Collecting and analyzing software process data can help to control and predict the performance of software development activities, helping software developers to achieve both business and technical objectives. Experience has shown that quantifying the software process operation can improve insight, e.g. allowing assessing the impact of process change on the software products.
On the other hand, the widespread adoption of agile processes and the increasing structural diversity of software development organizations around the world (e.g., in average size and available skills) as well as new concerns e.g. about privacy, are driving the need for non-intrusive, cost-effective methods capable to deliver long term success in collecting process data without further increasing the burden of process management. Process data mining techniques are also being investigated aimed at extracting valuable knowledge, capable to improve software products’ quality.
Several ongoing national and international research projects are dealing with these and related software data processing issues.
The proposed workshop is aimed at highlighting the cutting edge of process data collection and analysis research, fostering information exchange between researchers working on data analysis for agile software process improvement and practitioners interested in exploiting software data collection and analysis techniques as a basis for making process decisions and predicting process performance.
The workshop topics of interest include (but are not limited to):

• Techniques for monitoring agile processes’ performance and stability

• Non-intrusive, privacy-aware process data collection, analysis and mining

• Return-On-Investment (ROI) models for process data warehousing and
  analysis

• Network-based environments and protocols for measuring software process
  behaviour

• Using process data to assess capability and improvement potential

• Controlled obfuscation of process data

• Statistical process control

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