Call for virtual participation. http://planet-research20.org/ser2009

Software is BY and FOR people.

This fact has been neglected for too long as the terms “computer science” and “computer languages” testify. However, it should be clear now that collaboration between many stakeholders is one of the most important key factor in the success (or failure) of large software projects and complex software ecosystems. In this context, web 2.0 technologies provide new opportunities to share information between stakeholders, improve communications and build collaborative tools and processes. These technologies could also have a dramatic impact on how research is performed, leading to collaborative and social research, beyond the traditional separation between small research and big research. This workshop will explore the various facets of Software Engineering 2.0 and Research 2.0, considering not only collaborative tools, but also social aspects related to community engineering. The workshop will be physically held at toronto during IBM CASCON, the meeting of minds, today Nov 5th, but we anticipated on-line activities during and after the workshop through the workshop web 2.0 web site. You are cordially invited to join the network and to ask questions and discuss on-line with us.

Program

“Software Engineering 2.0 and Research 2.0 – What/Why the hell is that?”
Jean-Marie Favre, Principal Scientist at One Tree Technologies – University of Grenoble, LIG, Aconit

“Notification Design Research in Jazz”
Jin Li, User Experience Lead, IBM, Canada

“Personal Information Management for Software Engineering Researchers”
Dragan Gaševi?, Athabasca University, Canada

“Integrative Collaborative Research”
Joanna Ng, Head of Research, IBM CAS Canada

“Socialization of Software”
Grady Booch, IBM Chief Scientist, USA

“The future of Software Engineering 2.0 and Research 2.0″
Fishbowl panel – Every body is invited to participate (in flesh or online!)

Do not hesitate to join the research community. It’s fun and free. Go to: http://planet-research20.org/ser2009 community tab. But please give your REAL IDENTITY and upload your portrait. This social network is for professional use only.

May the fun be with you and looking forward to meet you in flesh or on-line.

Jean-marie on behalf of the SER2009 organizing committee

Organizing Committee

Denis Avrilionis, OneTree Technologies, Luxembourg
Grady Booch, IBM Research, USA
Jean-Marie Favre, OneTree Technologies, Univ. of Grenoble, LIG, ACONIT, Luxembourg/France
Hausi Müller, University of Victoria, Canada,

Here is a preview of recently submitted papers (created with Wordle.net).

Software development can be challenging because of the large information spaces that developers must navigate. Without assistance, developers can become bogged down, and spend a disproportionate amount of their time seeking information at the expense of other value-producing tasks. Recommendation Systems for Software Engineering are software tools that can assist developers with a wide range of activities, from reusing code to writing effective bug reports. We provide an overview of recommendation systems for software engineering: what they are, what they can do for developers, and what they might do in the future.

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For many software projects, bug tracking systems play a central role in supporting collaboration between the developers and the users of the software. To better understand this collaboration and how tool support can be improved, we have quantitatively and qualitatively analysed the questions asked in a sample of 600 bug reports from the MOZILLA and ECLIPSE projects. We categorised the questions and analysed response rates and times by category and project. Our results show that the role of users goes beyond simply reporting bugs: their active and ongoing participation is important for making progress on the bugs they report. Based on the results, we suggest four ways in which bug tracking systems can be improved.

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Predicting Defects in SAP Java Code: An Experience Report (with Tilman Holschuh, Markus Päuser, Kim Herzig, Rahul Premraj, Andreas Zeller).
In a study on a large SAP Java system, we evaluated and compared a number of defect predictors, based on code features such as complexity metrics, static error detectors, change frequency, or component imports.
Software Engineering in Practice Track.

Tilman’s presentation

Improving Bug Tracking Systems (with Rahul Premraj, Jonathan Sillito, and Silvia Breu). We present a prototype of an interactive bug tracking system that gathers relevant information from users and automatically identifies files that need to be fixed to resolve a bug.
New Ideas and Emerging Results Track.

Silvia’s poster
Rahul’s presentation

Also visit the official ICSE 2009 Post-Conference webpage, which has many other exciting talks, posters, and videos.

This week I will attend the USENIX 2009 Annual Technical Conference, where Stephan Neuhaus will present one of our papers.

The Beauty and the Beast: Vulnerabilities in Red Hat’s Packages.
In an empirical study of 3241 Red Hat packages, we show that software vulnerabilities correlate with dependencies between packages. With formal concept analysis and statistical hypothesis testing, we identify dependencies that decrease the risk of vulnerabilities (beauties) or increase the risk (beasts).
Session “Bugs and Software Updates”. Friday 2-3:30pm.

DEFECTS 2009 – Second International Workshop on Defects in Large Software Systems, Chicago, July 19, 2009.

Bugs are everywhere in today’s software and because of the huge economic damage they are actively studied by research. The goal of this one-day workshop is to connect the different research communities with each other and with industry. The workshop will provide a forum for researchers as well as practitioners to discuss issues related to all aspects of bugs. Researchers can present their tools and techniques and make them accessible to industry. Participants from industry can share their experiences and help identifying new and promising research directions.

Register now on the ISSTA website.
Early registration ends soon (June 19).

Prediction of software defects works well within projects as long as there is a sufficient amount of data available to train any models. However, this is rarely the case for new software projects and for many companies. So far, only a few have studies focused on transferring prediction models from one project to another. In this paper, we study cross-project defect prediction models on a large scale. For 12 real-world applications, we ran 622 cross-project predictions. Our results indicate that cross-project prediction is a serious challenge, i.e., simply using models from projects in the same domain or with the same process does not lead to accurate predictions. To help software engineers choose models wisely, we identified factors that do influence the success of cross-project predictions. We also derived decision trees that can provide early estimates for precision, recall, and accuracy before a prediction is attempted.

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