Abstract. Most points-to analysis research has been done on different systems by different groups, making it difficult to compare results, and to understand interactions between individual factors each group studied. Furthermore, points-to analysis for Java has been studied much less thoroughly than for C, and the tradeoffs appear very different. We introduce SPARK, a flexible framework for experimenting with points-to analyses for Java. SPARK supports equality-and subset-based analyses, variations in field sensitivity, respect for declared types, variations in call graph construction, off-line simplification, and several solving algorithms. SPARK is composed of building blocks on which new analyses can be based. We demonstrate SPARK in a substantial study of factors affecting precision and efficiency of subset-based points-to analyses, including interactions between these factors. Our results show that SPARK is not only flexible and modular, but also offers superior time/space performance when compared to other points-to analysis implementations.
Spark REF is a widely-used testbed for experimenting with points-to analysis for Java.
Scaling Java points-to analysis using Spark
Compiler Construction, 12th International Conference, volume 2622 of LNCS
Computer Science