Machine Learning based Success Prediction for Crowdsourcing Software Projects
Competitive Crowdsource Software Development (CCSD) has gained tremendous attention in the software engineering community. It explores the possibility of replacing inhouse software development to obtain cost-effective, innovative and high-quality solutions on time. CCSD depends on an open call format, where clients (companies) crowdsource their software development projects to CCSD platforms that arrange online competitions. The crowd (developers) participate in such competitions and present their innovative solutions to win monetary rewards. There are numbers of CCSD platforms e.g., TopCoder, uTest, GetACoder, and Taskcn that arrange online software development competitions. However, TopCoder1 is the largest and widely trusted CCSD platform.
Thu 18 NovDisplayed time zone: Hobart change
21:00 - 22:00 | Learning ApplicationsResearch Papers / Tool Demonstrations / Journal-first Papers at Kangaroo Chair(s): Michael Pradel University of Stuttgart | ||
21:00 20mTalk | Deep GUI: Black-box GUI Input Generation with Deep Learning Research Papers Faraz YazdaniBanafsheDaragh University of California, Irvine, Sam Malek University of California at Irvine, USA | ||
21:20 20mTalk | Towards Exploring the Limitations of Active Learning: An Empirical Study Research Papers Qiang Hu University of Luxembourg, Yuejun GUo University of Luxembourg, Maxime Cordy University of Luxembourg, Luxembourg, Xiaofei Xie Kyushu University, Wei Ma University of Luxembourg, Mike Papadakis University of Luxembourg, Luxembourg, Yves Le Traon University of Luxembourg, Luxembourg | ||
21:40 10mTalk | Machine Learning based Success Prediction for Crowdsourcing Software Projects Journal-first Papers Inam Illahi Beijing Institute of Technology, Hui Liu Beijing Institute of Technology, Qasim Umer Beijing Institute of Technology, Nan Niu University of Cincinnati | ||
21:50 5mTalk | SoManyConflicts: Resolve Many Merge Conflicts Interactively and Systematically Tool Demonstrations |