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SPLASH 2017
Sun 22 - Fri 27 October 2017 Vancouver, Canada
Fri 27 Oct 2017 11:15 - 11:37 at Regency C - Static Analysis Chair(s): Christian Hammer

We present a new data-driven approach to achieve highly cost-effective context-sensitive points-to analysis for Java. While context-sensitivity has greater impact on the analysis precision and performance than any other precision-improving techniques, it is difficult to accurately identify the methods that would benefit the most from context-sensitivity and decide how much context-sensitivity should be used for them. Manually designing such rules is a nontrivial and laborious task that often delivers suboptimal results in practice. To overcome these challenges, we propose an automated and data-driven approach that learns to effectively apply context-sensitivity from codebases. In our approach, points-to analysis is equipped with a parameterized and heuristic rules, in disjunctive form of properties on program elements, that decide when and how much to apply context-sensitivity. We present a greedy algorithm that efficiently learns the parameter of the heuristic rules. We implemented our approach in the Doop framework and evaluated using three types of context-sensitive analyses: conventional object-sensitivity, selective hybrid object-sensitivity, and type-sensitivity. In all cases, experimental results show that our approach significantly outperforms existing techniques.

Fri 27 Oct

Displayed time zone: Tijuana, Baja California change

10:30 - 12:00
Static AnalysisOOPSLA at Regency C
Chair(s): Christian Hammer University of Potsdam
10:30
22m
Talk
IDEal: Efficient and Precise Alias-Aware Dataflow Analysis
OOPSLA
Johannes Sp├Ąth Fraunhofer IEM, Karim Ali University of Alberta, Eric Bodden Heinz Nixdorf Institut, Paderborn University and Fraunhofer IEM
DOI
10:52
22m
Talk
P/Taint: Unified Points-to and Taint Analysis
OOPSLA
Neville Grech , Yannis Smaragdakis University of Athens
DOI
11:15
22m
Talk
Data-Driven Context-Sensitivity for Points-to Analysis
OOPSLA
Sehun Jeong Korea University, South Korea, Minseok Jeon Korea University, South Korea, Sungdeok (Steve) Cha Korea University, South Korea, Hakjoo Oh Korea University
DOI
11:37
22m
Talk
Automatically Generating Features for Learning Program Analysis Heuristics for C-Like Languages
OOPSLA
Kwonsoo Chae Korea University, Hakjoo Oh Korea University, Kihong Heo University of Pennsylvania, USA, Hongseok Yang University of Oxford
DOI