering InstituteEast China Normal UniversityShanghaiPeople’s Republic of China
  2. 2.Department of Computer and Information Science and EngineeringUniversity of FloridaGainsvilleUSA
  3. 3.Intel corporationSantaUSA

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