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Item type:Publication, Access status: without files , Scalable offline monitoring of temporal specifications(Springer, 2016-03-07); ; ; ; We propose an approach to monitoring IT systems offline where system actions are logged in a distributed file system and subsequently checked for compliance against policies formulated in an expressive temporal logic. The novelty of our approach is that monitoring is parallelized so that it scales to large logs. Our technical contributions comprise a formal framework for slicing logs, an algorithmic realization based on MapReduce, and a high-performance implementation. We evaluate our approach analytically and experimentally, proving the soundness and completeness of our slicing techniques and demonstrating its practical feasibility and efficiency on real-world logs with 400 GB of relevant data.Publicationtype: Journal Article19 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Scalable offline monitoring(Springer, 2014-09); ; ; ; We propose an approach to monitoring IT systems offline, where system actions are logged in a distributed file system and subsequently checked for compliance against policies formulated in an expressive temporal logic. The novelty of our approach is that monitoring is parallelized so that it scales to large logs. Our technical contributions comprise a formal framework for slicing logs, an algorithmic realization based on MapReduce, and a high-performance implementation. We evaluate our approach analytically and experimentally, proving the soundness and completeness of our slicing techniques and demonstrating its practical feasibility and efficiency on real-world logs with 400 GB of relevant data.Publicationtype: Conference Paper not in Proceedings9