Fri 22 Jun 2018 14:00 - 14:25 at Grand Ballroom CD - Program Analysis Chair(s): Isil Dillig

When analyzing programs, large libraries pose significant challenges to static points-to analysis. A popular solution is to have a human analyst provide points-to specifications that summarize relevant behaviors of library code, which can substantially improve precision and handle missing code such as native code. We propose Atlas, a tool that automatically infers points-to specifications. Atlas synthesizes unit tests that exercise the library code, and then infers points-to specifications based on observations from these executions. Atlas automatically infers specifications for the Java standard library, and produces better results for a client static information flow analysis on a benchmark of 46 Android apps compared to using existing handwritten specifications.

Fri 22 Jun

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14:00 - 15:40
Program AnalysisPLDI Research Papers at Grand Ballroom CD
Chair(s): Isil Dillig UT Austin
14:00
25m
Talk
Active Learning of Points-To Specifications
PLDI Research Papers
Osbert Bastani Stanford University, Rahul Sharma Microsoft Research, Alex Aiken Stanford University, Percy Liang Stanford University
Media Attached
14:25
25m
Talk
Pinpoint: Fast and Precise Sparse Value Flow Analysis for Million Lines of Code
PLDI Research Papers
Qingkai Shi Hong Kong University of Science and Technology, China, Xiao Xiao SourceBrella Inc., Rongxin Wu Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Jinguo Zhou Sourcebrella Inc., Gang Fan , Charles Zhang
Media Attached
14:50
25m
Talk
A Data-Driven CHC Solver
PLDI Research Papers
He Zhu Rutgers University, USA, Stephen Magill , Suresh Jagannathan Purdue University
Media Attached
15:15
25m
Talk
User-Guided Program Reasoning using Bayesian Inference
PLDI Research Papers
Mukund Raghotaman University of Pennsylvania, Sulekha Kulkarni Georgia Tech, Kihong Heo University of Pennsylvania, USA, Mayur Naik University of Pennsylvania
Media Attached