Results 21 to 25 of about 3,391 (25)

MintHint: Automated Synthesis of Repair Hints [PDF]

arXiv, 2013
Being able to automatically repair programs is an extremely challenging task. In this paper, we present MintHint, a novel technique for program repair that is a departure from most of today's approaches. Instead of trying to fully automate program repair, which is often an unachievable goal, MintHint performs statistical correlation analysis to ...
arxiv  

Increasing Availability in Distributed Storage Systems via Clustering [PDF]

arXiv, 2017
We introduce the Fixed Cluster Repair System (FCRS) as a novel architecture for Distributed Storage Systems (DSS), achieving a small repair bandwidth while guaranteeing a high availability. Specifically we partition the set of servers in a DSS into $s$ clusters and allow a failed server to choose any cluster other than its own as its repair group ...
arxiv  

Repair Pipelining for Erasure-Coded Storage: Algorithms and Evaluation [PDF]

arXiv, 2019
We propose repair pipelining, a technique that speeds up the repair performance in general erasure-coded storage. By carefully scheduling the repair of failed data in small-size units across storage nodes in a pipelined manner, repair pipelining reduces the single-block repair time to approximately the same as the normal read time for a single block in
arxiv  

A simple model of a sequence-reading diffusion: non-self-averaging and self-averaging properties [PDF]

arXiv
Motivated by a question about the sensitivity of knots' diffusive motion to the actual sequence of nucleotides placed on a given DNA, here we study a simple model of a sequence-reading diffusion on a stretched chain with a frozen sequence of "letters" $A$ and $B$, having different interaction energies. The chain contains a single distortion - a hernia -
arxiv  

Counterexample-Guided Repair of Reinforcement Learning Systems Using Safety Critics [PDF]

arXiv
Naively trained Deep Reinforcement Learning agents may fail to satisfy vital safety constraints. To avoid costly retraining, we may desire to repair a previously trained reinforcement learning agent to obviate unsafe behaviour. We devise a counterexample-guided repair algorithm for repairing reinforcement learning systems leveraging safety critics. The
arxiv