Automated Testing Tools for Android: Are We There Yet in Industrial Cases?

Speaker:        Wing Lam
                Department of Computer Science
                University of Illinois at Urbana-Champaign

Title:          "Automated Testing Tools for Android: Are We There Yet in
                 Industrial Cases?"

Date:           Wednesday, 27 December 2017

Time:           2:00pm - 3:00pm

Venue:          Room 2463 (via lift 25/26), HKUST

Abstract:

Monkey, a random testing tool from Google, has been popularly used in
industrial practices for automatic test input generation for Android due
to its wide applicability, e.g., ease of use and compatibility with
different Android platforms. Recently, Monkey has been under the spotlight
of the research community: recent studies found out that none of the
studied tools from the academia were better than Monkey when applied on a
set of open source Android apps. Besides automatic test input generation
tools such as Monkey, a variety of record and-replay tools for Android
from the academia or industry can be used by developers to record and
automate the replay of complicated usage scenarios of their app. To
investigate whether these two kinds of automated testing tools for Android
are applicable and effective for testing industrial Android apps, the
first of our recent efforts was on applying Monkey to WeChat, a popular
messenger app with over 900 million monthly active users, and discovering
many limitations of Monkey there. We then developed new techniques to
address some of these limitations. The second of our recent efforts was on
applying and comparing popular record-and-replay tools from researchers
and practitioners to test three popular industrial apps, and highlighting
future directions for improving these tools to better address testing
complications of industrial apps. This talk presents the findings from
these two recent efforts (published in FSE 2016 Industry, ICSE 2017 SEIP,
and ESEC/FSE 2017 Industry tracks) and discusses the lessons learned and
future directions in developing techniques and tools for industrial
adoption.


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Biography:

Wing Lam is a Ph.D. student in the Department of Computer Science at the
University of Illinois at Urbana-Champaign, USA. He is advised by
Professor Tao Xie and is a member of the Illinois Automated Software
Engineering Lab. He received a Bachelor's in Computer Science with Honors
from the Department of Computer Science & Engineering at the University of
Washington, advised by Professor Michael Ernst in 2014. In the past, he
interned at Google, Microsoft Research, and Fujitsu Laboratories of
America and worked fulltime as a mobile application developer at
Whitepages Inc. His research interests are in software engineering,
focusing on software testing and program analysis. He received an NSF
Graduate Research Fellowship Honorable Mention, Illinois Technology
Foundation Fifty for the Future Award, Ray Ozzie Computer Science
Fellowship, and a State Farm Companies Foundation Doctoral Scholarship.
His homepage is at http://winglam2.web.engr.illinois.edu/.