Recommender systems in software engineering (RSSE) have gained momentum in recent years. Such systems assist developers in navigating large information spaces and getting instant recommendations that might be helpful to solve their development tasks. Though a lot of improvements have been obtained so far, there is still the need to make RSSE more effective and efficient. Furthermore, while several attempts have been made to improve the recommendation accuracy, little attention has been paid to make such systems robust and resilient to malicious data. In fact, by manipulating training data available in open source software platforms, a hostile user may render recommender systems vulnerable to adversarial attacks, putting software clients at risk. The First International Workshop on Evaluation and Analysis of Recommender Systems in Software Engineering (WEARS 2021) brings in a forum for researchers and practitioners to share, discuss and explore the opportunities and challenges raised by the evaluation and in-depth investigation of RSSE. We solicit research work from the Software Engineering community as well as related fields such as Machine Learning and Recommender Systems.

The First International Workshop on Evaluation and Analysis of Recommender Systems in Software Engineering (WEARS 2021) brings in a forum for researchers and practitioners to share, discuss and explore the opportunities and challenges raised by the evaluation and in-depth investigation of RSSE. We solicit research work from the Software Engineering community as well as related fields such as Machine Learning and Recommender Systems.

The workshop is co-located with the 15th International Conference on Evaluation and Assessment in Software Engineering (EASE 2021). Please have a look at the following link for more detail: https://www.ntnu.edu/ease2021.


Topics of interest

Topics of interest for the workshop include, but are not limited to:
– Development and evaluation of RSSE.
– Case studies of real-world implementations; Replication of empirical studies on RSSE.
– User studies and benchmark for RSSE.
– Machine learning and deep learning for software engineering.
– Use of artificial intelligence techniques for data processing and data augmentation.
– Techniques and tools to curate data for evaluation.
– RSSE for mining open source software repositories.
– Dealing with bias during the evaluation of RSSE.
– Dealing with anonymized and partial data when evaluating RSSE.
– Reusing existing recommender systems that have not been developed for SE tasks.
– Quantitative versus qualitative analysis of RSSE.
– Adversarial Machine Learning: Threats, attacks and countermeasures.

Submissions

Submissions must be written in English and adhere to the ACM Proceedings Format. We solicit two types of contributions as follows:

– Research papers (max. 10 pages): Work presenting novel ideas, practical solutions to RSSE.
– Vision and position papers (max. 6 pages): Work in progress, visionary papers, and industrial experience.

WEARS 2021 imposes single-blind review, and all papers will be submitted and handled with EasyChair and peer-reviewed by three PC members. Accepted papers will be published in the Satellite Event Proceedings of the main conference (EASE 2021) in the ACM Digital Library. At least one author of each accepted paper must register for the conference and present their work in the workshop.


Program committee (listed in alphabetical order):

– Vito Walter Anelli (Politecnico di Bari, Italy)
– Gabriele Bavota (Università della Svizzera italiana, Switzerland)
– Andrea Capiluppi (University of Groningen, The Netherlands)
– Pablo Chamoso (Universidad de Salamanca, Spain)
– Thomas Degueule (Laboratoire Bordelais de Recherche en Informatique, France)
– Tommaso Di Noia (Politecnico di Bari, Italy)
– Davide Di Ruscio (Università degli Studi dell’Aquila, Italy)
– Antonio Ferrara (Politecnico di Bari, Italy)
– Reid Holmes (University of British Columbia, Canada)
– Ludovico Iovino (Gran Sasso Science Institute, Italy)
– Raula Gaikovina Kula (Nara Institute of Science and Technology, Japan)
– Michele Lanza (Università della Svizzera italiana, Switzerland)
– Collin McMillan (University of Notre Dame, USA)
– Meiyappan Nagappan (University of Waterloo, Canada)
– Alfonso Pierantonio (Università degli Studi dell’Aquila, Italy)
– Martin Robillard (McGill University, Canada)
– Alexander Serebrenik (Eindhoven University of Technology, The Netherlands)
– Damian A. Tamburri (Eindhoven University of Technology, The Netherlands)
– Robert J. Walker (University of Calgary, Canada)
– Thomas Zimmermann (Microsoft Research, USA)


Important dates
– Paper submission: March 26th, 2021.
– Notification: April 19th, 2021.
– Camera-ready: April 30th, 2021.
– Workshop: June 23rd, 2021.