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ICSE 2020
Wed 24 June - Thu 16 July 2020
Fri 10 Jul 2020 16:25 - 16:33 at Goguryeo - A23-Requirements Chair(s): Dalal Alrajeh

A software system’s design determines many of its properties, such as maintainability and performance. To uphold desired properties in a system, developers must be aware of its design. When developers are not aware of a system’s design, choices they make can erode desired system properties [1]. Unfortunately, developers often do not have access to in- formation about a system’s current design. One approach that has been investigated to solve this issue is to recover design automatically from projects artifacts [2]. Most of the existing approaches focus on how a system works by extracting struc- tural (e.g., [3]) and behaviour (e.g., [4]) information, rather than information about the desired design properties, such as robustness or performance. Recently, Brunet et al. and Tsay et al. have identified that developer discussions, captured in project artifacts, such as issue reports, include discussions of design [5], [6]. Tsay et al. have further showed that these discussions can be a major factor in deciding how a system evolves, suggesting that the discussions include information that goes beyond how a system works to explain why certain choices were made. In this paper, we explore whether it is possible to locate automatically where design is discussed in on-line developer discussions. We introduce a classifier that can locate para- graphs in pull request discussions that pertain to design with an average AUC score of 0.87. We show that this classifier, when applied to projects on which it was not trained, agrees with the identification of design points by humans with an average AUC score of 0.79. We finally describe how this classifier could be used as the basis of tools to improve such tasks as reviewing code and implementing new features. This paper shows that there is useful design information latent in on-line developer discussion and provides a means to locate this information at a coarse granularity. Future research can determine how to locate more specific and nuanced design information and investigate how to semantically model the information to produce even more useful tools for developers.

Conference Day
Fri 10 Jul

Displayed time zone: (UTC) Coordinated Universal Time change

16:05 - 17:05
A23-RequirementsJournal First / Technical Papers / New Ideas and Emerging Results at Goguryeo
Chair(s): Dalal AlrajehImperial College London
Caspar: Extracting and Synthesizing User Stories of Problems from App ReviewsTechnical
Technical Papers
Hui GuoNorth Carolina State University, Munindar P. SinghNorth Carolina State University
Dealing with Non-Functional Requirements in Model-Driven Development: A SurveyJ1
Journal First
David AmellerUniversitat Politècnica de Catalunya, Xavier FranchUniversitat Politècnica de Catalunya, Cristina GómezUniversitat Politècnica de Catalunya, Silverio Martínez-FernándezUPC-BarcelonaTech, João AraújoUniversidade Nova de Lisboa, Stefan BifflVienna University of Technology, Jordi CabotICREA - UOC, Vittorio CortellesaUniversity of L’Aquila, Daniel MendezTechnische Universität München, Ana MoreiraFCT / Universidade Nova de Lisboa, Henry MucciniUniversity of L'Aquila, Italy, Antonio VallecilloUniversity of Málaga, Spain, Manuel WimmerJohannes Kepler University Linz, Vasco AmaralUniversidade Nova de Lisboa, Wolfang BöhmTechnische Universität München, Hugo BrunelièreInria, Mines Nantes & LINA, Loli BurgueñoUniversidad de Malaga, Miguel GoulaoNOVA-LINCS, FCT/UNL, Sabine TeuflFortiss GmbH, Luca BerardinelliJohannes Kepler University Linz
Locating Latent Design Information in Developer Discussions: A Study on Pull RequestsJ1
Journal First
Giovanni VivianiUniversity of British Columbia, Michalis FamelisUniversité de Montréal, Xin XiaMonash University, Calahan Janik-JonesUniversity of Toronto, Gail MurphyUniversity of British Columbia
Status Quo in Requirements Engineering: A Theory and a Global Family of SurveysJ1
Journal First
Stefan WagnerUniversity of Stuttgart
Link to publication DOI Pre-print
Corba: Crowdsourcing to Obtain Requirements from Regulations and BreachesJ1
Journal First
Hui GuoNorth Carolina State University, Ozgur KafaliUniversity of Kent, Anne-Liz JeukengUniversity of Florida, Laurie WilliamsNorth Carolina State University, Munindar P. SinghNorth Carolina State University
With Registered Reports Towards Large Scale Data CurationNIER
New Ideas and Emerging Results
Steffen HerboldUniversity of Göttingen