Mon 21 JunDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
13:30 - 15:00 | Human AspectsEASE 2021 / Vision and Emerging Results Track at Zoom Chair(s): Anh Nguyen-Duc University of South Eastern Norway | ||
14:37 22mVision and Emerging Results | Storytelling in Human-Centric Software Engineering Research Vision and Emerging Results Track Austen Rainer Queen's University Belfast Pre-print | ||
15:15 - 16:15 | Software Quality IIEASE 2021 / Vision and Emerging Results Track at Zoom Chair(s): Paolo Arcaini National Institute of Informatics | ||
15:55 20mVision and Emerging Results | SLGPT: Using Transfer Learning to Directly Generate Simulink Model Files and Find Bugs in the Simulink Toolchain Vision and Emerging Results Track Sohil Lal Shrestha The University of Texas at Arlington, Christoph Csallner University of Texas at Arlington DOI Pre-print Media Attached | ||
Tue 22 JunDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
09:00 - 10:30 | Human and MethodologicalVision and Emerging Results Track / EASE 2021 at Zoom Chair(s): Nelly Condori-Fernández University of A Coruña/ Vrije Universiteit Amsterdam | ||
09:00 22mVision and Emerging Results | Towards Offensive Language Detection and Reduction in Four Software Engineering Communities Vision and Emerging Results Track Jithin Cheriyan University of Otago, Bastin Tony Roy Savarimuthu University of Otago, Dunedin, New Zealand, Stephen Cranefield University of Otago Pre-print | ||
10:07 23mVision and Emerging Results | Adversarial Machine Learning: On the Resilience of Third-party Library Recommender Systems Vision and Emerging Results Track Phuong T. Nguyen University of L’Aquila, Davide Di Ruscio University of L'Aquila, Juri Di Rocco University of L'Aquila, Claudio Di Sipio University of L'Aquila, Massimiliano Di Penta University of Sannio, Italy Pre-print | ||
13:00 - 14:30 | AgileEASE 2021 / Vision and Emerging Results Track at Zoom Chair(s): Michael Felderer University of Innsbruck | ||
14:07 22mVision and Emerging Results | Empirical Findings on BDD Story Parsing to Support Consistency Assurance between Requirements and Artifacts Vision and Emerging Results Track Thiago Rocha Silva , Brian Fitzgerald Lero - The Irish Software Research Centre and University of Limerick Link to publication DOI Pre-print | ||
Wed 23 JunDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
10:30 - 12:00 | Software MaintenanceVision and Emerging Results Track / EASE 2021 at Zoom Chair(s): Peng Liang Wuhan University | ||
11:37 22mVision and Emerging Results | debtHunter: A Machine Learning-based Approach for Detecting Self-Admitted Technical Debt Vision and Emerging Results Track Irene Sala University of Milano - Bicocca, Antonela Tommasel ISISTAN Research Institute, CONICET-UNCPBA, Francesca Arcelli Fontana University of Milano-Bicocca Pre-print | ||
13:00 - 14:30 | Software Quality EASE 2021 / Vision and Emerging Results Track at Zoom Chair(s): Irit Hadar University of Haifa | ||
14:07 22mVision and Emerging Results | Open Data-driven Usability Improvements of Static Code Analysis and its Challenges Vision and Emerging Results Track Emma Söderberg Lund University, Luke Church University of Cambridge | Lund University | Lark Systems, Martin Höst Lund University Pre-print | ||
Accepted Papers
| Title | |
|---|---|
| Adversarial Machine Learning: On the Resilience of Third-party Library Recommender Systems Vision and Emerging Results Track Pre-print | |
| debtHunter: A Machine Learning-based Approach for Detecting Self-Admitted Technical Debt Vision and Emerging Results Track Pre-print | |
| Empirical Findings on BDD Story Parsing to Support Consistency Assurance between Requirements and Artifacts Vision and Emerging Results Track Link to publication DOI Pre-print | |
| Open Data-driven Usability Improvements of Static Code Analysis and its Challenges Vision and Emerging Results Track Pre-print | |
| SLGPT: Using Transfer Learning to Directly Generate Simulink Model Files and Find Bugs in the Simulink Toolchain Vision and Emerging Results Track DOI Pre-print Media Attached | |
| Storytelling in Human-Centric Software Engineering Research Vision and Emerging Results Track Pre-print | |
| Towards Offensive Language Detection and Reduction in Four Software Engineering Communities Vision and Emerging Results Track Pre-print |
Call for papers
The Vision Papers should present long term challenges and opportunities rather than incremental improvements or evaluations of current solutions or practices. Typically, these papers include creative ways to extend the applicability of techniques in empirical software engineering and/or challenge the existing explicit or implicit assumptions or paradigms in the field. Bold calls to action for potential novel directions supported by a well-motivated scientific intuition or argument, as well as well-grounded well grounded predictions of how empirical software engineering research and practice will look in the far future are welcome.
The Emerging Results Papers should describe current work in progress on research and practice and communicate preliminary, initial research results for which the complete evaluation is not yet carried out. This type of papers could also include ideas on how to execute the research in the future, the longer-term objectives, planned work and expected results. Startling emerging results that disregard established results or beliefs, proposals on fundamentally new research directions are welcome. This track particularly invites work (e.g., practices, methodologies, technologies, tools, and software-based services) looking into the emerging areas of software engineering, for example (but not limited to):
- Emerging ideas for software engineering infrastructures (Cloud Computing, DevOps, Healthcare, Smart Cities, and IoT)
- Cross- and multi-disciplinary methods and studies
- New applications and advances in design science, case studies, action-research, and field studies, including multilevel and/or mixed methods research designs
- Simulation-based studies in software engineering as an empirical method
- New models of technology transfer to the industry
- Using AI as a research method in software engineering
- Cohort studies for large-scale research initiatives
- Software engineering for data science advances
- Incorporating virtual and augmented reality into software engineering research
- Empirical assessments of sustainability in software engineering
We are particularly interested in how the existing empirical research methods can be tailored for evaluating software-based solutions developed with emerging technological infrastructures. The primary purpose of the Emerging Results Papers is to communicate new ideas to get early feedback from the empirical software engineering community.
The vision, emerging results and artefact papers will not exceed six pages in camera-ready version.
Important Dates for the Vision and Emerging Results Track:
- Papers submission: 12 March (Hard deadline)
- Notification: 19 April
- Camera-ready: 30 April - extended to May 3, 2021
Submission Details
Submitted papers must be written in English, contain original, unpublished work, and conform to the ACM Proceedings Format (https://www.acm.org/publications/taps/word-template-workflow ). (Note: In the new ACM template https://www.acm.org/publications/taps/word-template-workflow, the submission template provided by the ACM is now one-column. The camera-ready version is still supposed to be two-column. The difference may make it difficult for authors to estimate their page numbers in the camera-ready version. For Word Template users, they shall refer to the Table at the bottom of the link https://www.acm.org/publications/taps/word-template-workflow to estimate the paper's pages in the camera-ready version. For Latex template users, the authors can use \documentclass[sigconf,authordraft]{acmart} to write the paper and to control the number of pages in the camera-ready version, and then change it to \documentclass[manuscript]{acmart} for submitting the paper for review.)
The conference enforces the ACM Policy and Procedures on Plagiarism (https://www.acm.org/publications/policies/plagiarism-overview).
To reduce bias in reviews, EASE conference will use a double-blind review process. As a result, the manuscripts should be submitted for review anonymously (i.e., without listing the author’s names on the paper) and references to own work should be made in the third person.
Please submit manuscripts via EasyChair, and in pdf format via the following url: https://easychair.org/conferences/?conf=ease2021. The conference proceedings will be published by ACM. The ACM offers options for Open Access (https://www.acm.org/openaccess).
At least one author of each accepted paper must register by the camera-ready deadline.
Silvia Abrahão
Universitat Politècnica de València
Spain
Pekka Aho
Open University of the Netherlands
Netherlands
Francesca Arcelli Fontana
University of Milano-Bicocca
Italy
Dan Berry
University of Waterloo
Canada
Markus Borg
RISE Research Institutes of Sweden
Sweden
Rafael Capilla
Universidad Rey Juan Carlos
Spain
Jinghui Cheng
Polytechnique Montreal
Canada
Nelly Condori-Fernández
University of A Coruña/ Vrije Universiteit Amsterdam
Spain
Tihana Galinac Grbac
University of Pula
Croatia
Stijn Hoppenbrouwers
HAN University of Applied Sciences
Netherlands
Miroslaw Ochodek
Poznan University of Technology
Poland
Shola Oyedeji
Lappeenranta University of Technology
Finland
Bestoun S. Ahmed
Karlstad University Sweden
Sweden
Norbert Seyff
FHNW & University of Zurich
Switzerland
Martin Shepperd
Brunel University London
United Kingdom
Sofia Sherman
Tel-Aviv Yoffo Academic College
Israel
Michael Unterkalmsteiner
Blekinge Institute of Technology
Sweden
Kristian Wiklund
Ericsson AB
Sweden
Dirk van der Linden
Northumbria University
United Kingdom
Mel Ó Cinnéide
University College Dublin & Lero, Ireland
Ireland