Dear all, Our next AI seminar is scheduled to be on January 19th, 2-3 PM. It will be followed by a 30-minute Q&A session with the graduate students. Location: KEC 1001 Zoom link: https://oregonstate.zoom.us/j/98684050301?pwd=ZzhianQxUFBPUmdYVWJKOFhaVURCQT09<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonstate.zoom.us%2Fj%2F98684050301%3Fpwd%3DZzhianQxUFBPUmdYVWJKOFhaVURCQT09&data=05%7C02%7Cai%40engr.orst.edu%7C38070393b2e743bcdb7008dc17ca2ce5%7Cce6d05e13c5e4d6287a84c4a2713c113%7C0%7C0%7C638411404300967633%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=UkhQoNBk2Xdfa7T1c63yCP9Uoy5nSlz9mHEW05RJYuc%3D&reserved=0> AI for Software Engineering (AI4SE): Opportunities and Challenges Manish Motwani Assistant Professor School of Electrical Engineering and Computer Science Oregon State University Abstract: Software is ubiquitous but often faulty. Software engineers spend 35–50% of their time debugging software, accounting for 50–75% of the total software development budget. With the transformative power of AI, software engineering researchers have begun integrating AI into various phases of the software development lifecycle to address these issues and enhance software quality. In this talk, I will provide a high-level overview of opportunities and challenges for applying AI in software engineering, specifically focusing on software testing and debugging. I will then present my research on using natural language artifacts to automatically improve software quality, including my technique for automatically generating tests with oracles from software specifications and my method for using developer-written tests in conjunction with bug reports to automatically localize and repair bugs. Speaker Bio: Manish Motwani is an Assistant Professor in the School of Electrical Engineering and Computer Science at Oregon State University. Before joining OSU, he worked as a postdoc at Georgia Tech and has four years of industry work experience as a researcher at the Tata Research Development and Design Center, an industrial research lab in India. His interests lie in improving software engineers’ productivity and aiding software engineers in developing high-quality software by automating software engineering practices. His research involves learning phenomena from large software repositories and using that knowledge to design novel automation techniques, such as requirements elicitation, test synthesis, and program repair. Please watch this space for future AI Seminars : https://engineering.oregonstate.edu/EECS/research/AI<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineering.oregonstate.edu%2FEECS%2Fresearch%2FAI&data=05%7C02%7Cai%40engr.orst.edu%7C38070393b2e743bcdb7008dc17ca2ce5%7Cce6d05e13c5e4d6287a84c4a2713c113%7C0%7C0%7C638411404300967633%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=Pf%2FNEDcj46myMvdu%2B5WSlL30u2fgbaJ%2BTY2vpCet8Pw%3D&reserved=0> Rajesh Mangannavar, Graduate Student Oregon State University ---- AI Seminar Important Reminders: -> For graduate students in the AI program, attendance is strongly encouraged