* 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

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

16:00 - 17:30
Mining, Verifying, and LearningNIER - New Ideas and Emerging Results at E3 room
Chair(s): Mukul Prasad Fujitsu Laboratories of America
16:00
15m
Talk
Mining Container Image Repositories---MSR for Software Configurations and Beyond
NIER - New Ideas and Emerging Results
Tianyin Xu University of Illinois at Urbana-Champaign, Darko Marinov University of Illinois at Urbana-Champaign
Pre-print
16:15
15m
Talk
Explainable Software Analytics
NIER - New Ideas and Emerging Results
Hoa Khanh Dam University of Wollongong, Truyen Tran , Aditya Ghose
Pre-print
16:30
15m
Talk
Generalizing Specific-Instance Interpolation Proofs with SyGuS
NIER - New Ideas and Emerging Results
Muqsit Azeem , Kumar Madhukar TCS Innovation Labs (TRDDC), R Venkatesh
16:45
15m
Talk
Efficient Parametric Model Checking Using Domain-Specific Modelling Patterns
NIER - New Ideas and Emerging Results
Radu Calinescu University of York, UK, Kenneth Johnson , Colin Paterson
17:00
15m
Talk
Deep Learning UI Design Patterns of Mobile Apps
NIER - New Ideas and Emerging Results
17:15
15m
Short-paper
Code Review Comments: Language matters
NIER - New Ideas and Emerging Results
Vasiliki Efstathiou Athens University of Economics and Business, Diomidis Spinellis Athens University of Economics and Business
DOI Pre-print