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Keynote Lectures

What a Tangled Effort Estimation Web We Weave! - How Can Knowledge Management Disentangle This Web?
Emilia Mendes, Blekinge Institute of Technology, Sweden

Social Structures in Software Engineering
J.C. (Hans) van Vliet, Vrije Universiteit, Netherlands

Democratization in Science and Technology through Cloud Computing
Ivona Brandić, Vienna UT, Austria

Model-Driven Development of Multi-View Modelling Tools: The MUVIEMOT Approach
Dimitris Karagiannis, University of Vienna, Austria

 

What a Tangled Effort Estimation Web We Weave! - How Can Knowledge Management Disentangle This Web?

Emilia Mendes
Blekinge Institute of Technology
Sweden
 

Brief Bio

Emilia Mendes is Professor in Software Engineering at the Blekinge Institute of Technology. She obtained her PhD in Computer Science from the University of Southampton (UK) in 1999, and then initiated her full time academic career in the Computer Science Department at the University of Auckland (NZ), where she worked for 12 years. After leaving NZ, she was Associate Professor at Zayed University (UAE) for a year. Her research is inter-disciplinary, encompassing different disciplines - Web & Software measurement &metrics, Empirical Software & Web Engineering and IT/Computer Science & Software/Web Engineering education. To date she has published over 180 refereed publications, which include two books (one edited (2005 - Web Engineering) and one authored (2007 - Cost Estimation Techniques for Web Projects)). She is on the editorial board of six International Journals in the fields of Web and Software Engineering, and has been a PC member of more than 130 different Conferences and workshops. Finally, she worked in the ICT industry for ten years as programmer, business analyst and project manager prior to moving to the UK in the end of 1995 to initiate her PhD studies.


Abstract

A cornerstone of Web project management is effort estimation, the process by which effort is forecasted and used as basis to predict costs and allocate resources effectively, so enabling Web projects to be delivered on time and within budget. Web effort estimation is a very complex domain where the relationship between factors is non-deterministic and has an inherently uncertain nature, and where corresponding decisions and predictions require reasoning with uncertainty.
Most studies in this field, however, have to date investigated ways to improve Web effort estimation by proposing and comparing techniques to build effort prediction models where such models are built solely from data on past software projects - data-driven models. The drawback with such approach is threefold: first, it ignores the explicit inclusion of uncertainty, which is inherent to the effort estimation domain, into such models; second, it ignores the explicit representation of causal relationships between factors; third, it relies solely on the variables being part of the dataset used for model building, under the assumption that those variables represent the fundamental factors within the context of software effort prediction.
Recently, as part of a New Zealand and later on Brazilian government-funded projects, we investigated the use of an expert-centred approach in combination with a technique that enables the explicit inclusion of uncertainty and causal relationships as means to improve Web effort estimation.
This talk will first provide an overview of the Web effort estimation process, followed by a brief summary of a recently conducted systematic literature review in Web resource estimation, followed by the discussion of how an expert-centred approach to improving such process can be advantageous to companies that develop Web applications. In addition, we will also detail our previous experience building and validating six different expert-based Web effort estimation models for ICT companies in New Zealand and Brazil.
Post-mortem interviews with the participating companies showed that they found the entire process extremely beneficial and worthwhile, and that all the models created remained in use by those companies. Finally, the methodology focus of this talk, which focuses on expert knowledge elicitation and participation, can be employed not only to improve a Web effort estimation process, but also to improve other Web development processes. 



 

 

Social Structures in Software Engineering

J.C. (Hans) van Vliet
Vrije Universiteit
Netherlands
 

Brief Bio
Hans van Vliet is Professor in Software Engineering at the VU University Amsterdam, The Netherlands, since 1986. He got his PhD from the University of Amsterdam. His research interests include software architecture, knowledge management in software development, global software development, and empirical software engineering. Before joining the VU University, he worked as a researcher at the Centrum voor Wiskunde en Informatica (CWI, Amsterdam). He spent a year as a visiting researcher at the IBM Almaden Research Center in San Jose, California. He is the author of “Software Engineering: Principles and Practice", published by Wiley (3rd Edition, 2008). He is a member of IFIP Working Group 2.10 on software architecture, and the Editor in Chief of the Journal of Systems and Software.


Abstract
Software is designed and written by groups of people, often distributed across sites and continents. These groups form social communities, with different ties, governance structures, membership structures, and so on. In this talk I explore ways to map the actual structure of a software development project onto well-known Organizational Social Structures in order to assess quality aspects of a software development organization, and software developed, in terms of this mapping.



 

 

Democratization in Science and Technology through Cloud Computing

Ivona Brandić
Vienna UT
Austria
 

Brief Bio
Dr. Ivona Brandic is Assistant Professor at the Distributed Systems Group, Information Systems Institute, Vienna University of Technology (TU Wien). Prior to that, she was Assistant Professor at the Department of Scientific Computing, Vienna University. She received her PhD degree from Vienna University of Technology in 2007. From 2003 to 2007 she participated in the special research project AURORA - Advanced Models, Applications and Software Systems for High Performance Computing and the European Union's GEMSS - Grid-Enabled Medical Simulation Services project. She is involved in the European Union's SCube project and she is leading the Austrian national FoSII - Foundations of Self-governing ICT Infrastructures project funded by the Vienna Science and Technology Fund (WWTF). She is management committee member of the European Commission's COST Action on Energy Efficient Large Scale Distributed Systems. From June to August 2008 she was visiting researcher at the University of Melbourne, Australia.

In 2011 she received the Distinguished Young Scientist Award from the Vienna University of Technology for her HALEY project on Holistic Energy Efficient Hybrid Clouds. Her interests comprise Service Level Agreement and Quality of Service management in large scale distributed systems, autonomic computing, workflow management for scientific applications, and energy efficient large scale distributed systems (Cloud, Grid, Cluster, etc.). She published more than 50 scientific journal, magazine and conference publications and co-authored a text book on federated and self-manageable Cloud infrastructures. I. Brandic co-authored European Union's Cloud Computing report paving future research directions of the EU. In 2010 she chaired the International Conference on Utility and Cloud Computing held in Chennai, India. She has been serving more than 50 program committees (among others EuroPar, COMPSAC, CloudCom) and was invited reviewer of more than 10 international journals. In 2011 she edited two special issues for Future Generation Computer Systems (Elsevier) and Scientific Programming Journal (IOS Press). I. Brandic has been invited expert evaluator of the European Commission, French National Research Organization (ANR), National Science and Engineering Research Council Canada (NSERC) and Netherlands Organization for Scientific Research (NWO).


Abstract
Cloud computing is a promising technology for the realization of large, scalable, and on-demand provisioned computing infrastructures. Currently, many enterprises are adopting Clouds to achieve high performance and scalability for their applications while maintaining low costs. Service provisioning in the Cloud is based on a set of predefined non-functional properties specified and negotiated by means of Service Level Agreements (SLAs).  Cloud workloads are dynamic and change constantly. Thus, in order to reduce steady human interactions, self-manageable Cloud techniques are required to comply with the agreed customers’ SLAs. Flexible and reliable management of SLAs is of paramount importance for both, Cloud providers and consumers. On one hand, the prevention of SLA violations avoids penalties that are costly to providers. On the other hand, based on flexible and timely reactions to possible SLA violation threats, user interaction with the system can be minimized enabling Cloud computing to take roots as a flexible and reliable form of on-demand computing. Furthermore, a trade-off has to be found between proactive actions that prevent SLA violations and those that reduce energy consumption, i.e., increase energy efficiency. In this talk we discuss how the application of Cloud computing technologies can support the work of scientists working in the field of high-throughput sequencing, while at the same time optimizing utilization of resource and increasing energy efficiency.



 

 

Model-Driven Development of Multi-View Modelling Tools: The MUVIEMOT Approach

Dimitris Karagiannis
University of Vienna
Austria
 

Brief Bio
Dimitris Karagiannis is head of the research group knowledge engineering at the University of Vienna. His main research interests include knowledge management, modelling methods and meta-modelling. Besides his engagement in national and EU-funded research projects Dimitris Karagiannis is the author of research papers and books on Knowledge Databases, Business Process Management, Workflow-Systems and Knowledge Management. He serves as expert in various international conferences and is presently on the editorial board of Business & Information Systems Engineering (BISE), Enterprise Modelling and Information Systems Architectures and the Journal of Systems Integration. He is member of IEEE and ACM and is on the executive board of GI as well as on the steering committee of the Austrian Computer Society and its Special Interest Group on IT Governance. Recently he started the Open Model Initiative (www.openmodels.at) in Austria. In 1995 he established the Business Process Management Systems Approach (BPMS), which has been successfully implemented in several industrial and service companies, and is the founder of the European software- and consulting company BOC (http://www.boc-group.com), which implements software tools based on the meta-modelling approach.


Abstract
As the complexity of modern computer and enterprise systems is ever increasing due to emerging technologies and the need to integrate different systems, modelling tools, designed to encourage modellers in creating models according to the complex reality are of rising importance. Multi-view modelling methods (MVMM) can cope with this complexity by providing visualization, decomposition, and specialization functionality. The creation of a model is decomposed into the creation of several views and integrating them in order to derive the whole model of the system. Keeping the multiple views consistent and providing suitable visualization means is vital for applicability and usability of MVMMs. By contrast, when designing such tools, one is forced to adopt conventional software engineering approaches. The paper at hand tries to contribute filling that research gap by introducing a model-driven approach, tailored to the specifics of designing multi-view modelling tools. A prototypical implementation of the approach enables automatic generation of modelling tools for MVMM using the ADOxx meta modelling platform.



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