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ASE 2021
Mon 15 - Fri 19 November 2021 Australia

This program is tentative and subject to change.

Thu 18 Nov 2021 22:00 - 22:20 at Koala - Modelling (any band 2)

In agile software development, proper team structures and effort estimates are crucial to ensure the on-time delivery of software projects. Delivery performance can vary due to the influence of changes in teams, resulting in team dynamics that remain largely unexplored. In this paper, we explore the effects of various aspects of teamwork on delays in software deliveries. We conducted a case study at ABC and analyzed historical log data from 765,200 user stories and 571 teams to identify team factors characterizing delayed user stories. Based on these factors, we built models to predict the likelihood and duration of delays in user stories. The evaluation results show that the use of team-related features leads to a significant improvement in the predictions of delay, achieving on average 74%-82% precision, 78%-86% recall and 76%-84% F-measure. Moreover, our results show that team-related features can help improve the prediction of delay likelihood, while delay duration can be explained exclusively using them. Finally, training on recent user stories using a sliding window setting improves the predictive performance; our predictive models perform significantly better for teams that have been stable. Overall, our results indicate that planning in agile development settings can be significantly improved by incorporating team-related information and incremental learning methods into analysis/predictive models.

This program is tentative and subject to change.

Thu 18 Nov

Displayed time zone: Hobart change

22:00 - 23:00
Modelling (any band 2)Research Papers at Koala
22:00
20m
Talk
Modeling Team Dynamics for the Characterization and Prediction of Delays in User Stories
Research Papers
Elvan Kula Delft University of Technology, Arie van Deursen Delft University of Technology, Netherlands, Georgios Gousios Facebook & Delft University of Technology
22:20
20m
Talk
DeepMemory: Model-based Memorization Analysis of Deep Neural Language Models
Research Papers
Derui Zhu Technical University of Munich, Jinfu Chen Centre for Software Excellence, Huawei, Canada, Weiyi Shang Concordia University, Xuebing Zhou Huawei Munich Research Center, Jens Grossklags Technical University of Munich, Ahmed E. Hassan Queen's University
22:40
20m
Talk
Automated Verification of Go Programs via Bounded Model CheckingACM Distinguished Paper
Research Papers
Nicolas Dilley University of Kent, Julien Lange Royal Holloway University of London
Pre-print