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PROMISE 2013 : The 9th International Conference on Predictive Models in Software EngineeringConference Series : Predictive Models in Software Engineering | |||||||||||||||
Link: http://promisedata.org/2013/ | |||||||||||||||
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Call For Papers | |||||||||||||||
PROMISE'13
The 9th International Conference on Predictive Models in Software Engineering Oct 9, 2013, Baltimore, Maryland, USA http://promisedata.org/2013/ (Co-located with ESEM 2013) IMPORTANT DATES: Abstracts due: April 05, 2013 Submissions due: April 12, 2013 Author notification: June 10, 2013 Camera-ready copy due: June 28, 2013 KEYNOTE SPEAKER: Tom Zimmermann, Microsoft Research PROMISE conference is an annual forum for researchers and practitioners to present, discuss and exchange ideas, results, expertise and experiences in construction and/or application of prediction models in software engineering. Such models could be targeted at: planning, design, implementation, testing, maintenance, quality assurance, evaluation, process improvement, management, decision making, and risk assessment in software and systems development. PROMISE is distinguished from similar forums with its public data repository and focus on methodological details, providing a unique interdisciplinary venue for software engineering and machine learning communities, and seeking for verifiable and repeatable prediction models that are useful in practice. SPECIAL THEME: The special theme of PROMISE’13 is predictions across projects, contexts and organizations, where the predictions employ approaches (e.g. transfer learning, instance selection, data filtering) with an impact that is useful in practice, in order to solve the problem of learning under concept drift (across time and space). TOPICS OF INTEREST: * (Application oriented): Predicting for cost, effort, quality, defects, business value; quantification and prediction of other intermediate or final properties of interest in software development regarding people, process or product aspects; using predictive models in policy and decision making; using predictive models in different settings, e.g. lean/agile, waterfall, distributed, community-based software development. * (Theory oriented): Interdisciplinary and novel approaches to predictive modeling that contribute to the theoretical body of knowledge in software engineering; verifying/refuting/challenging previous theory and results; the effectiveness of human experts vs. automated models in predictions. * (Data and model oriented): Data quality, sharing, and privacy; ethical issues related to data collection; metrics; contributions to the repository; model construction, evaluation, sharing and reusability; tools and frameworks to support researchers and practitioners to collect data and construct models to share/repeat experiments and results. KINDS OF PAPERS: We invite all kinds of empirical studies on the topics of interest (e.g. case studies, meta-analysis, replications, experiments, simulations, surveys etc.), as well as industrial experience reports detailing the application of prediction technologies and their effectiveness in industrial settings. Both positive and negative results are welcome, though negative results should still be based on rigorous research and provide details on lessons learned. Following the tradition, PROMISE'13 will give the highest priority to empirical studies based on publicly available datasets. It is therefore encouraged, but it is not mandatory, that conference attendees contribute the data used in their analysis to the on-line PROMISE data repository. We solicit both full and short papers. Short papers are intended to disseminate new ideas, on-going work and preliminary results for early feedback, and do not necessarily require complete results as in full papers. The deadline for short papers is the same as full papers. SUBMISSIONS: * Submissions must be original work, not published or under review elsewhere. * Submissions must conform to the ACM SIG proceedings templates from http://goo.gl/wE1k. * Submissions must not exceed 10 (4) pages for full (short) papers including references. * Papers should be submitted via Easychair (please choose either “full” or “short” papers): http://www.easychair.org/conferences/?conf=promise2013. * Accepted papers will be published in the ACM digital library. SPECIAL ISSUE: The venue for the special issue is TBA. Previous PROMISE special issues have appeared in IEEE Software, Empirical Software Engineering Journal, Information and Software Technology Journal, and Automated Software Engineering Journal. ORGANIZATION: Steering Committee: Stefan Wagner, University of Stuttgart (General Chair) Burak Turhan, University of Oulu (PC Chair) Ye Yang, Chinese Academy of Science (Publicity Chair) Ayse Bener, Ryerson University (Local Org. Chair) Programme Committee: Lefteris Angelis, Aristotle University of Thessaloniki Ayse Bener, Ryerson University Christian Bird, Microsoft Research David Bowes, University of Hertfordshire Daniela Da Cruz, University of Minho Massimiliano Di Penta, RCOST - University of Sannio Harald Gall, University of Zurich Vahid Garousi, University of Calgary Tracy Hall, Brunel University Mark Harman, University College London Rachel Harrison, University of Oxford Jacky Keung, The Hong Kong Polytechnic University Sunghun Kim, The Univ. of Hong Kong Science and Tech. Ekrem Kocaguneli, West Virginia University Lech Madeyski, Wroclaw University of Technology Kenichi Matsumoto, Nara Inst. of Science and Tech. Emilia Mendes, Blekinge Institute of Technology Tim Menzies, West Virginia University Leandro Minku, The University of Birmingham Thomas Ostrand, AT&T Labs - Research Daryl Posnett, UC Davis Rudolf Ramler, Software Competence Center Hagenberg GmbH Daniel Rodriguez, The University of Alcalá Guenther Ruhe, University of Calgary Federica Sarro, University College London Carolyn Seaman, UMBC Martin Shepperd, Brunel University Qinbao Song, Xi'an Jiaotong University Ayse Tosun Misirli, University of Oulu Burak Turhan, University of Oulu Stefan Wagner, University of Stuttgart Dietmar Winkler, Vienna University of Technology Ye Yang, Chinese Academy of Sciences Hongyu Zhang, Tsinghua University Yuming Zhou, Nanjing University |
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