Wed 11 May 2022 11:25 - 11:30 at ICSE room 2-odd hours - Performance and Reliability Chair(s): Andrea Zisman
The static detection of divide-by-zero, a common programming error, is particularly prone to false positives because conventional static analysis reports a divide-by-zero bug whenever it cannot prove the safety property — the divisor variable is not zero in all executions. When reasoning the program semantics over a large number of under-constrained variables, conventional static analyses significantly loose the bounds of divisor variables, which easily fails the safety proof and leads to a massive number of false positives. We propose a static analysis to detect divide-by-zero bugs taking additional evidence for under-constrained variables into consideration. Based on an extensive empirical study of known divide-by-zero bugs, we no longer arbitrarily report a bug once the safety verification fails. Instead, we actively look for affirmative evidences, namely source evidence and bound evidence, that imply a high possibility of the bug to be triggerable at runtime. When applying our tool Wit to the real-world software such as the Linux kernel, we have found 72 new divide-by-zero bugs with a low false positive rate of 22%.
Tue 10 MayDisplayed time zone: Eastern Time (US & Canada) change
04:00 - 05:00 | Reliability and Safety 1Technical Track / SEIP - Software Engineering in Practice at ICSE room 1-even hours Chair(s): Cristian Cadar Imperial College London, UK | ||
04:00 5mTalk | Automatically Identifying Shared Root Causes of Test Breakages in SAP HANA SEIP - Software Engineering in Practice Gabin An KAIST, Juyeon Yoon Korea Advanced Institute of Science and Technology, Jeongju Sohn University of Luxembourg, Jingun Hong SAP Labs, Dongwon Hwang SAP Labs, Shin Yoo KAIST Pre-print Media Attached | ||
04:05 5mTalk | Record and Replay of Online Traffic for Microservices with Automatic Mocking Point Identification SEIP - Software Engineering in Practice Jiangchao Liu Ant Group, Jierui Liu Ant Group, Peng Di Ant Group, Alex X. Liu Ant Group, Zexin Zhong Ant Group; University of Technology Sydney Pre-print Media Attached | ||
04:10 5mTalk | DeepTraLog: Trace-Log Combined Microservice Anomaly Detection through Graph-based Deep Learning Technical Track Chenxi Zhang Fudan University, Xin Peng Fudan University, Chaofeng Sha Fudan University, Ke Zhang Fudan University, Zhenqing Fu Fudan University, Xiya Wu Fudan University, Qingwei Lin Microsoft Research, Dongmei Zhang Microsoft Research Pre-print Media Attached | ||
04:15 5mTalk | Decomposing Software Verification into Off-the-Shelf Components: An Application to CEGAR Technical Track Dirk Beyer LMU Munich, Germany, Jan Haltermann University of Oldenburg, Thomas Lemberger LMU Munich, Heike Wehrheim Carl von Ossietzky Universität Oldenburg / University of Oldenburg Pre-print Media Attached | ||
04:20 5mTalk | Precise Divide-By-Zero Detection with Affirmative Evidence Technical Track Yiyuan Guo The Hong Kong University of Science and Technology, Ant Group, Jinguo Zhou Ant Group, Peisen Yao The Hong Kong University of Science and Technology, Qingkai Shi Ant Group, Charles Zhang Hong Kong University of Science and Technology DOI Pre-print Media Attached | ||
04:25 5mTalk | Repairing Brain-Computer Interfaces with Fault-based Data Acquisition Technical Track Cailin Winston University of Washington, Caleb Winston University of Washington, Chloe N Winston University of Washington, Claris Winston University of Washington, Cleah Winston , Rajesh PN Rao University of Washington, René Just University of Washington Pre-print Media Attached |
Wed 11 MayDisplayed time zone: Eastern Time (US & Canada) change
11:00 - 12:00 | Performance and ReliabilityTechnical Track / Journal-First Papers at ICSE room 2-odd hours Chair(s): Andrea Zisman The Open University | ||
11:00 5mTalk | Predicting unstable software benchmarks using static source code features Journal-First Papers Christoph Laaber Simula Research Laboratory, Mikael Basmaci University of Zurich, Pasquale Salza University of Zurich Link to publication DOI Media Attached | ||
11:05 5mTalk | Evaluating the impact of falsely detected performance bug-inducing changes in JIT models Journal-First Papers Sophia Quach Concordia University, Maxime Lamothe Polytechnique Montréal, Bram Adams Queens University, Yasutaka Kamei Kyushu University, Weiyi Shang Concordia University Link to publication DOI Pre-print Media Attached | ||
11:10 5mTalk | Using Reinforcement Learning for Load Testing of Video Games Technical Track Rosalia Tufano Università della Svizzera Italiana, Simone Scalabrino University of Molise, Luca Pascarella Università della Svizzera italiana (USI), Emad Aghajani Software Institute, USI Università della Svizzera italiana, Rocco Oliveto University of Molise, Gabriele Bavota Software Institute, USI Università della Svizzera italiana Pre-print Media Attached | ||
11:15 5mTalk | EAGLE: Creating Equivalent Graphs to Test Deep Learning Libraries Technical Track Jiannan Wang Purdue University, Thibaud Lutellier University of Waterloo, Shangshu Qian Purdue University, Hung Viet Pham University of Waterloo, Lin Tan Purdue University Pre-print Media Attached | ||
11:20 5mTalk | Decomposing Software Verification into Off-the-Shelf Components: An Application to CEGAR Technical Track Dirk Beyer LMU Munich, Germany, Jan Haltermann University of Oldenburg, Thomas Lemberger LMU Munich, Heike Wehrheim Carl von Ossietzky Universität Oldenburg / University of Oldenburg Pre-print Media Attached | ||
11:25 5mTalk | Precise Divide-By-Zero Detection with Affirmative Evidence Technical Track Yiyuan Guo The Hong Kong University of Science and Technology, Ant Group, Jinguo Zhou Ant Group, Peisen Yao The Hong Kong University of Science and Technology, Qingkai Shi Ant Group, Charles Zhang Hong Kong University of Science and Technology DOI Pre-print Media Attached |