* ICSE 2018 *
Sun 27 May - Sun 3 June 2018 Gothenburg, Sweden
Wed 30 May 2018 11:40 - 12:00 at G1 room - Software Evolution and Maintenance I Chair(s): Chanchal K. Roy

Numerous automated techniques have been proposed to reduce the cost of software debugging, a notoriously time-consuming and human-intensive activity. Among these techniques, Statistical Fault Localization (SFL) is particularly popular. One issue with SFL is that it is based on strong, often unrealistic assumptions on how developers behave when debugging. To address this problem, we propose Enlighten, an interactive, feedback-driven fault localization technique. Given a failing test, Enlighten (1) leverages SFL and dynamic dependence analysis to identify suspicious method invocations and corresponding data values, (2) presents the developer with a query about the most suspicious invocation expressed in terms of inputs and outputs, (3) encodes the developer feedback on the correctness of individual data values as extra program speci cations, and (4) repeats these steps until the fault is found. We evaluated Enlighten in two ways. First, we applied Enlighten to 1,807 real and seeded faults in 3 open source programs using an automated oracle as a simulated user; for over 96% of these faults, Enlighten required less than 10 interactions with the simulated user to localize the fault, and a sensitivity analysis showed that the results were robust to erroneous responses. Second, we performed an actual user study on 4 faults with 24 participants and found that participants who used Enlighten performed signi cantly better than those not using our tool, in terms of both number of faults localized and time needed to localize the faults.

Enlightened Debugging (Enlightened Debugging.pptx)7.13MiB

Wed 30 May

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

11:00 - 12:30
Software Evolution and Maintenance ITechnical Papers / Journal first papers at G1 room
Chair(s): Chanchal K. Roy University of Saskatchewan
Neuro-Symbolic Program Repair for Correcting Introductory Programming Assignments
Technical Papers
Sahil Bhatia , Pushmeet Kohli Microsoft Research, Rishabh Singh Google Brain
Automated Localization for Unreproducible BuildsAward
Technical Papers
Zhilei Ren , He Jiang , Jifeng Xuan , Zijiang Yang Western Michigan University
Enlightened Debugging
Technical Papers
Xiangyu Li Georgia Institute of Technology, Shaowei Zhu Georgia Institute of Technology, Marcelo d'Amorim Federal University of Pernambuco, Alessandro Orso Georgia Tech
Pre-print File Attached
Research paper
Experiences and Challenges in Building a Data Intensive System for Data Migration
Journal first papers
Marco Scavuzzo Politecnico di Milano, Elisabetta Di Nitto Politecnico di Milano, Danilo Ardagna
Link to publication DOI
Q&A in groups
Technical Papers