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PROMISE 2011: Banff, Alberta, Canada
- Tim Menzies:
Proceedings of the 7th International Conference on Predictive Models in Software Engineering, PROMISE 2011, Banff, Alberta, Canada, September 20-21, 2011. ACM 2011, ISBN 978-1-4503-0709-3 - Laurie A. Williams:
Seven habits of highly impactful empirical software engineers. 1 - Robert M. Bell, Thomas J. Ostrand, Elaine J. Weyuker:
Does measuring code change improve fault prediction? 2 - Vu Nguyen
, LiGuo Huang
An analysis of trends in productivity and cost drivers over years. 3 - Wen Zhang, Ye Yang, Qing Wang:
Handling missing data in software effort prediction with naive Bayes and EM algorithm. 4 - Andreas Zeller
Failure is a four-letter word: a parody in empirical research. 5 - Mohammad Azzeh
Software effort estimation based on optimized model tree. 6 - Sandeep Krishnan, Chris Strasburg, Robyn R. Lutz
Are change metrics good predictors for an evolving software product line? 7 - Tomi Prifti, Sean Banerjee, Bojan Cukic
Detecting bug duplicate reports through local references. 8 - Leandro L. Minku
A principled evaluation of ensembles of learning machines for software effort estimation. 9 - Massimiliano Di Penta
Nothing else matters: what predictive model should I use? 10 - Lionel Marks, Ying Zou, Ahmed E. Hassan:
Studying the fix-time for bugs in large open source projects. 11 - Ibrahim Aljarah
Selecting discriminating terms for bug assignment: a formal analysis. 12 - Anh Nguyen Duc, Daniela S. Cruzes, Reidar Conradi, Claudia P. Ayala:
Empirical validation of human factors in predicting issue lead time in open source projects. 13 - Ye Yang, Lang Xie, Zhimin He, Qi Li, Vu Nguyen
Local bias and its impacts on the performance of parametric estimation models. 14 - Huihua Lu, Bojan Cukic
An iterative semi-supervised approach to software fault prediction. 15 - Elham Paikari, Bo Sun, Günther Ruhe, Emadoddin Livani:
Customization support for CBR-based defect prediction. 16 - Masateru Tsunoda, Takeshi Kakimoto, Akito Monden
An empirical evaluation of outlier deletion methods for analogy-based cost estimation. 17
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