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ICSE 2021
Mon 17 May - Sat 5 June 2021

This program is tentative and subject to change.

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.

This program is tentative and subject to change.

Wed 26 May
Times are displayed in 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 SeamanUniversity of Maryland Baltimore County
14:30
20m
Paper
Automatic Web Testing using Curiosity-Driven Reinforcement LearningTechnical Track
Technical Track
YAN ZHENGNanyang Technological University, Yi LiuSouthern University of Science and Technology, Xiaofei XieNanyang Technological University, Yepang LiuSouthern University of Science and Technology, China, Lei MaUniversity of Alberta, Jianye HaoTianjin University, Yang LiuNanyang Technological University
Pre-print
14:50
20m
Paper
Evaluating SZZ Implementations Through a Developer-informed OracleTechnical Track
Technical Track
Giovanni RosaUniversity of Molise, Luca PascarellaUniversità della Svizzera italiana (USI), Simone ScalabrinoUniversity of Molise, Rosalia TufanoUniversità della Svizzera Italiana, Gabriele BavotaSoftware Institute, USI Università della Svizzera italiana, Michele LanzaSoftware Institute, USI Università della Svizzera italiana, Rocco OlivetoUniversity of Molise
Pre-print
15:10
20m
Paper
D2A: A Dataset Built for AI-Based Vulnerability Detection Methods Using Differential AnalysisSEIP
SEIP - Software Engineering in Practice
Yunhui ZhengIBM Research, Saurabh PujarIBM Research, Burn LewisIBM Research, Luca BurattiIBM Research, Edward EpsteinIBM Research, Bo YangIBM Research, Jim A. LaredoIBM Research, USA, Alessandro MorariIBM Research, Zhong SuIBM Research
Pre-print

Thu 27 May
Times are displayed in 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 ZHENGNanyang Technological University, Yi LiuSouthern University of Science and Technology, Xiaofei XieNanyang Technological University, Yepang LiuSouthern University of Science and Technology, China, Lei MaUniversity of Alberta, Jianye HaoTianjin University, Yang LiuNanyang Technological University
Pre-print
02:50
20m
Paper
Evaluating SZZ Implementations Through a Developer-informed OracleTechnical Track
Technical Track
Giovanni RosaUniversity of Molise, Luca PascarellaUniversità della Svizzera italiana (USI), Simone ScalabrinoUniversity of Molise, Rosalia TufanoUniversità della Svizzera Italiana, Gabriele BavotaSoftware Institute, USI Università della Svizzera italiana, Michele LanzaSoftware Institute, USI Università della Svizzera italiana, Rocco OlivetoUniversity of Molise
Pre-print
03:10
20m
Paper
D2A: A Dataset Built for AI-Based Vulnerability Detection Methods Using Differential AnalysisSEIP
SEIP - Software Engineering in Practice
Yunhui ZhengIBM Research, Saurabh PujarIBM Research, Burn LewisIBM Research, Luca BurattiIBM Research, Edward EpsteinIBM Research, Bo YangIBM Research, Jim A. LaredoIBM Research, USA, Alessandro MorariIBM Research, Zhong SuIBM Research
Pre-print
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