The Concept of Stratified Sampling of Execution Traces

Pirzadeh, Heidar; Shanian, Sara; Hamou-Lhadj, Abdelwahab; Mehrabian, Ali Reza

doi:10.1109/icpc.2011.17

Cited by 20 publications

(12 citation statements)

References 10 publications

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“…Pirzadeh et al [15] proposed a trace sampling framework based on stratified sampling to reduce the size of a trace by distributing the desired characteristics of an execution trace similarly in both the sampled and the original trace. To generate sampled execution traces, random sampling techniques have been extensively used.…”

Section: Related Workmentioning

confidence: 99%

SCAN: An Approach to Label and Relate Execution Trace Segments

Medini

Antoniol

Guéhéneuc

et al. 2012

2012 19th Working Conference on Reverse Engineering

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Identifying concepts in execution traces is a task often necessary to support program comprehension or maintenance activities. Several approaches-static, dynamic or hybrid-have been proposed to identify cohesive, meaningful sequence of methods in execution traces. However, none of the proposed approaches is able to label such segments and to identify relations between segments of the same trace.This paper present SCAN (Segment Concept AssigNer) an approach to assign labels to sequences of methods in execution traces, and to identify relations between such segments. SCAN uses information retrieval methods and formal concept analysis to produce sets of words helping the developer to understand the concept implemented by a segment. Specifically, formal concept analysis allows SCAN to discover commonalities between segments in different trace areas, as well as terms more specific to a given segment and high level relations between segments.The paper describes SCAN along with a preliminary manual validation-upon execution traces collected from usage scenarios of JHotDraw and ArgoUML-of SCAN accuracy in assigning labels representative of concepts implemented by trace segments.

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Section: Related Workmentioning

confidence: 99%

SCAN: An Approach to Label and Relate Execution Trace Segments

Medini

Antoniol

Guéhéneuc

et al. 2012

2012 19th Working Conference on Reverse Engineering

View full text Add to dashboard Cite

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“…We traced the system for a small duration, but long enough to have a lot of half-open TCP connections. The whole XML file that describes this scenario is accessible from our public web page 4 . Our described pattern has 2 coexisting FSMs.…”

Section: Illustrative Example and Discussionmentioning

confidence: 99%

“…Another solution is events filtering which allows to only analyze an interesting sequence of events from a trace. Trace filtering actually eliminates outlier trace events and noise, and highlights a selected set of trace data based on either the type of events, timestamps, process name, event arguments or even the priority or importance of an event [4], [5].…”

Section: Introductionmentioning

confidence: 99%

A Flexible Data-Driven Approach for Execution Trace Filtering

Kouame

Ezzati‐Jivan

Dagenais

2015

2015 IEEE International Congress on Big Data

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“…As said before, one have to deal with huge volume of traces and the size explosion problem was largely described in [1]. Different techniques to reduce traces were proposed, as those in [7,8], and Pirzadeh in [9] introduces a notion of trace size reduction to obtain a representative sample of the original trace; however the last approach does not take into account the sequentiality of events, essential to understand multimedia application traces. The same author gives an idea in [23] to mimic the psychological processes in order to deal with huge volume of visual data.…”

Section: Related Workmentioning

confidence: 99%

“…Various studies have proposed the techniques to reduce the volume of traces ( [7,8]) with sampling methods. These techniques can obtain a reduced execution trace but not always representative of the entire trace [9]. Pirzadeh et al introduced in [2] that the general consensus in the trace analysis community is to emphasise the work towards effective trace abstraction techniques, such as [10].…”

Section: Introductionmentioning

confidence: 98%

Enhancing the Analysis of Large Multimedia Applications Execution Traces with FrameMiner

Kengne

Fopa

Ibrahim

et al. 2012

2012 IEEE 12th International Conference on Data Mining Workshops

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ISBN: 978-1-4673-5164-5 - http://icdm2012.ua.ac.be/International audienceThe analysis of multimedia application traces can reveal important information to enhance program comprehension. However traces can be very large, which hinders their effective exploitation. In this paper, we study the problem of finding a \textit{k-golden} set of blocks that best characterize data. Sequential pattern mining can help to automatically discover the blocks, and we called \textit{k-golden set}, a set of $k$ blocks that maximally covers the trace. These kind of blocks can simplify the exploration of large traces by allowing programmers to see an abstraction instead of low-level events. We propose an approach for mining golden blocks and finding coverage of frames. The experiments carried out on video and audio application decoding show very promising results

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The Concept of Stratified Sampling of Execution Traces

Cited by 20 publications

References 10 publications

SCAN: An Approach to Label and Relate Execution Trace Segments

SCAN: An Approach to Label and Relate Execution Trace Segments

A Flexible Data-Driven Approach for Execution Trace Filtering

Enhancing the Analysis of Large Multimedia Applications Execution Traces with FrameMiner

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