Deep defect and vulnerability prediction

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The objective of the proposed project is to build a product based on the patented technology from theapplicant's team on detecting software defects and security vulnerabilities automatically. The proposed productwill help developers deliver high-quality software with speed and agility.The technology, referred to as deep defect and vulnerability prediction, predicts source code regions thatcontain defects and security vulnerabilities, i.e., buggy code regions. A core technique is to leverage deeplearning to automatically learn semantic features for building more accurate prediction models to identifydefects and security vulnerabilities. Similar to a weather forecast system that leverages statistical models topredict a rainy day from abundant weather histories, this technology leverages deep learning to automaticallylearn new defect and vulnerability patterns from software development histories. The learned patterns enablethis technology to detect new classes of defects and vulnerabilities.In addition to research contributions, the potential cost savings for the software industry from the proposedproject will be immense because it will significantly reduce the cost of software development and maintenanceby (1) detecting more defects and vulnerabilities earlier (the earlier they are detected, the less they cost), and (2)improving software development productivity