Current software engineering practice has shown large interest and demonstrated quick adoption of experimentation ideas and practices, and, more generally of data science platforms and techniques that will allow to generate value from users’ data by catering for their needs. Additionally, the large amount of data collected at runtime, together with the increasing need to understand the impact changes on software systems have on end users call for novel software engineering approaches that focus on experiment-driven feature development, data collection pipelines and architectures, runtime frameworks and data management for data-driven decisions. This is also manifested in the recent DataOps movement, which strives to streamline the development and operation of data analytics pipelines using agile practices.

To realize these approaches and develop innovative solutions with respect to automation and tooling for runtime optimization, decision making and data management, there is a need for deep synergies between software engineers, data scientists and researchers.

In align with the overall goals of DDrEE on identifying problems in adoption and use of data-driven decisions, discussing new ideas and innovative use cases, and building a community, DDrEE 2020 will focus is on open topics identified in the SEN report of the previous edition of the workshop:

The full-day workshop will open with a keynote talk. The presenter of each accepted paper will then have approx. 20 mins for presentation and Q&A. We will try to stimulate discussions on the important challenges of data-driven decisions and experimentation, creating an interactive environment and involving participants with and without accepted paper.

In the afternoon, we will create topic-based groups and organize two break-out group sessions. Following the experience from the past edition and to better consolidate the results from it, we plan to publish a report of the workshop’s outcomes in ACM SIGSOFT Software Engineering Notes (see last year's report)

The workshop invites three types of submissions:

• Full research papers and experience reports, presenting original and evaluated research. Maximum length: 7 pages incl. references.
• Position papers, presenting promising initial results from work-in-progress approaches or research challenges, experiences or roadmaps related to the theme of the workshop. Maximum length: 4 pages incl. references.
• Industrial abstracts describe challenges or success stories from practice. Maximum length: 2 pages incl. references.

Submitted papers must conform to the ACM Formatting Instruction available at https://www.acm.org/publications/proceedings-template

Please submit your paper using the following link: https://easychair.org/conferences/?conf=ddree2020

Submitted papers will be reviewed by at least 3 members of the PC and judged based on their relevance to the workshop scope, quality and originality of their results. Accepted papers will be published at the ICSE 2020 Companion volume by ACM.