Abstract. We propose a symbolic algorithm to accurately predict atomicity violations by analyzing a concrete execution trace of a concurrent program. We use both the execution trac...
Chao Wang, Rhishikesh Limaye, Malay K. Ganai, Aart...
This study exploits statistical redundancy inherent in natural language to automatically predict scores for essays. We use a hybrid feature identification method, including syntac...
Jill Burstein, Karen Kukich, Susanne Wolff, Chi Lu...
The automated analysis of feature models is recognized as one of the key challenges for automated software development in the context of Software Product Lines (SPL). However, aft...
David Benavides, Sergio Segura, Pablo Trinidad, An...
We propose a novel unsupervised learning framework for activity perception. To understand activities in complicated scenes from visual data, we propose a hierarchical Bayesian mod...
Principles of the framework called time series forecasting automation are presented. It is required in processing massive temporal data sets and creating completely user-oriented f...