Motivation and Goals

Systems we build are ultimately evaluated based on the value they deliver to their users and stakeholders. To increase the value, systems are subject to fast-paced evolution of the systems, due to unpredictable markets, complex and changing customer requirements, pressures of shorter time-to-market, and rapidly advancing information technologies.

To address this situation, agile practices advocate flexibility, efficiency and speed. Continuous software engineering refers to the organisational capability to develop, release and learn from software in rapid parallel cycles, typically hours, days or very small numbers of weeks. This includes to determine new functionality to build, evolving and refactoring the architecture, developing the functionality, validating it, and releasing it to customers. One needs to relate the changes performed on the system with their effect on the metrics of interest, keep the changes with positive effects, and discard the rest. In case of complex systems involving humans in the loop, such a relation is difficult to infer a priori; a solution is then to observe and experiment with systems in production environments, e.g. with continuous experimentation.

Reaching this goal requires crosscutting research which spans from the area of process and organisational aspects in software engineering to the individual phases of the software engineering lifecycle and finally to live experimentation to evaluate different system alternatives by users’ feedback. With the proliferation of data analysis and machine learning techniques and flexible approaches to rapid deployment, experimentation can be used in different domains (e.g. embedded systems); it can also be automated and used for runtime adaptation. These new concepts call for synergy between software engineers and data scientists.

RCoSE/DDrEE'19 brings together academics and practitioners with the overall goals:


to identify the problems in adoption and use of continuous software engineering and data-driven decisions

New ideas

to discuss new ideas that apply successfull and established concepts to other domains and use cases


to build a community between software engineers and data scientists working on a common research agenda


Workshop structure and planned outcomes

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 identified challenges and proposed solutions. Breakout groups will discuss the general topics of the workshop’s contributions.

As a follow-up of the workshop 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.

Submission and Important Dates

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.
Please submit your paper using the following link:

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 2019 Companion volume by IEEE.

Important Dates