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Thu 13 Oct 2022 10:00 - 10:20 at Gold A - Technical Session 24 - Human Aspects Chair(s): Silvia Abrahão

Exploratory testing is an effective testing approach which leverages the tester’s knowledge and creativity to design test cases to provoke and recognize failures at the system level from the end user’s perspective. Although some principles and guidelines have been proposed to guide exploratory testing, there are no effective tools for automatic generation of exploratory test scenarios (a.k.a soap opera tests). Existing test generation techniques rely on specifications, program differences and fuzzing, which are not suitable for exploratory test generation. In this paper, we propose to leverages the scenario and oracle knowledge in bug reports to generate soap opera test scenarios. We develop open information extraction methods to construct a system knowledge graph (KG) of user tasks and failures from the steps to reproduce, expected results and observed results in bug reports. We construct a proof-of-concept KG from 25,939 bugs of the Firefox browser. Our evaluation shows the constructed KG is of high quality. Based on the KG, we creates soap opera test scenarios by combining the scenarios of relevant bugs, and develop a web tool to present the created test scenarios and support exploratory testing. In our user study, 5 users find 18 bugs from 5 seed bugs in 2 hours using our tool, while the control group find only 5 bugs based on the recommended similar bugs.

Thu 13 Oct

Displayed time zone: Eastern Time (US & Canada) change

10:00 - 12:00
Technical Session 24 - Human AspectsResearch Papers / Journal-first Papers / NIER Track at Gold A
Chair(s): Silvia Abrahão Universitat Politècnica de València
10:00
20m
Research paper
Constructing a System Knowledge Graph of User Tasks and Failures from Bug Reports to Support Soap Opera Testing
Research Papers
Yanqi Su Australian National University, Zheming Han , Zhenchang Xing Australian National University, Xin Xia Huawei Software Engineering Application Technology Lab, Xiwei (Sherry) Xu CSIRO Data61, Liming Zhu CSIRO’s Data61; UNSW, Qinghua Lu CSIRO’s Data61
10:20
20m
Research paper
Data Augmentation for Improving Emotion Recognition in Software Engineering Communication
Research Papers
Mia Mohammad Imran Virginia Commonwealth University, Yashasvi Jain Drexel University, Preetha Chatterjee Drexel University, USA, Kostadin Damevski Virginia Commonwealth University
Pre-print
10:40
10m
Vision and Emerging Results
End-to-End Rationale Reconstruction
NIER Track
Mouna Dhaouadi University of Montreal, Bentley Oakes Université de Montréal, Michalis Famelis Université de Montréal
Pre-print
10:50
20m
Paper
Towards digitalization of requirements: Generating context-sensitive user stories from diverse specifications
Journal-first Papers
Padmalata Nistala Tata Consultancy Services Research, Asha Rajbhoj TCS Research, Vinay Kulkarni Tata Consultancy Services Research, Shivani Soni TCS Research, Kesav Vithal Nori IIIT Hyderabad, Raghu Reddy IIT Hyderabad
Link to publication DOI
11:10
20m
Paper
Which neural network makes more explainable decisions? An approach towards measuring explainabilityVirtual
Journal-first Papers
Mengdi Zhang Singapore Management University, Singapore, Jun Sun Singapore Management University, Jingyi Wang Zhejiang University
Link to publication DOI
11:30
20m
Paper
Automatically Identifying the Quality of Developer Chats for Post Hoc UseVirtual
Journal-first Papers
Preetha Chatterjee Drexel University, USA, Kostadin Damevski Virginia Commonwealth University, Nicholas A. Kraft UserVoice, Lori Pollock University of Delaware
Link to publication Media Attached