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ICSE 2021
Mon 17 May - Sat 5 June 2021

Web testing has long been recognized as a notoriously difficult task.Even nowadays, web testing still mainly relies on manual efforts in many cases while automated web testing is still far from achieving human-level performance. Key challenges include dynamic content update and deep bugs hiding under complicated user interactions and specific input values, which can only be triggered by certain action sequences in the huge space of all possible sequences. In this paper, we propose WebExplor, an automatic end-to-end web testing framework, to achieve an adaptive exploration of web applications. WebExplor adopts a curiosity-driven reinforcement learning to generate high-quality action sequences (test cases) with temporal logical relations. Besides, WebExplor incrementally builds an automaton during the online testing process, which acts as the high-level guidance to further improve the testing efficiency. We have conducted comprehensive evaluations on six real-world projects, a commercial SaaS web application, and performed an in-the-wild study of the top 50 web applications in the world. The results demonstrate that in most cases WebExplor can achieve significantly higher failure detection rate, code coverage and efficiency than existing state-of-the-art web testing techniques. WebExplor also detected 12 previously unknown failures in the commercial web application, which have been confirmed and fixed by the developers. Furthermore, our in-the-wild study further uncovered 3,466 exceptions and errors.

Wed 26 May

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

14:30 - 15:30
2.3.1. Defect Prediction: Automation #1Technical Track / SEIP - Software Engineering in Practice at Blended Sessions Room 1 +12h
Chair(s): Carolyn Seaman University of Maryland Baltimore County
14:30
20m
Paper
Automatic Web Testing using Curiosity-Driven Reinforcement LearningTechnical Track
Technical Track
YAN ZHENG Nanyang Technological University, Yi Liu Southern University of Science and Technology, Xiaofei Xie Nanyang Technological University, Yepang Liu Southern University of Science and Technology, China, Lei Ma University of Alberta, Jianye Hao Tianjin University, Yang Liu Nanyang Technological University
Pre-print Media Attached
14:50
20m
Paper
Evaluating SZZ Implementations Through a Developer-informed OracleTechnical Track
Technical Track
Giovanni Rosa University of Molise, Luca Pascarella Università della Svizzera italiana (USI), Simone Scalabrino University of Molise, Rosalia Tufano Università della Svizzera Italiana, Gabriele Bavota Software Institute, USI Università della Svizzera italiana, Michele Lanza Software Institute, USI Università della Svizzera italiana, Rocco Oliveto University of Molise
Pre-print Media Attached
15:10
20m
Paper
D2A: A Dataset Built for AI-Based Vulnerability Detection Methods Using Differential AnalysisSEIP
SEIP - Software Engineering in Practice
Yunhui Zheng IBM Research, Saurabh Pujar IBM Research, Burn Lewis IBM Research, Luca Buratti IBM Research, Edward Epstein IBM Research, Bo Yang IBM Research, Jim A. Laredo IBM Research, USA, Alessandro Morari IBM Research, Zhong Su IBM Research
Pre-print Media Attached

Thu 27 May

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

02:30 - 03:30
02:30
20m
Paper
Automatic Web Testing using Curiosity-Driven Reinforcement LearningTechnical Track
Technical Track
YAN ZHENG Nanyang Technological University, Yi Liu Southern University of Science and Technology, Xiaofei Xie Nanyang Technological University, Yepang Liu Southern University of Science and Technology, China, Lei Ma University of Alberta, Jianye Hao Tianjin University, Yang Liu Nanyang Technological University
Pre-print Media Attached
02:50
20m
Paper
Evaluating SZZ Implementations Through a Developer-informed OracleTechnical Track
Technical Track
Giovanni Rosa University of Molise, Luca Pascarella Università della Svizzera italiana (USI), Simone Scalabrino University of Molise, Rosalia Tufano Università della Svizzera Italiana, Gabriele Bavota Software Institute, USI Università della Svizzera italiana, Michele Lanza Software Institute, USI Università della Svizzera italiana, Rocco Oliveto University of Molise
Pre-print Media Attached
03:10
20m
Paper
D2A: A Dataset Built for AI-Based Vulnerability Detection Methods Using Differential AnalysisSEIP
SEIP - Software Engineering in Practice
Yunhui Zheng IBM Research, Saurabh Pujar IBM Research, Burn Lewis IBM Research, Luca Buratti IBM Research, Edward Epstein IBM Research, Bo Yang IBM Research, Jim A. Laredo IBM Research, USA, Alessandro Morari IBM Research, Zhong Su IBM Research
Pre-print Media Attached