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摘要: ## Abstract 背景:关于test RNN-based stateful system的研究较少 本文:DeepStellar Method: 1. model RNN as an abstract state transition system 2. design 2 trace simi 阅读全文
posted @ 2023-08-29 16:02 雪溯 阅读(31) 评论(0) 推荐(0)
摘要: ## Abstract 本文:VerifyML Task: testing ML based applications(ML based image classifier) by metamorphic testing Github: https://github.com/verml/VerifyM 阅读全文
posted @ 2023-08-29 16:02 雪溯 阅读(13) 评论(0) 推荐(0)
摘要: ## Abstract 本文: 1. 分析DL Library中的错误,给出了2个研究问题的答案 1. RQ1: TensorFlow 中的错误有哪些症状和原因? 2. RQ2: TensorFlow 内部的错误在哪⾥? 2. 总结了5个发现 1. 与症状相⽐,根本原因更具决定性,因为多个根本原因主 阅读全文
posted @ 2023-08-29 16:02 雪溯 阅读(14) 评论(0) 推荐(0)
摘要: ## Abstract 本文:RTIs(Referentially Transparent Inputs), Purity Task: Testing Machine Translation Model Method: referentially transparent input(在不同的上下文中 阅读全文
posted @ 2023-08-29 16:01 雪溯 阅读(13) 评论(0) 推荐(0)
摘要: ## Abstract Background: 1. discriminatory inputs, e.g., from societal bias, produce error, need to conduct fairness testing(generating discriminatory 阅读全文
posted @ 2023-08-29 15:48 雪溯 阅读(19) 评论(0) 推荐(0)
摘要: ## Abstract 本文: ShapeTracer Task: 1. Study on 12289 failed TensorFlow jobs 2. detecting TensorFlow shape-related errors with a constraint-based approa 阅读全文
posted @ 2023-08-29 15:48 雪溯 阅读(16) 评论(0) 推荐(0)
摘要: ## Abstract 本文:Metamorphic Testing for machine learning classifiers Method: cross-validation, metamorphic testing 1. MR-0: Consistence with affine tra 阅读全文
posted @ 2023-08-29 15:48 雪溯 阅读(16) 评论(0) 推荐(0)
摘要: ## Abstract 背景:目前的研究集中在例如交换几个像素这种digital perturbation,这些是很难发生在现实世界的;生成both digital and physical adversarial perturbation很重要 本文:DeepBillboard Task: Tes 阅读全文
posted @ 2023-08-29 15:47 雪溯 阅读(21) 评论(0) 推荐(0)
摘要: ## Abstract 本文:Eagle Task: use equivalent graphs to differential test DL libraries Method: 使用不同的APIs, data types or optimizations来获取equivalent graphs, 阅读全文
posted @ 2023-08-29 15:47 雪溯 阅读(20) 评论(0) 推荐(0)
摘要: ## Abstract 背景:Neural networks can be regarded as a new programming paradigm, Tensorflow 和PyTorch相当于Compiler,我们已知如果编译器缺乏Specification 本文:ExAIS Task: p 阅读全文
posted @ 2023-08-29 15:47 雪溯 阅读(18) 评论(0) 推荐(0)
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