Early Performance Modeling for Web Based Applications

Geetha, D. Evangelin; Kumar, T. V. Suresh; Kanth, K. Rajani

doi:10.1007/978-3-540-30561-3_41

Cited by 8 publications

(8 citation statements)

References 9 publications

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“…The first step derives automatically a UML model with concrete performance annotations using MARTE profile for a specific product from a SPL model with generic performance annotations. The second step transforms the model obtained in the first step into a performance model by using Performance by Unified Model Analysis (PUMA) [49], model transformation approach. Even though several of these approaches have been successfully applied, still there is a gap in integrating the software performance prediction process into the SDLC.…”

Section: Related Workmentioning

confidence: 99%

Framework for hybrid performance prediction process model

Geetha

Kumar

Kanth

2011

SIGSOFT Softw. Eng. Notes

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The dynamic behavior of distributed systems requires that their performance characteristics be determined rigorously, preferably in the early stages of software engineering process. Evaluation of the performance at the end of software development leads to increase in the cost of design change. To compare design alternatives or to identify system bottlenecks, quantitative system analysis must be carried out from the early stages of the software development life cycle. In this paper we describe a process model, Hybrid Performance Prediction Process Model that allows modeling and evaluating distributed systems with the explicit goal of assessing performance of the software system during feasibility study. The use case performance engineering approach proposed in this paper exploits use case model and provides flexibility to integrate the software performance prediction process with software engineering process. We use an e-parking application to demonstrate various elements in our framework. The performance metrics are obtained and analyzed by considering two software architectures. Sensitivity analysis on the behavior of resources is carried out. This analysis helps to determine the capacity of the execution environment to obtain the defined performance objectives.

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Section: Related Workmentioning

confidence: 99%

Framework for hybrid performance prediction process model

Geetha

Kumar

Kanth

2011

SIGSOFT Softw. Eng. Notes

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“…Performance analysis using different diagrams of (UML) widely discussed in [7], [8], [9], [10], [11], [18]. The use of SPE during software architectural design phase is discussed in [4], [9], [14], [16], [17]. Performance evaluation in the early phase using queuing network models is discussed in [16], [18].…”

Section: Introductionmentioning

confidence: 99%

“…Performance analysis of Internet based software retrieval systems using petrinets and a comparative study proposed in [13]. Performance analysis using different diagrams of (UML) widely discussed in [7], [8], [9], [10], [11], [18]. The use of SPE during software architectural design phase is discussed in [4], [9], [14], [16], [17].…”

Section: Introductionmentioning

confidence: 99%

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Predicting performance of software systems during feasibility study of software project management

Geetha

Kumar

Kanth

2007

2007 6th International Conference on Information, Communications &Amp; Signal Processing

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Software performance is an important nonfunctional attribute of software systems for producing quality software. Performance issues must be considered throughout software project development. Predicting performance early in the life cycle is addressed by many methodologies, but the data collected during feasibility study not considered for predicting performance. In this paper, we consider the data collected (technical and environmental factors) during feasibility study of software project management to predict performance. We derive an algorithm to predict the performance metrics and simulate the results using a case study on banking application.

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“…In [11,12] estimating costs for agent oriented software is discussed. Few authors Addressed the performance issues early in SDLC [5], [6], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Predicting Performance of Multi-Agent systems during feasibility study

Ajitha¹,

Kumar²,

Geetha³

et al. 2009

2009 International Conference on Intelligent Agent &Amp; Multi-Agent Systems

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Agent Oriented software engineering (AOSE) is a software paradigm that has grasped the attention of researchers/developers for the last few years. As a result, many different methods have been introduced to enable researchers/developers to develop multi agent systems. However Performance, a non-functional attribute have not been given that much importance for producing quality software. Performance issues must be considered throughout software project development. Predicting performance early in the life cycle during feasibility study is not considered for predicting performance. In this paper, we consider the data collected (technical and environmental factors) during feasibility study of Multi-Agent software development to predict performance. We derive an algorithm to predict the performance metrics and simulate the results using a case study on scheduling the use of runways on an airport.

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Early Performance Modeling for Web Based Applications

Cited by 8 publications

References 9 publications

Framework for hybrid performance prediction process model

Framework for hybrid performance prediction process model

Predicting performance of software systems during feasibility study of software project management

Predicting Performance of Multi-Agent systems during feasibility study

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