This award is presented at each ESEM, ACM/IEEE International Symposium on Empirical Software Engineering and Measurement.
RECIPIENTS AND TITLE OF THE BEST PAPER AWARD
|2012||Best Full Paper:
Experimental Assessment of Software Metrics using Automated Refactoring; Mel Ë CinnÚide, Laurence Tratt, Mark Harman, Steven Counsell and Iman Hemati Moghadam.
Best Short Paper:
Handling Categorical Variables in Effort Estimation; Masateru Tsunoda, Sousuke Amasaki and Akito Monden
The following technical papers were selected as the "top 5" papers at the conference, on the strength of the reviews received from the PC. The winners were invited to send an extended version of their conference paper for consideration for a special issue of IST Journal. In no particular order, our selected papers are:
IEEE Software sponsored an award for the best paper in the industry experience track. The criteria were that the selected paper should be well-written and of high-quality, but also be able to influence the state of the practice. The winner is expected to be an example of the kind of practical, experiential, yet rigorous papers that are of interest to IEEE Software readers. The winning paper was selected by a review committee that consisted of IEEE Software Editor in Chief Forrest Shull, the Industry Experience track chair Brian Robinson, and additional members drawn from both the magazine's editorial board and the experience track's program committee: Mark Grechanik, Maurizio Morisio, and Helen Sharp. The winning paper was:
|2010||Best Full Papers:
Best Short Paper:
Stephen MacDonell and Martin Shepperd. Data Accumulation and Software Effort Prediction
|2009||Juristo, N. and Vegas, S.: Using Differences among Replications of Software Engineering Experiments to Gain Knowledge|
|2008||Cataldo, M, Herbsleb, J., Carley, K.: Socio-Technical Congruence: A Framework for Assessing the Impact of Technical and Work Dependencies on Software Development Productivity.|
|2007||Layman, L.; Williams, L.; Amant, R.S.: Toward Reducing Fault Fix Time: Understanding Developer Behavior for the Design of Automated Fault Detection Tools
Kamei, Y.; Monden, A.; Matsumoto S.; Kakimoto, T. and Matsumoto, K.:.The Effects of Over and Under Sampling on Fault-prone Module Detection