Friday, May 20, 2016

ICSE 2016 presentations

Type: Presentation

Venue: ICSE 2016 (Doctoral Symposium and CSI-SE workshop)


I presented the following papers in ICSE 2016 and collocated events:


Left: Leonardo Mariani (University of Milan Bicocca)
Right: James Clause (University of Delaware)


Friday, February 26, 2016

Measuring User Influence in Github: The Million Follower Fallacy

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Type: Publication (accepted)

Venue: 3rd International Workshop on CrowdSourcing In Software Engineering; CSI-SE 2016
May 16, 2016, Austin, TX, USA

Authors: Ali Sajedi Badashian, Eleni Stroulia
Department of Computing Science, University of Alberta, Canada

Abstract
Influence in social networks has been extensively studied for collaborative-filtering recommendations and marketing purposes. We are interested in the notion of influence in Software Social Networks (SSNs); more specifically, we want to answer the following questions: 1) What does “influence” mean in SSNs? Given the variety of types of interactions supported in these networks and the abundance of centrality-type metrics, what is the nature of the influence captured by these matrics? 2) Are there silos of influence in these platforms or does influence span across thematic boundaries?

To investigate these two questions, we first conducted an in-depth comparison of three influence metrics, number of followers, number of forked projects, and number of project watchers in GitHub1 (the largest code-sharing and versioncontrol system). Next, we examined how the influence of the top software engineering people in GitHub is spread over different programming languages.

Our results indicate (a) that the three influence metrics capture two major characteristics: popularity and content value (code reusability) and (b) that the influence of influentials is spread over more than one programming language, but there is no specific trend toward any two programming languages.

Keywords:
Software engineering, influence, Software repositories, programming languages, software social network analysis, crowdsourcing

Saturday, January 23, 2016

Realistic Bug Triaging

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Type: Publication (accepted)

Venue: The 38th International Conference on Software Engineering
May 14-22, 2016, Austin, TX, USA

Authors: Ali Sajedi Badashian
Department of Computing Science, University of Alberta, Canada

Abstract
Bug triaging, i.e., assigning a bug report to the developer “best” able to address it, involves identifying a list of developers qualified to understand and address the bug report and ranking them according to their expertise. Most research in this area addresses this task by matching the description of the bug report and the developers’ prior development and bug-fixing activities.
This thesis puts forward a more realistic formulation of the bug-triaging task. First, we develop a novel model of the developers’ expertise, taking into account relevant evidence from their code-development conributions, as well as their contributions to relevant Question-and-Answer (Q&A) platforms. Second, we adopt an economics perspective to the task, and we propose to generalize bug-triaging from“assigning one bug to the best developer”to“cost-effectively assigning multiple peding bugs to a set of qualified and available developers.” In this paper, we report on our early results on the value of broadening the notion of developer’s expertise to take into account evidence from Q&Aplatforms.

Keywords:
Bug triaging, bug assignment, expertise retrieval, crowdsoucring, GitHub, Stack Overflow