Książka Workload-sensitive Timing Behavior Analysis for Fault Localization in Software Systems Matthias Rohr

Workload-sensitive Timing Behavior Analysis for Fault Localization in Software Systems

Autor: Matthias Rohr
Język: Angielski
Oprawa: Twarda
Wydawca: Books on Demand
Dostępność: Dostępna u dostawcy
Wysyłamy za 10-13 dni
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Software timing behavior measurements, such as response times, often show high statistical variance....

Informacje o książce

Język
Angielski
Oprawa
Książka - Twarda
Data wydania
2015
strony
232
EAN
9783734745164
ISBN
3734745160
Enbook ID
09207923
Wydawca
Waga
498
Wymiary
160 x 226 x 19

Pełny opis

Software timing behavior measurements, such as response times, often show high statistical variance. This variance can make the analysis difficult or even threaten the applicability of statistical techniques. This thesis introduces a method for improving the analysis of software response time measurements that show high variance.§§Our approach can find relations between timing behavior variance and both trace shape information and workload intensity information. This relation is used to provide timing behavior measurements with virtually less variance. This can make timing behavior analysis more robust (e.g., improved confidence and precision) and faster (e.g., less simulation runs and shorter monitoring period). The thesis contributes TracSTA (Trace-Context-Sensitive Timing Behavior Analysis) and WiSTA (Workload-Intensity-Sensitive Timing Behavior Analysis). TracSTA uses trace shape information (i.e., the shape of the control flow corresponding to a software operation execution) and WiSTA uses workload intensity metrics (e.g., the number of concurrent software executions) to create context-specific timing behavior profiles.§§Both the applicability and effectiveness are evaluated in several case studies and field studies. The evaluation shows a strong relation between timing behavior and the metrics considered by TracSTA and WiSTA. Additionally, a fault localization approach for enterprise software systems is presented as application scenario. It uses the timing behavior data provided by TracSTA and WiSTA for anomaly detection.

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