Github Wayne Coding Devmut Based on the interview result, we design a novel framework testing method, i.e., devmut, which adopts the mutation operators and constraints based on the expertise of developers and detect defects in more stages of dl models' lifecycle. To identify important bugs that matter to developers, we propose a novel dl framework testing method devmut, which generates models by adopting mutation operators and constraints derived from developer expertise.
Wayne Coding Github Contribute to wayne coding devmut development by creating an account on github. Wayne coding devmut public notifications you must be signed in to change notification settings fork 1 star 1. Deep learning (dl) frameworks are the fundamental infrastructure for various dl applications. framework defects can profoundly cause disastrous accidents, thus. {"payload":{"feedbackurl":" github orgs community discussions 53140","repo":{"id":856911741,"defaultbranch":"main","name":"devmut","ownerlogin":"wayne coding","currentusercanpush":false,"isfork":false,"isempty":false,"createdat":"2024 09 13t12:51:50.000z","owneravatar":" avatars.githubusercontent u 172040318?v=4","public.
Datawayne Wayne Github Deep learning (dl) frameworks are the fundamental infrastructure for various dl applications. framework defects can profoundly cause disastrous accidents, thus. {"payload":{"feedbackurl":" github orgs community discussions 53140","repo":{"id":856911741,"defaultbranch":"main","name":"devmut","ownerlogin":"wayne coding","currentusercanpush":false,"isfork":false,"isempty":false,"createdat":"2024 09 13t12:51:50.000z","owneravatar":" avatars.githubusercontent u 172040318?v=4","public. To identify important bugs that matter to developers, we propose a novel dl framework testing method devmut, which generates models by adopting mutation operators and constraints derived from developer expertise. Devmut extends defect detection across the lifecycle stages of dl models (e.g., model construction, execution, and deployment), targeting various framework defects such as resource and. Our research aims to ensure the correctness of deep learning systems, building more reliable, effective, and efficient ai systems for software engineering. specifically, we focus on the following ai infrastructures testing:. Have a question about this project? sign up for a free github account to open an issue and contact its maintainers and the community. by clicking “sign up for github”, you agree to our terms of service and privacy statement. we’ll occasionally send you account related emails. already on github? sign in to your account 0 open 0 closed.
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