An Evolutionary Approach to Adapt Tests Across Mobile Apps (AST 2021 - 2nd ACM/IEEE International Conference on Automation of Software Test AST 2021)

Who

Leonardo Mariani, Mauro Pezze, Valerio Terragni, Daniele Zuddas

Track

AST 2021

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When

Fri 21 May 2021 12:00 - 12:30 at AST Room - Testing for Specific Domains - 1 Chair(s): Antonia Bertolino

Abstract

Automatic generators of GUI tests often fail to generate semantically relevant test cases, and thus miss important test scenarios. To address this issue, test adaptation techniques can be used to automatically generate semantically meaningful GUI tests from test cases of applications with similar functionalities. In this paper, we present ADAPTDROID, a technique that approaches the test adaptation problem as a search-problem, and uses evolutionary testing to adapt GUI tests (including oracles) across similar Android apps. In our evaluation with 32 popular Android apps, ADAPTDROID successfully adapted semantically relevant test cases in 11 out of 20 cross-app adaptation scenarios.

Link to Preprint

https://arxiv.org/abs/2104.05233

Leonardo Mariani

University of Milano Bicocca

Italy

Mauro Pezze

USI Lugano, Switzerland

Switzerland

Valerio Terragni

The University of Auckland

New Zealand

Daniele Zuddas

Università della Svizzera italiana (USI)

Italy

Time Zone

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Session Program

Fri 21 May
Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

12:00 - 13:15	Testing for Specific Domains - 1AST 2021 at AST Room Chair(s): Antonia Bertolino CNR-ISTI

12:00 30m Long-paper		An Evolutionary Approach to Adapt Tests Across Mobile Apps AST 2021 Leonardo Mariani University of Milano Bicocca, Mauro Pezze USI Lugano, Switzerland, Valerio Terragni The University of Auckland, Daniele Zuddas Università della Svizzera italiana (USI) Pre-print Media Attached
12:30 15m Short-paper		A framework for the automation of testing computer vision systems AST 2021 Franz Wotawa , Ledio Jahaj Technische Universitaet Graz, Lorenz Klampfl Graz University of Technology, Austria Pre-print Media Attached
12:45 30m Long-paper		Multimodal Surprise Adequacy Analysis of Inputs for Natural Language Processing DNN Models AST 2021 Seah Kim KAIST, Shin Yoo Korea Advanced Institute of Science and Technology Pre-print Media Attached

Information for Participants

Fri 21 May 2021 12:00 - 13:15 at AST Room - Testing for Specific Domains - 1 Chair(s): Antonia Bertolino

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