I have got the comment on my previous post “ BIRT based Control Chart “ with questions about how actually in BIRT the data are prepared for ...
Final update: The COMPUTER MEASUREMENT GROUP (www.CMG.org) membership has elected me to serve as Director for the 2016 - 2017 term 2015 ...
Friday, January 20, 2012
Control Chart usage in "Automated Analysis of Load Testing Results"
Searching again in http://academic.research.microsoft.com I have found that not only CMG papers have some discussions about anomaly detection/control charting subjects in the Systems Capacity Management field. Below are a few examples:
1. Automated Analysis of Load Testing Results , Zhen Ming Jiang published in Conference: International Symposium on Software Testing and Analysis - ISSTA , pp. 143-146, 2010
From Abstract of the paper: ".. This dissertation proposes
automated approaches to detect functional and performance
problems in a load test by mining the recorded load testing
data (execution logs and performance metrics).."
The paper has reference to three other ones (see below) related to the subject of this blog, I believe:
- I. A. Trubin and L. Merritt. Mainframe global and
workload level statistical exception detection system,
based on masf. In 2004 CMG Conference, 2004
Here is the content where my paper was referenced:
"... It is di cult for humans to interpret raw performance
metrics, as it is not clear how to categorize these raw met-
ric values into performance categories (e.g. high, medium
and low). Furthermore, some data mining algorithms (e.g.
Navie Bayes Classi er) only take discrete values as input.
We are currently exploring generic approaches to classify
performance metrics into discrete performance categories us-
ing techniques like control charts [Trubin's CMG'04 paper] to facilitate our future
work in performance analysis...."
BTW Here is a slide with MIPS control chart from that paper presentation:
2. L. Cherkasova, K. Ozonat, N. Mi, J. Symons, and
E. Smirni. Anomaly? application change? or workload
change? towards automated detection of application
performance anomaly and change. In IEEE
International Conference on Dependable Systems and
2. B. Anton, M. Leonardo, and P. Fabrizio. Ava:
Automated interpretation of dynamically detected
anomalies. In Proceedings of the Eighteenth
International Symposium on Software Testing and
I plan to find and read the last two papers and maybe to report something here....