NDLI: Automatic Comparison of Load Tests to Support the Performance Analysis of Large Enterprise Systems

Content Provider	IEEE Xplore Digital Library
Author	Malik, H. Zhen Ming Jiang Adams, B. Hassan, A.E. Flora, P. Hamann, G.
Copyright Year	2010
Abstract	Load testing is crucial to uncover functional and performance bugs in large-scale systems. Load tests generate vast amounts of performance data, which needs to be compared and analyzed in limited time across tests. This helps performance analysts to understand the resource usage of an application and to find out if an application is meeting its performance goals. The biggest challenge for performance analysts is to identify the few important performance counters in the highly redundant performance data. In this paper, we employed a statistical technique, Principal Component Analysis (PCA) to reduce the large volume of performance counter data, to a smaller, more meaningful and manageable set. Furthermore, our methodology automates the process of comparing the important counters across load tests to identify performance gains/losses. A case study on load test data of a large enterprise application shows that our methodology can effectively guide performance analysts to identify and compare top performance counters across tests in limited time.
Starting Page	222
Ending Page	231
File Size	345711
Page Count	10
File Format	PDF
ISBN	9781612843698
ISSN	15345351
e-ISBN	9780769543215
DOI	10.1109/CSMR.2010.39
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-03-15
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Radiation detectors Principal component analysis Testing Loading Correlation Stress Monitoring PCA Load Test Performance Counters
Content Type	Text
Resource Type	Article

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