SCS Recruitment Semiar: Fan Long, Learning How to Patch Software Errors Automatically

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Software systems are increasingly integrated into every part of our society. As the number of systems and our dependence on these systems continue to grow, making these systems reliable and secure becomes an increasingly important challenge for our society and a daunting task for software developers.

Automatic patch generation holds out the promise of automatically correcting software defects without the need for developers to diagnose, understand, and correct these defects.

In this talk, Long will present two novel automatic patch generation systems, Prophet and Genesis, both of which learn from past successful patches to automatically fix defects. By collectively leveraging development efforts worldwide, Prophet and Genesis automatically generate correct patches for real-world defects in large open-source C and Java applications with millions of lines of code.

This research also demonstrates that the growing volume of software programs are not just a challenge but a great opportunity. Exploiting this opportunity can enable revolutionary automated techniques that enhance software reliability and security.



Fan Long is a Ph.D. candidate studying computer science at the Massachusetts Institute of Technology. His research focuses on developing automated programming systems to improve software reliability and security.

He has developed systems that automatically identify and eliminate errors in large software programs. These systems enable software programs to operate successfully in spite of the presence of errors.


  • Workflow Status: Published
  • Created By: Devin Young
  • Created: 02/17/2017
  • Modified By: Fletcher Moore
  • Modified: 04/13/2017