IDEal: Efficient and precise alias-Aware dataflow analysis

Johannes Späth, Karim Ali, Eric Bodden

Research output: Contribution to journalArticlepeer-review


Program analyses frequently track objects throughout a program, which requires reasoning about aliases. Most dataflow analysis frameworks, however, delegate the task of handling aliases to the analysis clients, which causes a number of problems. For instance, custom-made extensions for alias analysis are complex and cannot easily be reused. On the other hand, due to the complex interfaces involved, off-the-shelf alias analyses are hard to integrate precisely into clients. Lastly, for precision many clients require strong updates, and alias abstractions supporting strong updates are often relatively inefficient. In this paper, we present IDEal , an alias-aware extension to the framework for Interprocedural Distributive Environment (IDE) problems. IDEal relieves static-analysis authors completely of the burden of handling aliases by automatically resolving alias queries on-demand, both efficiently and precisely. IDEal supports a highly precise analysis using strong updates by resorting to an on-demand, flow-sensitive, and context-sensitive all-alias analysis. Yet, it achieves previously unseen efficiency by propagating aliases individually, creating highly reusable per-pointer summaries. We empirically evaluate IDEal by comparing TSf , a state-of-the-art typestate analysis, to TSal , an IDEal - based typestate analysis. Our experiments show that the individual propagation of aliases within IDEal enables TSal to propagate 10.4× fewer dataflow facts and analyze 10.3× fewer methods when compared to TSf . On the DaCapo benchmark suite, TSal is able to efficiently compute precise results.

Original languageEnglish (US)
Article number99
JournalProceedings of the ACM on Programming Languages
Issue numberOOPSLA
StatePublished - Oct 2017


  • Aliasing
  • Dataflow
  • Static analysis

ASJC Scopus subject areas

  • Software
  • Safety, Risk, Reliability and Quality


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