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): Jin L.C. Guo, Jie M. Zhang
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.
Presentation (Towards Comprehensible Representation of Controllers using Machine Learning (1).pdf) | 2.6MiB |
Tue 12 NovDisplayed time zone: Tijuana, Baja California change
Wed 13 NovDisplayed time zone: Tijuana, Baja California change
13:40 - 15:20 | Student Research Competition - Selected Presentations (Undergraduate)Student Research Competition at South Park Chair(s): Jin L.C. Guo McGill University, Jie M. Zhang University College London, UK | ||
13:40 15m | Crowdsourced Report Generation via Bug Screenshot Understanding Student Research Competition Shengcheng Yu Nanjing University, China File Attached | ||
13:55 15m | Towards Comprehensible Representation of Controllers using Machine Learning Student Research Competition Gargi Balasubramaniam Birla Institute of Technology and Science, Pilani, K K Birla Goa Campus File Attached | ||
14:10 15m | Empirical Study of Python Call Graph Student Research Competition Li Yu Nanjing University | ||
14:25 15m | A Machine Learning based Approach to Identify SQL Injection Vulnerabilities Student Research Competition Kevin Zhang Wayne State University | ||
14:40 15m | Boosting Neural Commit Message Generation with Code Semantic Analysis Student Research Competition Shuyao Jiang Fudan University |