* ICSE 2018 *
Sun 27 May - Sun 3 June 2018 Gothenburg, Sweden
Wed 30 May 2018 16:15 - 16:30 at E3 room - Mining, Verifying, and Learning Chair(s): Mukul Prasad

Software analytics has been the subject of considerable recent attention but is yet to receive significant industry traction. One of the key reasons is that software practitioners are reluctant to trust predictions produced by the analytics machinery without understanding the rationale for those predictions. While complex models such as deep learning and ensemble methods improve predictive performance, they have limited explainability. In this paper, we argue that making software analytics models explainable to software practitioners is as important as achieving accurate predictions. Explainability should therefore be a key measure for evaluating software analytics models. We envision that explainability will be a key driver for developing software analytics models that are useful in practice. We outline a research roadmap for this space, building on social science, explainable artificial intelligence and software engineering.

Wed 30 May

icse-2018-New-Ideas-and-Emerging-Results
16:00 - 17:30: NIER - New Ideas and Emerging Results - Mining, Verifying, and Learning at E3 room
Chair(s): Mukul PrasadFujitsu Laboratories of America
icse-2018-New-Ideas-and-Emerging-Results16:00 - 16:15
Talk
Tianyin XuUniversity of Illinois at Urbana-Champaign, Darko MarinovUniversity of Illinois at Urbana-Champaign
Pre-print
icse-2018-New-Ideas-and-Emerging-Results16:15 - 16:30
Talk
Hoa Khanh DamUniversity of Wollongong, Truyen Tran, Aditya Ghose
Pre-print
icse-2018-New-Ideas-and-Emerging-Results16:30 - 16:45
Talk
Muqsit Azeem, Kumar MadhukarTCS Innovation Labs (TRDDC), R Venkatesh
icse-2018-New-Ideas-and-Emerging-Results16:45 - 17:00
Talk
icse-2018-New-Ideas-and-Emerging-Results17:00 - 17:15
Talk
icse-2018-New-Ideas-and-Emerging-Results17:15 - 17:30
Short-paper
Vasiliki EfstathiouAthens University of Economics and Business, Diomidis SpinellisAthens University of Economics and Business
DOI Pre-print