ECOOP is Europe’s longest-standing annual Programming Languages (PL) conference, bringing together researchers, practitioners, and students to share their ideas and experiences in all topics related to programming languages, software development, object-oriented technologies, systems and applications. ECOOP welcomes high quality research papers relating to these fields in a broad sense.
This 34th edition of ECOOP will take place in July 2020 in Berlin, Germany. ECOOP is committed to affordable open-access publishing. Recent year’s publications have been published by Dagstuhl’s LIPIcs series under a Creative Commons CC BY license where the authors retain their copyright. ECOOP articles have been published without open-access publishing fee and can be accessed via a DOI. LIPIcs is indexed in DBLP, Google Scholar, Scopus and others.
ECOOP is a conference about programming. Originally its primary focus was on object orientation, but now it looks at a much broader range of programming topics. Areas of interest include, at least, the design, implementation, optimization, analysis, and theory of programs, programming languages, and programming environments. It solicits both innovative and creative solutions to real problems as well as evaluations of existing solutions—evaluations that provide new insights. It also encourages the submission of reproduction studies.
ECOOP 2020 solicits high-quality submissions describing original, unpublished results.
The program committee will evaluate the technical contribution of each submission as well as its general relevance and accessibility to the ECOOP audience according the following criteria:
Originality. Papers must present new ideas and place them appropriately within the context established by previous research in the field.
Significance. The results in the paper must have the potential to add significantly to the state of the art or practice.
Evidence. The paper must present evidence supporting its claims. Examples of evidence include implemented systems, experimental results, statistical analyses, case studies, formalizations, and proofs.
Clarity. The paper must present its contributions and results clearly.
A Reproduction Study is an empirical evaluation. A reproduction study independently reconstructs an already published experiment but in a different context (for example, using a different virtual machine or platform, or in a different class of applications) in order to validate or refute important results of earlier work. A good reproduction study includes thorough empirical evaluation as well as a detailed comparison with the previous results, providing reasons for possible disagreements.