IBM hosted its annual Centre for Advanced Studies Conference (CASCON) at Hilton Suites in Markham, Ontario. In this conference, academia and industry partners demonstrate their latest development of advanced software technologies in a technology showcase as well as series of paper presentations and workshops. LS3 presented its latest development in the Moviesion project in CASCON technology showcase. It also presented some of its research in two paper presentation sessions.
Our paper “Mining Common Morphological Fragments from Process Event Logs” by Asef Pourmasoumi,Mohsen Kahani, Ebrahim Bagheri, and Mohsen Asadi won the Best Student Paper Award.
More information about IBM CASCON can be found here: https://www.ibm.com/ibm/cas/cascon/
LS3 hosted the first of its research-day colloquium series on Wednesday May 7th 2014. LS3 Researchers shared the highlights of their research with their colleagues at the laboratory for systems, software and semantics by preparing a presentation about their research.
The presenter focused on Research Domain, Motivation for Work, Contributions, and Outline of their Solutions. The members shared their thoughts with presenters after each presentation.
The presentation titles and slides can be found below:
“Engineering Self-adaptive Service Mashups” (Mahdi Bashari)
“Metrics-Driven Approach for LOD Quality Assessment” (Behshid Behkamal)
“Semantic Search” (Andisheh Keikha)
“Indexing and retrieval for semantic search” (Fatemeh Lashkari)
“Non-functional Properties in Software Product Lines: A Framework for Developing Quality-centric Software Products” (Mehdi Noorian)
“DERIVE – Assigning properties to objects within natural language text” (John Cuzzola)
Presented at 17th International Software Product Conference (SPLC 2013).
Self-adaptive systems are a class of software applications, which are able to dynamically transform their internal structure and hence their behavior in response to internal or external stimuli. The transformation may provide the basis for new functionalities or improve or maintain non-functional properties in order to match the application better to its operational requirements and standards. Software Product Line Engineering has rich methods and techniques in variability modeling and management which is one of the main issues in developing self-adaptive systems. Dynamic software product lines (DSPL) have been proposed to exploit the knowledge acquired in SPLE to develop self-adaptive software systems.
In this tutorial, we portray the problem of developing self-adaptive systems. Then we investigate how the idea of dynamic software product line could help to deal with the challenges that we face in developing efficient self-adaptive software. We also offer insight into the different approaches that use dynamic software product line engineering for developing self-adaptive systems focusing on practical approaches by showing how the approaches are applied to real case studies and also methods for evaluating these approaches. This tutorial also discuss how DSPL could be used some relevant areas to self-adaptive systems and challenges which still exist in the area.
Mahdi Bashari, Ebrahim Bagheri
Empirical Software Engineering:
An International Journal
Special issue on
Empirical Evidence on Software Product Line Engineering
Software product line engineering (SPLE) is a paradigm that advocates the reusability of software assets and the rapid development of new applications for a target domain. These objectives are achieved by capturing the commonalities and variabilities between the applications of a target domain and through the development of comprehensive and variability-rich models. Software product line engineering practices offer desirable characteristics such as rapid product development, reduced time-to-market, quality improvement, and more affordable development costs as a result of a systematic management of the variabilities in a set of products (the product line) leading to methodical reuse of software assets. In light of these achieved benefits, the software product line community has received very significant attention both in research and in industry. However, a recent systematic literature review  showed that only a limited portion of the proposed work actually offers serious or effective empirical evidence regarding the appropriateness, usability and/or effectiveness of their work. This special issue seeks submissions in areas pertaining to empirical evidence of success or failure of software product line or emerging software product line approaches. Contributions in the following forms are especially encouraged:
- Industrial experience reports, case studies and action-research in SPL
- Applied SPL approaches with a strong empirical component
- New research methods for evaluating SPL research
- Measurement, comparison and development of empirical methods in SPL
- Studies on SPL technology transfer to industry
- Process improvement in SPLs supported by empirical evidences
- Longitudinal studies of SPL evolution over time
- Cost-benefit analysis for SPLs in practice
- Submission Deadline: 7 Feb 2014
- First Notification: 10-April-2014
- Major Revisions Due: 10-May-2014
- Second Notification: 1-July-2014
- Minor Revision Due: 20-August-2014
- Final Recommendations: 10-November-2014
PAPER SUBMISSION DETAILS – Authors are invited to submit original contributions to http://www.editorialmanager.com/emse. Authors should state in their cover letter to the EiC that “This manuscript is submitted for the special issue on Empirical Evidence in Software Product Line Engineering “. Submission instructions can be found under “Information for Authors” at: http://www.springer.com/computer/swe/journal/10664
GUEST EDITORS (alphabetical order)
- Ebrahim Bagheri, Ryerson University, Canada
- David Benavides, University of Seville,Spain
- Per Runeson, Lund University, Sweden
- Klaus Schmid, University of Hildesheim, Germany
 Alvin Ahnassay, Ebrahim Bagheri, Dragan Gasevic, Empirical Evaluation in Software Product Line Engineering, Technical Report, Laboratory for Systems, Software and Semantics, Ryerson University, TR-LS3-130084R4T, 2013. Link