Fri 22 Jun 2018 15:15 - 15:40 at Grand Ballroom CD - Program Analysis Chair(s): Isil Dillig

Program analyses necessarily make approximations that often lead them to report true alarms interspersed with many false alarms. We propose a new approach to leverage user feedback to guide program analyses towards true alarms and away from false alarms. Our approach associates each alarm with a confidence value by performing Bayesian inference on a probabilistic model derived from the analysis rules. In each iteration, the user inspects the alarm with the highest confidence and labels its ground truth, and the approach recomputes the confidences of the remaining alarms given this feedback. It thereby maximizes the return on the effort by the user in inspecting each alarm. We have implemented our approach in a tool named Bingo for program analyses expressed in Datalog. Experiments with real users and two sophisticated analyses—a static datarace analysis for Java programs and a static taint analysis for Android apps—show significant improvements on a range of metrics, including false alarm rates and number of bugs found.

Conference Day
Fri 22 Jun

Displayed time zone: Eastern Time (US & Canada) change

14:00 - 15:40
Program AnalysisPLDI Research Papers at Grand Ballroom CD
Chair(s): Isil DilligUT Austin
14:00
25m
Talk
Active Learning of Points-To Specifications
PLDI Research Papers
Osbert BastaniStanford University, Rahul SharmaMicrosoft Research, Alex AikenStanford University, Percy LiangStanford University
Media Attached
14:25
25m
Talk
Pinpoint: Fast and Precise Sparse Value Flow Analysis for Million Lines of Code
PLDI Research Papers
Qingkai ShiHong Kong University of Science and Technology, China, Xiao XiaoSourceBrella Inc., Rongxin WuDepartment of Computer Science and Engineering, The Hong Kong University of Science and Technology, Jinguo ZhouSourcebrella Inc., Gang Fan, Charles Zhang
Media Attached
14:50
25m
Talk
A Data-Driven CHC Solver
PLDI Research Papers
He ZhuRutgers University, USA, Stephen Magill, Suresh JagannathanPurdue University
Media Attached
15:15
25m
Talk
User-Guided Program Reasoning using Bayesian Inference
PLDI Research Papers
Mukund RaghotamanUniversity of Pennsylvania, Sulekha KulkarniGeorgia Tech, Kihong HeoUniversity of Pennsylvania, USA, Mayur NaikUniversity of Pennsylvania
Media Attached