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Conference Papers Year : 2013

Rewriting Large Multimedia Application Execution Traces with few Event Sequences

Abstract

The analysis of multimedia application traces can reveal important information to enhance program execution comprehension. However typical size of traces can be in gigabytes, which hinders their effective exploitation by application developers. In this paper, we study the problem of finding a set of sequences of events that allows a reduced-size rewriting of the original trace. These sequences of events, that we call blocks, can simplify the exploration of large execution traces by allowing application developers to see an abstraction instead of low-level events. The problem of computing such set of blocks is NP-hard and naive approaches lead to prohibitive running times that prevent analysing real world traces. We propose a novel algorithm that directly mines the set of blocks. Our experiments show that our algorithm can analyse real traces of up to two hours of video. We also show experimentally the quality of the set of blocks proposed, and the interest of the rewriting to understand actual trace data.
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Dates and versions

hal-00923538 , version 1 (06-01-2014)

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Christiane Kamdem Kengne, Leon Constantin Fopa, Alexandre Termier, Noha Ibrahim, Marie-Christine Rousset, et al.. Rewriting Large Multimedia Application Execution Traces with few Event Sequences. KDD 2013 - International Conference on Knowledge Discovery and Data Mining, Aug 2013, Chicago, IL, United States. pp.1348-1356, ⟨10.1145/2487575.2488211⟩. ⟨hal-00923538⟩
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