Making Sense of Data in Software Engineering Data Analytics
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Speaker (s):
Jacky KEUNG
Associate Professor,
Department of Computer Science,
City University of Hong Kong
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Date:
Time:
Venue:
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June 19, 2019, Wednesday
11:00am - 12:00pm
Meeting Room 4.4, Level 4
School of Information Systems
Singapore Management University
80 Stamford Road
Singapore 178902
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ABSTRACT
Software Engineering has been shifting its primary focus from traditional software development techniques to utilizing a diverse range of techniques such as machine learning and statistics to understand and making sense of software data observed, in order to making and communicating decisions from data. In this seminar, we are focusing on our predictive analytics in software defect predictions on the class imbalance issue and its effects of resampling approaches, as well as their significant effects on defect prioritization and classification problems. Furthermore, we show new experimentations on utilizing Convolutional Neural Network CNN on Deep Learning to improve bug localization as well as its applications to future directions in software engineering.
About the Speaker
Dr. Jacky Keung received his B.Sc. (Hons) in Computer Science from the University of Sydney, Australia and his Ph.D. in Software Engineering from the University of New South Wales, Australia. He is Associate Professor in the Department of Computer Science, City University of Hong Kong. He has substantial research experience in experimental software engineering, including software effort estimation, data analytics, statistical analysis, and the empirical evaluation of software engineering theories and methodologies. His main research area is in software effort and cost estimation, empirical modelling and evaluation of complex systems, and intensive data mining for software engineering datasets, as well as his latest work in deep-learning and blockchain for a FinTech Project. He has published many papers in prestigious journals including IEEE-TSE, IEEE-SOFTWARE, EMSE, IST, JSS as well as in many other leading journals and international conferences. He has recently received over HK$10M+ external research funds from the industry and the government in Hong Kong, mainly for projects related to Data Analytics and FinTech areas.
Publication List (DBLP) : https://dblp2.uni-trier.de/pid/86/7853.html
