Reference number : GC-2017-Q1-00581, amendment number : , agreement type : G, recipient legal name : Tan, Lin (University of Waterloo), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Idea to Innovation, program name french : De l'idée à l'innovation, program purpose english : The objective of the proposed project is to build a product based on the patented technology from the_x000D_
applicant's team on detecting software defects and security vulnerabilities automatically. The proposed product_x000D_
will help developers deliver high-quality software with speed and agility._x000D_
The technology, referred to as deep defect and vulnerability prediction, predicts source code regions that_x000D_
contain defects and security vulnerabilities, i.e., buggy code regions. A core technique is to leverage deep_x000D_
learning to automatically learn semantic features for building more accurate prediction models to identify_x000D_
defects and security vulnerabilities. Similar to a weather forecast system that leverages statistical models to_x000D_
predict a rainy day from abundant weather histories, this technology leverages deep learning to automatically_x000D_
learn new defect and vulnerability patterns from software development histories. The learned patterns enable_x000D_
this technology to detect new classes of defects and vulnerabilities._x000D_
In addition to research contributions, the potential cost savings for the software industry from the proposed_x000D_
project will be immense because it will significantly reduce the cost of software development and maintenance_x000D_
by (1) detecting more defects and vulnerabilities earlier (the earlier they are detected, the less they cost), and (2)_x000D_
improving software development productivity, program purpose french : The objective of the proposed project is to build a product based on the patented technology from the_x000D_
applicant's team on detecting software defects and security vulnerabilities automatically. The proposed product_x000D_
will help developers deliver high-quality software with speed and agility._x000D_
The technology, referred to as deep defect and vulnerability prediction, predicts source code regions that_x000D_
contain defects and security vulnerabilities, i.e., buggy code regions. A core technique is to leverage deep_x000D_
learning to automatically learn semantic features for building more accurate prediction models to identify_x000D_
defects and security vulnerabilities. Similar to a weather forecast system that leverages statistical models to_x000D_
predict a rainy day from abundant weather histories, this technology leverages deep learning to automatically_x000D_
learn new defect and vulnerability patterns from software development histories. The learned patterns enable_x000D_
this technology to detect new classes of defects and vulnerabilities._x000D_
In addition to research contributions, the potential cost savings for the software industry from the proposed_x000D_
project will be immense because it will significantly reduce the cost of software development and maintenance_x000D_
by (1) detecting more defects and vulnerabilities earlier (the earlier they are detected, the less they cost), and (2)_x000D_
improving software development productivity, agreement title english : Deep defect and vulnerability prediction, agreement title french : Deep defect and vulnerability prediction, agreement number : I2IPJ, agreement value : 125000.0, agreement start date : 2017-04-25, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2018-2019), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2018-2019), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada