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29th ISSTA 2020: Virtual Event, USA
- Sarfraz Khurshid, Corina S. Pasareanu:
ISSTA '20: 29th ACM SIGSOFT International Symposium on Software Testing and Analysis, Virtual Event, USA, July 18-22, 2020. ACM 2020, ISBN 978-1-4503-8008-9
Fuzzing
- Andrea Fioraldi
, Daniele Cono D'Elia
WEIZZ: automatic grey-box fuzzing for structured binary formats. 1-13 - Yuqi Chen, Bohan Xuan, Christopher M. Poskitt
Active fuzzing for testing and securing cyber-physical systems. 14-26 - Björn Mathis, Rahul Gopinath, Andreas Zeller
Learning input tokens for effective fuzzing. 27-37
Symbolic Execution and Constraint Solving
- Peisen Yao, Qingkai Shi
Fast bit-vector satisfiability. 38-50 - David Trabish, Noam Rinetzky:
Relocatable addressing model for symbolic execution. 51-62 - Frank Busse
Running symbolic execution forever. 63-74
Repair and Debug
- Yiling Lou, Ali Ghanbari
Can automated program repair refine fault localization? a unified debugging approach. 75-87 - Raja Ben Abdessalem, Annibale Panichella, Shiva Nejati, Lionel C. Briand, Thomas Stifter:
Automated repair of feature interaction failures in automated driving systems. 88-100 - Thibaud Lutellier
CoCoNuT: combining context-aware neural translation models using ensemble for program repair. 101-114
Mobile Apps
- Xueliang Li, Yuming Yang, Yepang Liu, John P. Gallagher
Detecting and diagnosing energy issues for mobile applications. 115-127 - Hui Liu, Mingzhu Shen, Jiahao Jin, Yanjie Jiang:
Automated classification of actions in bug reports of mobile apps. 128-140 - Oliviero Riganelli, Simone Paolo Mottadelli, Claudio Rota
Data loss detector: automatically revealing data loss bugs in Android apps. 141-152
Machine Learning I
- Minxue Pan, An Huang, Guoxin Wang, Tian Zhang, Xuandong Li:
Reinforcement learning based curiosity-driven testing of Android applications. 153-164 - Seokhyun Lee, Sooyoung Cha, Dain Lee, Hakjoo Oh:
Effective white-box testing of deep neural networks with adaptive neuron-selection strategy. 165-176 - Yang Feng, Qingkai Shi
DeepGini: prioritizing massive tests to enhance the robustness of deep neural networks. 177-188
Machine Learning II
- Saeid Tizpaz-Niari, Pavol Cerný, Ashutosh Trivedi:
Detecting and understanding real-world differential performance bugs in machine learning libraries. 189-199 - Arnab Sharma, Heike Wehrheim:
Higher income, larger loan? monotonicity testing of machine learning models. 200-210 - Saikat Dutta, August Shi, Rutvik Choudhary, Zhekun Zhang, Aryaman Jain, Sasa Misailovic:
Detecting flaky tests in probabilistic and machine learning applications. 211-224
Bug Localization and Test Isolation
- Michael Pradel, Vijayaraghavan Murali, Rebecca Qian, Mateusz Machalica, Erik Meijer, Satish Chandra:
Scaffle: bug localization on millions of files. 225-236 - Rahul Gopinath, Alexander Kampmann, Nikolas Havrikov
Abstracting failure-inducing inputs. 237-248 - Pengyu Nie, Ahmet Çelik, Matthew Coley, Aleksandar Milicevic, Jonathan Bell
Debugging the performance of Maven's test isolation: experience report. 249-259
Security
- Ismet Burak Kadron, Nicolás Rosner, Tevfik Bultan:
Feedback-driven side-channel analysis for networked applications. 260-271 - Mohannad Alhanahnah, Clay Stevens
Scalable analysis of interaction threats in IoT systems. 272-285 - Muyang Liu, Ke Li, Tao Chen:
DeepSQLi: deep semantic learning for testing SQL injection. 286-297
Regression Testing
- Wing Lam, August Shi, Reed Oei, Sai Zhang, Michael D. Ernst, Tao Xie:
Dependent-test-aware regression testing techniques. 298-311 - Patrice Godefroid, Daniel Lehmann
Differential regression testing for REST APIs. 312-323 - Qianyang Peng, August Shi, Lingming Zhang:
Empirically revisiting and enhancing IR-based test-case prioritization. 324-336
Challenging Domains
- Per Erik Strandberg, Thomas J. Ostrand, Elaine J. Weyuker, Wasif Afzal, Daniel Sundmark:
Intermittently failing tests in the embedded systems domain. 337-348 - Carl Hildebrandt
Feasible and stressful trajectory generation for mobile robots. 349-362 - Hui Li, Dong Wang
Detecting cache-related bugs in Spark applications. 363-375
Binary Analysis
- Yifei Xu, Zhengzi Xu, Bihuan Chen, Fu Song, Yang Liu
Patch based vulnerability matching for binary programs. 376-387 - George Fourtounis, Leonidas Triantafyllou, Yannis Smaragdakis:
Identifying Java calls in native code via binary scanning. 388-400 - Muhui Jiang, Yajin Zhou, Xiapu Luo, Ruoyu Wang, Yang Liu
An empirical study on ARM disassembly tools. 401-414
Static Analysis and Search-Based Testing
- Asem Ghaleb
How effective are smart contract analysis tools? evaluating smart contract static analysis tools using bug injection. 415-427 - Dominik Helm
A programming model for semi-implicit parallelization of static analyses. 428-439 - Yun Lin, Jun Sun, Gordon Fraser, Ziheng Xiu, Ting Liu, Jin Song Dong:
Recovering fitness gradients for interprocedural Boolean flags in search-based testing. 440-451
Build Testing
- Kaiyuan Wang, Greg Tener, Vijay Gullapalli, Xin Huang, Ahmed Gad, Daniel Rall:
Scalable build service system with smart scheduling service. 452-462 - Gang Fan, Chengpeng Wang, Rongxin Wu
Escaping dependency hell: finding build dependency errors with the unified dependency graph. 463-474 - Zhibo Liu
How far we have come: testing decompilation correctness of C decompilers. 475-487
Numerical Software Analysis and Clone Detection
- Jackson Vanover
Discovering discrepancies in numerical libraries. 488-501 - Xiao He, Xingwei Wang, Jia Shi, Yi Liu:
Testing high performance numerical simulation programs: experience, lessons learned, and open issues. 502-515 - Chunrong Fang
Functional code clone detection with syntax and semantics fusion learning. 516-527 - Yakun Zhang, Wensheng Dou, Jiaxin Zhu, Liang Xu, Zhiyong Zhou, Jun Wei, Dan Ye, Bo Yang:
Learning to detect table clones in spreadsheets. 528-540
Tool Demonstrations
- Ali Ghanbari
ObjSim: lightweight automatic patch prioritization via object similarity. 541-544 - Chao Guo, Tieke He, Wei Yuan, Yue Guo, Rui Hao:
Crowdsourced requirements generation for automatic testing via knowledge graph. 545-548 - Zichen Guo, Jiawei Liu, Tieke He, Zhuoyang Li, Peitian Zhangzhu:
TauJud: test augmentation of machine learning in judicial documents. 549-552 - Wentian Yan, Jianbo Gao, Zhenhao Wu, Yue Li, Zhi Guan, Qingshan Li, Zhong Chen:
EShield: protect smart contracts against reverse engineering. 553-556 - Gustavo Grieco, Will Song, Artur Cygan, Josselin Feist, Alex Groce:
Echidna: effective, usable, and fast fuzzing for smart contracts. 557-560 - George Thompson, Allison K. Sullivan
ProFL: a fault localization framework for Prolog. 561-564 - Yang Zhang, Shuai Shao
FineLock: automatically refactoring coarse-grained locks into fine-grained locks. 565-568 - Ezio Bartocci
CPSDebug: a tool for explanation of failures in cyber-physical systems. 569-572 - Ruixiang Qian, Yuan Zhao, Duo Men, Yang Feng, Qingkai Shi, Yong Huang, Zhenyu Chen:
Test recommendation system based on slicing coverage filtering. 573-576
Doctoral Symposium
- Feng Xue:
Automated mobile apps testing from visual perspective. 577-581 - Luis Gustavo Araujo Rodriguez
Program-aware fuzzing for MQTT applications. 582-586 - João Choma Neto:
Automatic support for the identification of infeasible testing requirements. 587-591
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