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Cor-Paul Bezemer; Andy Zaidman
Performance Optimization of Deployed Software-as-a-service Applications Journal Article
Journal of Systems and Software (JSS), 87 , pp. 87-103, 2014.
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Abstract | BibTeX | Tags: Performance analysis, Performance maintenance
@article{BezemerJSS13,
title = {Performance Optimization of Deployed Software-as-a-service Applications},
author = {Cor-Paul Bezemer and Andy Zaidman},
year = {2014},
date = {2014-01-01},
urldate = {2014-01-01},
journal = {Journal of Systems and Software (JSS)},
volume = {87},
pages = {87-103},
publisher = {Elsevier},
abstract = {The goal of performance maintenance is to improve the performance of a software system after delivery. As the performance of a system is often characterized by unexpected combinations of metric values, manual analysis of performance is hard in complex systems. In this paper, we propose an approach that helps performance experts locate and analyze spots – so called performance improvement opportunities (PIOs) –, for possible performance improvements. PIOs give performance experts a starting point for performance improvements, e.g., by pinpointing the bottleneck component. The technique uses a combination of association rules and performance counters to generate the rule coverage matrix, a matrix which assists with the bottleneck detection.
In this paper, we evaluate our technique in two cases studies. In the first, we show that our technique is accurate in detecting the timeframe during which a PIO occurs. In the second, we show that the starting point given by our approach is indeed useful and assists a performance expert in diagnosing the bottleneck component in a system with high precision.},
keywords = {Performance analysis, Performance maintenance},
pubstate = {published},
tppubtype = {article}
}
The goal of performance maintenance is to improve the performance of a software system after delivery. As the performance of a system is often characterized by unexpected combinations of metric values, manual analysis of performance is hard in complex systems. In this paper, we propose an approach that helps performance experts locate and analyze spots – so called performance improvement opportunities (PIOs) –, for possible performance improvements. PIOs give performance experts a starting point for performance improvements, e.g., by pinpointing the bottleneck component. The technique uses a combination of association rules and performance counters to generate the rule coverage matrix, a matrix which assists with the bottleneck detection.
In this paper, we evaluate our technique in two cases studies. In the first, we show that our technique is accurate in detecting the timeframe during which a PIO occurs. In the second, we show that the starting point given by our approach is indeed useful and assists a performance expert in diagnosing the bottleneck component in a system with high precision.
In this paper, we evaluate our technique in two cases studies. In the first, we show that our technique is accurate in detecting the timeframe during which a PIO occurs. In the second, we show that the starting point given by our approach is indeed useful and assists a performance expert in diagnosing the bottleneck component in a system with high precision.