DAPSE 2013 - International Workshop on Data Analysis Patterns in Software Engineering (DAPSE’13)

Data scientists in software engineering seek insight in data collected from software projects to improve software development. The demand for data scientists with domain knowledge in software development is growing rapidly and there is already a shortage of such data scientists.
Data science is a skilled art with a steep learning curve. To shorten that learning curve, this workshop will collect best practices in form of data analysis patterns, that is, analyses of data that leads to meaningful conclusions and can be reused for comparable data. In the workshop we will compile a catalog of such patterns that will help both experienced and emerging data scientists to better communicate about data analysis. The workshop is intended for anyone interested in how to analyze data correctly and efficiently in a community accepted way.
SUBMISSIONS
We solicit papers (2-3 pages) describing one or more data analysis pattern. Authors should use the form that is most suited to describe the pattern. Where possible, we encourage authors to describe pattern as follows
Pattern name: a handle for the pattern
Problem: when to apply the pattern
Solution: how to apply the pattern
Consequence: results and trade-offs of applying the pattern, common mistakes in applying the pattern to be avoided, etc.
Examples: brief summary and/or cite example applications of the pattern in literature; if possible, R snippets or Weka code to apply the pattern, etc.