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ASE2023顶会

Persisting and Reusing Results of Static Program Analyses on a Large Scale

Johannes Düsing, Ben Hermann

2023年份
1被引次数

摘要

Static Program Analysis (SPA) has long been established as an important technique for gaining insights into software systems. Over the last years, analysis designers increasingly produced analyses that are compositional, collaborative, or incremental in nature - thus relying on some form of existing results to increase performance or even precision. However, systematic result reuse is still rare in this field even though the analyzed software is mainly composed of reusable software components. For this work, we study 40 state-of-the-art SPA implementations and find that there is a tremendous potential for reusing analysis results. We attribute this to the fact that there is no systematic process in place for persisting and sharing analysis results and propose such a process here to fill this gap. In this paper, we present SPARRI, a prototype implementation providing an HTTP API to publish, search, and reuse SPA results. Our evaluation shows that reusing existing results with SPARRI can improve analysis performance by up to 92%. Furthermore, we see potential in applying it to other research areas like empirical software studies. benchmark creation. and artifact evaluation.

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