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ICSOFT 2018 - 13th International Conference on Software Technologies (ins)...

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ICSOFT 2018 - 13th International Conference on Software Technologies




ICSOFT 2018 will be held in conjunction with DATA 2018, ICETE 2018 and SE-CLOUD 2018.
Registration to ICSOFT allows free access to the DATA, ICETE and SE-CLOUD conferences (as a non-speaker).




UPCOMING DEADLINES
Regular Paper Submission: March 13, 2018
Regular Paper Authors Notification: May 14, 2018
Regular Paper Camera Ready and Registration: May 28, 2018
The purpose of the ICSOFT 2018, the 13th International Conference on Software Technologies, is to bring together researchers, engineers and practitioners interested on software technologies. The conference areas are "Software Engineering and Systems Development", "Software Systems and Applications" and "Foundational and Trigger Technologies".




CONFERENCE AREAS

1 . Software Engineering and Systems Development

2 . Software Systems and Applications

3 . Foundational and Trigger Technologies



CONFERENCE CHAIR
Leszek Maciaszek, Wroclaw University of Economics, Poland and Macquarie University, Sydney, Australia



PROGRAM CHAIR
Marten van Sinderen, University of Twente, Netherlands



KEYNOTE SPEAKER
João Gama, LIAAD - INESC TEC, University of Porto, Portugal




SCOPE


The purpose of the ICSOFT 2018, the 13th International Conference on Software Technologies, is to bring together researchers, engineers and practitioners interested on software technologies. The conference areas are "Software Engineering and Systems Development", "Software Systems and Applications" and "Foundational and Trigger Technologies".

Papers describing original work are invited in any of the areas listed below. Accepted papers, presented at the conference by one of the authors, will be published in the Proceedings of ICSOFT with an ISBN. Acceptance will be based on quality, relevance and originality. Both full research reports and work-in-progress reports are welcome. There will be both oral and poster sessions.

Special sessions, dedicated to case-studies and commercial presentations, as well as tutorials dedicated to technical/scientific topics are also envisaged: companies interested in presenting their products/methodologies or researchers interested in holding a tutorial, workshop or special session are invited to contact the conference secretariat or visit the conference website.




CONFERENCE AREAS

Each of these topic areas is expanded below but the sub-topics list is not exhaustive. Papers may address one or more of the listed sub-topics, although authors should not feel limited by them. Unlisted but related sub-topics are also acceptable, provided they fit in one of the following main topic areas:

1. SOFTWARE ENGINEERING AND SYSTEMS DEVELOPMENT
2. SOFTWARE SYSTEMS AND APPLICATIONS
3. FOUNDATIONAL AND TRIGGER TECHNOLOGIES




AREA 1: SOFTWARE ENGINEERING AND SYSTEMS DEVELOPMENT

Mainstream topics in software engineering with wide adoption in practice, but where new methods, tools and techniques can bring further improvements in systems development.


  • Agile Development
  • Architectural Design, Refactoring and Patterns
  • Automated Software Engineering
  • Change and Configuration Management
  • Data-driven Software Engineering
  • Empirical Software Engineering
  • Formal Methods
  • Mobile and Cross Platform Development
  • Model-driven Software Engineering
  • Open Source Development
  • People Management
  • Process Modeling
  • Programming Frameworks and Platforms
  • Project Management
  • Quality Management
  • Requirements Engineering
  • Software Engineering Tools
  • Software Development Lifecycle
  • Software and Systems Modeling
  • Risk Management
  • Software Project Planning and Tracking
  • Testing and Testability
  • User-centered Design




AREA 2: SOFTWARE SYSTEMS AND APPLICATIONS

Topics with emphasis on results and products of software development in specific application areas.


  • Agent and Multi-agent Systems
  • Ambient Intelligence and Digital Ecosystems
  • Application Software
  • Artificial Intelligence Applications
  • Complex Systems
  • Cyber-physical Systems
  • Decision Support Systems
  • Embedded Systems
  • Enterprise Systems and Applications
  • Government Systems and Applications
  • Mobile Apps
  • Real-time Systems
  • Robotics
  • Social Systems and Applications
  • Software Product Line
  • System Software
  • Web Systems and Applications
  • 3D Printing




AREA 3: FOUNDATIONAL AND TRIGGER TECHNOLOGIES

Foundational technologies for software development as well as trigger technologies for software systems. Trigger technologies are technologies which are promising but have not yet been proven in practice (i.e., they belong to the early hype cycle phase).


  • Big Data and Data Science
  • Cloud Computing
  • Cybersecurity Technologies
  • Digital Divide Technology Factors
  • High performance computing
  • Image Processing and Computer Vision
  • Information Age and Digital Revolution
  • Internet of Things
  • Mobile Technologies
  • Natural Language Technologies
  • Network and Data Communications
  • Software as a Service
  • Virtual and Augmented Reality
  • Web Technologies




Keynote Lecture


Data Mining in the XXI Century

João Gama
LIAAD - INESC TEC, University of Porto
Portugal

Brief Bio

João Gama is an Associate Professor at the University of Porto, Portugal. He is also a senior researcher and member of the board of directors of the Laboratory of Artificial Intelligence and Decision Support (LIAAD), a group belonging to INESC Porto. João Gama serves as the member of the Editorial Board of Machine Learning Journal, Data Mining and Knowledge Discovery, Intelligent Data Analysis and New Generation Computing. He served as Co-chair of ECML 2005, DS09, ADMA09 and a series of Workshops on KDDS and Knowledge Discovery from Sensor Data with ACM SIGKDD. He was also the chair for the conference of Intelligent Data Analysis 2011. His main research interest is in knowledge discovery from data streams and evolving data. He is the author of more than 200 papers reviewed by peers and author of a recent book on Knowledge Discovery from Data Streams. He has extensive publications in the area of data stream learning.


Abstract
Nowadays, there are applications in which the data are modelled best not as persistent tables, but rather as transient data streams. In this keynote, we discuss the limitations of current machine learning and data mining algorithms. We discuss the fundamental issues in learning in dynamic environments like learning decision models that evolve over time, learning and forgetting, concept drift and change detection. Data streams are characterized by huge amounts of data that introduce new constraints in the design of learning algorithms: limited computational resources in terms of memory, processing time and CPU power. In this talk, we present some illustrative algorithms designed to taking these constrains into account. We identify the main issues and current challenges that emerge in learning from data streams, and present open research lines for further developments.



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