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SPLASH 2017
Sun 22 - Fri 27 October 2017 Vancouver, Canada
Thu 26 Oct 2017 16:37 - 16:59 at Regency A - Testing Chair(s): Christian Hammer

Localizing failure-inducing code is essential for software debugging. Manual fault localization can be quite tedious, error-prone, and time-consuming. Therefore, a huge body of research efforts have been dedicated to automated fault localization. Spectrum-based fault localization, the most intensively studied fault localization approach based on test execution information, may have limited effectiveness, since a code element executed by a failed tests may not necessarily have impact on the test outcome and cause the test failure. To bridge the gap, mutation-based fault localization has been proposed to transform the programs under test to check the impact of each code element for better fault localization. However, there are limited studies on the effectiveness of mutation-based fault localization on sufficient number of real bugs. In this paper, we perform an extensive study to compare mutation-based fault localization techniques with various state-of-the-art spectrum-based fault localization techniques on 357 real bugs from the Defects4J benchmark suite. The study results demonstrate the effectiveness of mutation-based fault localization, as well as firstly revealing a number of guidelines for further improving the mutation-based fault localization. Based on the learnt guidelines, we further transform test outputs/messages and test code to obtain various mutation information. Then, we propose TraPT, an automated Learning-to-Rank technique to fully explore the obtained mutation information for effective fault localization. The experimental results show that TraPT localizes at least 62.79% more bugs within Top-1 than state-of-the-art spectrum or mutation based techniques when using the default setting of LIBSVM.

Thu 26 Oct

Displayed time zone: Tijuana, Baja California change

15:30 - 17:22
TestingOOPSLA at Regency A
Chair(s): Christian Hammer University of Potsdam
15:30
22m
Talk
A Solver-Aided Language for Test Input Generation
OOPSLA
Talia Ringer University of Washington, Dan Grossman University of Washington, Daniel Schwartz-Narbonne Amazon, n.n., Serdar Tasiran Amazon, n.n.
DOI
15:52
22m
Talk
Automated Testing of Graphics Shader Compilers
OOPSLA
Alastair F. Donaldson Imperial College London, Hugues Evrard Imperial College London, UK, Andrei Lascu Imperial College London, Paul Thomson Imperial College London
DOI
16:14
22m
Talk
Bounded Exhaustive Test-Input Generation on GPUs
OOPSLA
Ahmet Celik University of Texas at Austin, USA, Sreepathi Pai University of Rochester, Sarfraz Khurshid University of Texas at Austin, Milos Gligoric University of Texas at Austin
DOI
16:37
22m
Talk
Transforming Programs and Tests in Tandem for Fault Localization
OOPSLA
Xia Li University of Texas at Dallas, USA, Lingming Zhang
DOI
16:59
22m
Talk
Type Test Scripts for TypeScript Testing
OOPSLA
Erik Krogh Kristensen Aarhus University, Denmark, Anders Møller Aarhus University
DOI