?**************************** Prof. Aditya Ghose has been invited to deliver a 2-week course on "Computational Service Science" as part of the Prime Minister of India's key educational project, GIAN, under which under which foreign scholars teach at India's leading technology institutes to build knowledge and transform higher education across the country.
DSL authors Renuka Sindhgatta (also of IBM Research India), Prof. Aditya Ghose and Dr. Hoa Dam will report on a novel framework that uses data analytics for optimal business process provisioning at the 2016 International Conference on Advanced Information Systems Engineering (CAISE), the premier conference in this area (acceptance rate: 16.5%)
Prof. Aditya Ghose, Prof. Andrew Miller and Dr. David Stirling were among the authors of a submission (with Prof. David Thwaites of the University of Sydney as lead author) entitled "Mining routine radiation oncology clinical datasets within a distributed rapid learning framework: the potential for supporting optimised clinical decisions" that won the Best Abstract Award at the Cancer Institute of NSW Innovations in Cancer Treatment and Care Conference 2014.
Prof. John Mylopoulos, eminent software engineering and conceptual modelling researcher, is currently visiting the Decision Systems Lab for a period of 3 weeks. His visit was preceded by a visit by Prof. Akhil Kumar from Penn State University in early January.
The Decision Systems Lab/Centre for Oncology Informatics has initiated a new collaboration with the Liverpool Hospital on radiation oncology decision support, funded by a $114,000 research contract.
Prof. Aditya Ghose presented a keynote at a plenary session of Int'l Conf. on Service-Oriented Computing Workshops on Nov. 16th, 2015 in Goa, India.
Prof. Aditya Ghose has been invited to deliver a keynote at a joint plenary session of the Service-Oriented Enterprise Architecture and Evolutionary Business Process Workshops at the EDOC-2015 conference (Adelaide, September, 2015). His keynote title: "The post-theoretic enterprise: Data-driven evolution of enterprise functionality".
SPEAKER: Morakot Choetkiertikul UOW
DATE: Thursday, June 16, 2016
TIME: 4pm onwards
TITLE: Predicting Delivery Capability in Iterative and Agile Software Development
Abstract: Agile and iterative software development has become widely practiced in the industry. Since agile projects require fast, incremental delivery in every iteration of software development, it is essential to monitor the execution of an iteration, and predict and manage relevant risks as the iteration progresses. We present a novel, data-driven approach to providing automated support for project managers and other decision makers in predicting delivery capability for an ongoing iteration. Our approach leverages a history of project iterations and associated issues, and in particular, we extract characteristics of previous iterations and their issues in the form of features. In addition, our approach characterizes an iteration using a novel combination of techniques including feature aggregation statistics, automatic feature learning using the Bag-of-Words approach, and graph-based complexity measures. An extensive evaluation on seven large open source projects demonstrates the accuracy of our predictive models, achieving on average 75% precision, 72% recall, 72% F-measure, 89% Area Under the ROC Curve and a low error rate of 0.36 for Macro-averaged Mean Absolute Error.
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