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Ontario Tech acknowledges the lands and people of the Mississaugas of Scugog Island First Nation.

We are thankful to be welcome on these lands in friendship. The lands we are situated on are covered by the Williams Treaties and are the traditional territory of the Mississaugas, a branch of the greater Anishinaabeg Nation, including Algonquin, Ojibway, Odawa and Pottawatomi. These lands remain home to many Indigenous nations and peoples.

We acknowledge this land out of respect for the Indigenous nations who have cared for Turtle Island, also called North America, from before the arrival of settler peoples until this day. Most importantly, we acknowledge that the history of these lands has been tainted by poor treatment and a lack of friendship with the First Nations who call them home.

This history is something we are all affected by because we are all treaty people in Canada. We all have a shared history to reflect on, and each of us is affected by this history in different ways. Our past defines our present, but if we move forward as friends and allies, then it does not have to define our future.

Learn more about Indigenous Education and Cultural Services

November 2, 2011

Speakers: Kevin Jalbert, MSc student, Ontario Tech University; David Kelk, PhD student, Ontario Tech University

Title: ARC: Automatic Repair of Concurrency Bugs

Abstract: Concurrent software bugs appear intermittently due to the non-deterministic nature of how threads might be scheduled to run. A concurrency bug can be fixed by using known concurrency mechanisms to ensure proper thread scheduling. ARC takes advantage of this fact by evolving a buggy program using known concurrency mutation operators in attempts to ensure proper program execution. An evolved program is evaluated using ConTest by repeatedly exploring thread interleavings to provide a certain level of confidence that the majority of schedules have been explored. A fitness function will evaluated the functional correctness of the evolved program. The evaluation feedback from ConTest is used to heuristically select the most appropriate mutation operator to next apply. A second phase of evolution is applied after an appropriate level of functional fitness is achieved to optimize the non-functional fitness. This phase will minimize the usage of synchronization mechanisms to ensure timely execution of the evolved program while retaining the functional correctness.