14 July 2009
SEAD Seminar: Alberto Sardinha
JLB meeting room 10
Alberto Sardinha, Lancaster University
Title: EA-Analyzer: Automating Conflict Detection in Aspect-Oriented Requirements
Abstract: One of the aims of Aspect-Oriented Requirements Engineering is to address the composability and subsequent analysis of crosscutting and non-crosscutting concerns during requirements engineering. Composing concerns may help to reveal conflicting dependencies that need to be identified and resolved. However, detecting conflicts in a large set of textual aspect-oriented requirements is an error-prone and time- consuming task. This talk presents EA-Analyzer, an automated tool for identifying conflicts in aspect-oriented requirements specified in natural-language text. The tool is based on a novel application of a Bayesian learning method that has been effective at classifying text. We present an empirical evaluation of the tool with three industrial- strength requirements documents from different real-life domains. We show that the tool achieves up to 92.97% accuracy when one of the case study documents is used as a training set and the other two as a validation set.
Short Bio: Alberto Sardinha is a Research Fellow in the Computing Department at Lancaster University (on a Marie Curie “International Incoming” Fellowship from the European Commission). His research is focused on building tools (based on machine learning techniques and multi-agent systems) for aspect-oriented requirements engineering. From 2005 to 2008, he was a post-doc in the e-Supply Chain Management Laboratory at Carnegie Mellon University, where he conducted research on supply chain trading agents and decentralized trust management. He received a Doctor of Science degree from the Pontifical Catholic University (PUC-Rio) of Rio de Janeiro, Brazil, in 2005 for a work on trading agents and agent-oriented software engineering.
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