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Coverage Discounting: Improved Testbench Qualification by Combining Mutation Analysis with Functional Coverage
| Content Provider | CiteSeerX |
|---|---|
| Author | Lesperance, Nicole Lisherness, Peter Cheng, Kwang-Ting Tim |
| Abstract | Abstract—Testbench quality is commonly measured using cov-erage metrics. Code, toggle, and functional coverage all have a significant flaw: they reflect how well the design is activated by the test vectors, but insensitive to the error detection capabilities of the testbench. Mutation testing is an established technique for scrutinizing testbench checkers, but its adoption has been limited by the manual effort required to analyze the results. This paper describes the use of coverage discounting, where undetected mutants are explained in terms of functional coverpoints, thereby exposing testbench deficiencies in terms of design functionality rather than synthetic design errors. Two benchmarks are shown to compare this improved flow against regular mutation analysis. A confidence metric and simulation ordering algorithm optimized for coverage discounting are also outlined. I. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Coverage Discounting Functional Coverage Mutation Analysis Testbench Qualification Undetected Mutant Test Vector Manual Effort Synthetic Design Error Abstract Testbench Quality Cov-erage Metric Regular Mutation Analysis Significant Flaw Testbench Checker Functional Coverpoints Improved Flow Design Functionality Testbench Deficiency Error Detection Capability |
| Content Type | Text |
| Resource Type | Article |
