On the Caching Schemes to Speed Up Program Reduction

Program reduction is a highly practical, widely demanded technique to help debug language tools, such as compilers, interpreters and debuggers. Given a program P that exhibits a property ψ, conceptually, program reduction iteratively applies various program transformations to generate a vast number of variants from P by deleting certain tokens and returns the minimal variant preserving ψ as the result.

A program reduction process inevitably generates duplicate variants, and the number of them can be significant. Our study reveals that on average 61.8% and 24.3% of the generated variants in two representative program reducers HDD and Perses, respectively, are duplicates. Checking them against ψ is thus redundant and unnecessary, which wastes time and computation resources. Although it seems that simply caching the generated variants can avoid redundant property tests, such a trivial method is impractical in the real world due to the significant memory footprint. Therefore, a memory-efficient caching scheme for program reduction is in great demand.

This study is the first effort to conduct a systematic, extensive analysis of memory-efficient caching schemes for program reduction. We first propose to use two well-known compression methods, ZIP and SHA, to compress the generated variants before they are stored in the cache. Furthermore, our keen understanding on the program reduction process motivates us to propose a novel, domain-specific, both memory and computation-efficient caching scheme, Refreshable Compact Caching (RCC). Our key insight is two-fold: ① by leveraging the correlation between variants and the original program P, we losslessly encode each variant into an equivalent, compact, canonical representation; ② periodically, stale cache entries, which will never be accessed, are timely removed to minimize the memory footprint over time.

Our extensive evaluation on 31 real-world C compiler bugs demonstrates that caching schemes help avoid issuing redundant queries by 61.8% and 24.3% in HDD and Perses, respectively; correspondingly, the runtime performance is notably boosted by 22.8% and 18.2%. With regard to the memory efficiency, all three methods use less memory than the state-of-the-art string-based scheme STR. Specifically, ZIP and SHA cut down the memory footprint by more than 80% and 90% in both Perses and HDD compared to STR; moreover, the highly-scalable, domain-specific RCC dominates peer schemes, and outperforms the SHA by 96.4% and 91.74% in HDD and Perses, respectively.