Euromicro Conference on
Software Engineering and Advanced Applications

August 28 – 30, 2019
Kallithea, Chalkidiki | Greece

SEAA 2019

SEAA 2019 Call For Papers Committees Submissions Registration

Paper Submission Deadline:

15 March 2019

1 April 2019

Notification of Acceptance:

6 May 2019

Camera-Ready Papers:

14 June 2019

Call for Papers

Special Session @ 45th EUROMICRO SEAA Conference in Thessaloniki / Chalkidiki, Greece

Software and Big Data Analytics (SBDA)


August 28-30, 2019

http://dsd-seaa2019.csd.auth.gr

Important Dates:

  • Abstract submission to tracks and sessions: March 1st, 2019
  • Paper submission deadline: March 15th, 2019 April 1st, 2019
  • Notification of accepted papers: May 6th, 2019
  • Camera-ready paper due: June 3rd, 2019

In recent years, software engineering has taken advantage of the ability to collect, process and visualize large quantities of data originating from software development tools and the application of the software products, systems or services themselves. To be able to take the next step in excelling in software development, we need to be more efficient in utilizing the latest research in data mining, data analytics (such as deep learning), and visualization of large quantities of data. This relates to big data analytics, which is about extracting valuable information from data to use it in intelligent ways such as to revolutionize decision-making in business, engineering, science and society. Big data analytics copes with a vast amount of information from heterogeneous sources, with various characteristics, levels of trust, and provenance. The aim of big data analytics is to cost-effectively turn high-volume, high-velocity and high-variety data into new knowledge and real-time situation awareness. This special session will look at big data analytics from two perspectives. How big data analytics may be used for software engineering (a.k.a. “software analytics”), and how to engineer data-intensive software systems that exploit big data analytics.

Increasingly, software systems and applications emerge that exploit big data for intelligent processing and reasoning. These applications use advanced machine learning techniques that detect patterns in big data and reason on them with events, context and greater situation awareness, facilitating operational decision-support and self-adaptation. These emerging data-intensive software systems are creating a new class of software systems altogether and require special software engineering approaches. These new systems are shifting existing and established software engineering principles, methods and tools towards new opportunities but also challenges in software development and operation. For example, traditional software testing and verification may reach its limits due to the size of data and the changes of data in real-time.

Mission

This special session aims to explore the impact of software and big data analytics on software engineering and vice versa, serving as a forum for the exchange of ideas, solutions and experiences among researchers and practitioners from the communities of software visualization, mining software repositories, software analytics and big data systems in software engineering.

Topics

Topics of interest include, but are not restricted to:

  • Methods, tools, and applications of software analytics in software engineering
  • Visualization to support program comprehension, software testing, and debugging
  • Specification, design, development, quality assurance, deployment, and operation of big data and data-intensive software systems
  • Human and social aspects of engineering big data and data-intensive software systems
  • Data science in software engineering
  • Big data analytics for self-adaptive software systems
  • Software and data life-cycle management
  • Integrated software and data engineering
  • Data-driven software development
  • Privacy and security in big data software systems
  • New applications for deep learning, advanced analytics and reasoning
  • Software visualization and visual analytics
  • Empirical studies on software visualization, mining software repositories, software analytics and big data systems in software engineering

Session Chairs

Michael Felderer University of Innsbruck, Austria

Andreas Metzger University of Duisburg-Essen, Germany

Program Committee

Sebastian Baltes, University of Trier

Olga Baysal, Carleton University

Ayse Bener, Ryerson University

Alexandre Bergel, University of Chile

Markus Borg, RISE SICS AB

Steffen Frey, University of Stuttgart

Davide Fucci, HITeC, University of Hamburg

Regina Hebig, Chalmers | Gothenburg University

Stephen MacDonell, University of Otago

Nazim Madhavji, University of Western Ontario

Zoltan Mann, University of Duisburg-Essen

Leonel Merino, University of Stuttgart

Maleknaz Nayebi, Ecole Polytechnique de Montreal

Ezequiel Scott, University of Tartu