DocumentCode :
1824060
Title :
A metric to predict software scalability
Author :
Weyuker, Elaine J. ; Avritzer, Alberto
Author_Institution :
AT&T Labs - Res., Florham Park, NJ, USA
fYear :
2002
fDate :
2002
Firstpage :
152
Lastpage :
158
Abstract :
Software system scalability is an important issue for most businesses. It is essential that as the customer base increases, and therefore the system has to deal with significantly increased loads, the system is prepared to handle the increased traffic so that the users do not encounter unacceptable system performance. For this reason we introduce a new metric, the PNL metric, that can be used to predict the likely loads at which the probability of performance problems will exceed acceptable levels. A case study is described that demonstrates the application of the PNL metric to a large industrial software system. A description of the steps taken to model the software and collect data is provided, as well as the computation of the PNL metric and implications derived from the computation for this system. This information was used by the project to help plan for additional capacity so that the performance experienced by customers was likely to remain acceptable.
Keywords :
business data processing; software metrics; software performance evaluation; PNL metric; performance nonscalability likelihood metric; scalability; software load; software performance prediction; Capacity planning; Instruments; Management training; Predictive models; Production systems; Scalability; Software performance; Software systems; Software testing; System performance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Metrics, 2002. Proceedings. Eighth IEEE Symposium on
ISSN :
1530-1435
Print_ISBN :
0-7695-1339-5
Type :
conf
DOI :
10.1109/METRIC.2002.1011334
Filename :
1011334
Link To Document :
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