DocumentCode :
1496691
Title :
Predicting the software performance during feasibility study
Author :
Evangelin Geetha, D. ; Suresh Kumar, T.V. ; Rajani Kanth, K.
Author_Institution :
M.S. Ramaiah Inst. of Technol., Bangalore, India
Volume :
5
Issue :
2
fYear :
2011
fDate :
4/1/2011 12:00:00 AM
Firstpage :
201
Lastpage :
215
Abstract :
Performance is an important non-functional attribute to be considered for producing quality software. Software performance engineering (SPE) is a methodology having significant role in software engineering to assess the performance of software systems early in the lifecycle. Gathering performance data is an essential aspect of SPE approach. The authors have proposed a methodology to gather data during feasibility study by exploiting the use case point approach, gearing factor and COCOMO model. The proposed methodology is used to estimate the performance data required for performance assessment in the integrated performance prediction process (IP3) model. The gathered data is used as the input for solving the two models, (i) use case performance model and (ii) system model. The methodology is illustrated with a case study of airline reservation application. A regression analysis is carried out to validate the response time obtained in the use case performance model. The analysis shows the proposed estimation can be used along with performance walkthrough in data gathering. The performance metrics are obtained by solving the system model, and the behaviour of the hardware resources is observed. Bottleneck resources are identified and the performance parameters are optimised using sensitivity analysis.
Keywords :
data handling; regression analysis; sensitivity analysis; software performance evaluation; COCOMO model; airline reservation application; case performance model; data gathering; gearing factor; integrated performance prediction process model; regression analysis; sensitivity analysis; software performance; software performance engineering; system model;
fLanguage :
English
Journal_Title :
Software, IET
Publisher :
iet
ISSN :
1751-8806
Type :
jour
DOI :
10.1049/iet-sen.2010.0075
Filename :
5751770
Link To Document :
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