Research map / Learning theory and algorithms / Combinatorial and search optimization
SharpSSAT: A Witness-Generating Stochastic Boolean Satisfiability Solver
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add clause learning to SharpSSAT (ablation) | SharpSSAT · ClauSSat benchmark set | solved instances: 208 -> 218 | Helped |
| Add pure-literal detection to SharpSSAT (ablation) | SharpSSAT · ClauSSat benchmark set | solved instances: 218 -> 232 | Helped |
| Use VSIDS instead of random branching (ablation) | SharpSSAT · SharpSSAT benchmark set | solved instances: 215 -> 232 | Helped |
| Use VSADS instead of VSIDS branching (ablation) | SharpSSAT · SharpSSAT benchmark set | solved instances: 232 -> 232 | No clear effect |
| Use SharpSSAT instead of Prime | SSAT solving · ClauSSat benchmark set | solved instances: 177 -> 232 | Helped |
| Use SharpSSAT instead of ClauSSat | SSAT solving · ClauSSat benchmark set | solved instances: 196 -> 232 | Helped |
| Use SharpSSAT instead of DC-SSAT | SSAT solving · ClauSSat benchmark set | solved instances: 186 -> 232 | Helped |
| Use SharpSSAT instead of ElimSSAT | SSAT solving · ClauSSat benchmark set | solved instances: 226 -> 232 | Helped |
| Generate witnesses with SharpSSAT rather than ClauSSat | Witness generation · Solved benchmark instances | witness size | Helped |
| Generate witnesses with SharpSSAT rather than ClauSSat | Witness generation · Solved benchmark instances | memory usage | Hurt |
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