Q-learning is an attractive option for GUI testing, allowing for sophisticated test generation strategies that learn and exploit effective GUI interactions. However, learning comprehensive models requires very long test sessions, and the issue is exacerbated by the needs of both testers, who might want to run multiple testing sessions to fine-tune the test strategy to their applications under test, and researchers, who might want to experiment with multiple alternative approaches. To address these concerns, this paper presents GTPQL, a testing tool that supports GUI testing with a parallel deployment parallel Q-learning, and the can be flexibly configured and extended with multiple state-space abstractions and Q-leaning variants.
Demo video: https://youtu.be/G78l9KrFpnU
Wed 17 MayDisplayed time zone: Hobart change
15:45 - 17:15 | Test generationSEIP - Software Engineering in Practice / DEMO - Demonstrations / Technical Track / NIER - New Ideas and Emerging Results / Journal-First Papers at Meeting Room 102 Chair(s): Chunyang Chen Monash University | ||
15:45 7mTalk | SoapOperaTG: A Tool for System Knowledge Graph Based Soap Opera Test Generation DEMO - Demonstrations Yanqi Su Australian National University, Zheming Han , Zhenchang Xing CSIRO’s Data61; Australian National University, Xiwei (Sherry) Xu CSIRO’s Data61, Liming Zhu CSIRO’s Data61, Qinghua Lu CSIRO’s Data61 | ||
15:52 7mTalk | GUI Testing to the Power of Parallel Q-Learning DEMO - Demonstrations Marco Mobilio University of Milano Bicocca, Diego Clerissi University of Milano-Bicocca, Giovanni Denaro University of Milano-Bicocca, Italy, Leonardo Mariani University of Milano-Bicocca | ||
16:00 15mTalk | BADGE: Prioritizing UI Events with Hierarchical Multi-Armed Bandits for Automated UI Testing Technical Track Dezhi Ran Peking University, Hao Wang Peking University, China, Wenyu Wang University of Illinois Urbana-Champaign, Tao Xie Peking University | ||
16:15 15mTalk | Efficiency Matters: Speeding Up Automated Testing with GUI Rendering Inference Technical Track Sidong Feng Monash University, Mulong Xie Australian National University, Chunyang Chen Monash University Pre-print | ||
16:30 15mTalk | CodaMOSA: Escaping Coverage Plateaus in Test Generation with Pre-trained Large Language Models Technical Track Caroline Lemieux University of British Columbia, Jeevana Priya Inala Microsoft Research, Shuvendu K. Lahiri Microsoft Research, Siddhartha Sen Microsoft Research | ||
16:45 15mTalk | Simulation-Driven Automated End-to-End Test and Oracle Inference SEIP - Software Engineering in Practice Shreshth Tuli Meta Platforms Inc. and Imperial College, Kinga Bojarczuk Facebook, Natalija Gucevska Facebook, Mark Harman University College London, Xiaoyu Wang Meta Platforms Inc., Graham Wright Meta Platforms Inc. | ||
17:00 7mTalk | Reasoning-Based Software Testing NIER - New Ideas and Emerging Results Luca Giamattei Università di Napoli Federico II, Roberto Pietrantuono Università di Napoli Federico II, Stefano Russo Università di Napoli Federico II Pre-print | ||
17:07 7mTalk | Automated Generation and Evaluation of JMH Microbenchmark Suites From Unit Tests Journal-First Papers Mostafa Jangali Concordia University, Yiming Tang Concordia University, Niclas Alexandersson Chalmers University of Technology, Philipp Leitner Chalmers University of Technology, Sweden / University of Gothenburg, Sweden, Jinqiu Yang Concordia University, Weiyi Shang University of Waterloo | ||