Towards Comprehensible Representation of Controllers using Machine Learning
Wed 13 Nov 2019 13:55 - 14:10 at South Park - Student Research Competition - Selected Presentations (Undergraduate) Chair(s): Jie M. Zhang, Jin L.C. Guo
From the point of view of a software engineer, having safe and optimal controllers for real life systems like cyber physical systems is a crucial requirement before deployment. Given the mathematical model of these systems along with their specifications, model checkers can be used to synthesize controllers for them. The given work proposes novel approaches for making controller analysis easier by using machine learning to represent the controllers synthesized by model checkers in a succinct manner, while also incorporating the domain knowledge of the system. It also proposes the implementation of a visualization tool which will be integrated into existing model checkers. A lucid controller representation along with a tool to visualize it will help the software engineer debug and monitor the system much more efficiently.
Tue 12 Nov
Wed 13 Nov
13:40 - 15:20: Student Research Competition - Student Research Competition - Selected Presentations (Undergraduate) at South Park Chair(s): Jie M. ZhangUniversity College London, UK, Jin L.C. GuoMcGill University | ||||||||||||||||||||||||||||||||||||||||||
13:40 - 13:55 | Crowdsourced Report Generation via Bug Screenshot Understanding Shengcheng YuNanjing University, China | |||||||||||||||||||||||||||||||||||||||||
13:55 - 14:10 | Towards Comprehensible Representation of Controllers using Machine Learning Gargi BalasubramaniamBirla Institute of Technology and Science, Pilani, K K Birla Goa Campus | |||||||||||||||||||||||||||||||||||||||||
14:10 - 14:25 | Empirical Study of Python Call Graph Li YuNanjing University | |||||||||||||||||||||||||||||||||||||||||
14:25 - 14:40 | A Machine Learning based Approach to Identify SQL Injection Vulnerabilities Kevin ZhangWayne State University | |||||||||||||||||||||||||||||||||||||||||
14:40 - 14:55 | Boosting Neural Commit Message Generation with Code Semantic Analysis Shuyao JiangFudan University |