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IBM Research - Haifa

CDG – Coverage Directed Test Generation

Overview

One of the main bottlenecks of the verification process in general and coverage analysis in particular is closing the loop between the coverage results and directives to the stimuli generators. To address this bottleneck, we research and develop coverage-directed generation (CDG) methodology and technology, which are designed to automate the process of using feedback from coverage analysis for tuning generation stimuli towards areas not adequately verified. CDG casts the problem as a statistical inference problem, and uses Bayesian networks to encode the complex joint input-output distribution space for ultimately inferring generation directives to the stimuli generator.

For details, refer to: http://www.haifa.il.ibm.com/projects/verification/ml_cdg/index.html.