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DTSTART:20231105T020000
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DTSTART:20240310T020000
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UID:calendar.2995.events_uoft_date.0@www.statistics.utoronto.ca
CREATED:20240108T143153Z
DESCRIPTION:\nWhen and Where: \nMonday, February 05, 2024 3:30 pm to 4:30
  pm \n Hybrid, Rooms 9014 & 9016 \n Ontario Power Building \n 700 Univers
 ity Avenue, Toronto, ON M5G 1Z5 \n\nSpeakers \nCaroline Lemieux \n\nDesc
 ription: \nAs software becomes increasingly pervasive throughout all diffe
 rent aspects of our society, the consequences of software bugs (inconsist
 encies between a developer’s intent and the implementation) become increas
 ingly severe. Even basic programming errors can lead to security vulnerabi
 lities with disastrous consequences, such as the Heartbleed bug which led
  to the shutdown of the Canada Revenue Agency website and the leak of 900 
 SINs. The field of automated testing aims to uncover these bugs automatica
 lly, before they have broader impacts on software users. This talk first 
 covers the importance of manual testing of software as well as the fundame
 ntals of automated testing, in particular randomized testing techniques s
 uch as fuzz testing and property-based testing. This will include practica
 l examples as well as pointers to testing tools to use in different scenar
 ios. Then, the talk will cover areas of research and improvement in autom
 ated testing, as well as the promise of generative AI techniques in lower
 ing the barrier to entry to fuzz testing and property-based testing.Please
  join the event.About Caroline LemieuxCaroline Lemieux is an Assistant Pro
 fessor at The University of British Columbia. Her research interests centr
 e around improving the correctness and reliability of software systems by 
 developing automated methods for engineering tasks such as testing, debug
 ging, and comprehension. Her work on fuzz testing has been awarded an ACM
  SIGSOFT Distinguished Paper Award, Distinguished Artifact Award, Tool D
 emonstration Award, and Best Paper Award (Industry Track). She was a post
 doctoral researcher at Microsoft Research NYC, studying the use of deep l
 earning for automated testing. She completed her PhD in Computer Science a
 t UC Berkeley, advised by Koushik Sen; there, she was the recipient of 
 a Berkeley Fellowship for Graduate Study, and a Google PhD Fellowship in 
 Programming Technologies and Software Engineering. Prior to Berkeley, she
  completed her undergraduate studies in Combined Honours Computer Science 
 and Mathematics at UBC, winning the Governor General’s Silver Medal in th
 e Faculty of Science. \n\nContact Information: \n CANSSI \n700 University 
 Avenue, Toronto, ON M5G 1Z5 \n\nCategories \n Data Science ARES \n\nAudi
 ences \n FacultyGraduate Students
DTSTART;TZID=America/New_York:20240205T153000
DTEND;TZID=America/New_York:20240205T163000
LAST-MODIFIED:20240108T143230Z
LOCATION:700 University Avenue, Toronto, ON M5G 1Z5
SUMMARY:How Automated Testing Works, and When to Use It
URL;TYPE=URI:https://www.statistics.utoronto.ca/events/how-automated-testin
 g-works-and-when-use-it
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