Enhancing the Analysis of Large Multimedia Applications Execution Traces with FrameMiner

Kengne, Christiane Kamdem; Fopa, Leon; Ibrahim, Noha; Termier, Alexandre; Rousset, Marie-Christine; Washio, Takashi

doi:10.1109/icdmw.2012.95

Cited by 1 publication

(1 citation statement)

References 16 publications

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“…A naive approach, that we exposed previously in [6], consists in solving these two subproblems separately. A good heuristic for the discovery of the blocks is to assume the blocks are frequent sequences of the set of frames.…”

Section: Baseline Approachesmentioning

confidence: 99%

Efficiently rewriting large multimedia application execution traces with few event sequences

Kengne

Fopa

Termier

et al. 2013

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

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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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Section: Baseline Approachesmentioning

confidence: 99%