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Empirical Study of an Improved Component Based Software Development Model using Expert Opinion Technique
Author(s) -
Asif Irshad Khan,
Md. Mottahir Alam,
Noor-ul- Qayyum
Publication year - 2013
Publication title -
international journal of information technology and computer science
Language(s) - English
Resource type - Journals
eISSN - 2074-9015
pISSN - 2074-9007
DOI - 10.5815/ijitcs.2013.08.01
Subject(s) - computer science , component (thermodynamics) , expert opinion , software engineering , software , software development , empirical research , artificial intelligence , machine learning , programming language , statistics , physics , thermodynamics , medicine , mathematics , intensive care medicine
IT industry in the present market situation faces high demand for performance and burgeoning user expectations; with the pressure manifesting itself in three forms – Development Cost, Time-to-market and Product Quality. Researchers have proposed several techniques to effectively deal with these conflicting scenarios and draw optimized output. One of the relevant techniques in this context is Component Based Software Development (CBSD) with a targeted and discriminative approach influencing all phases of development. Although, CBSD proposes a multi-faceted approach in complex scenarios, its prime focus lies in “write once and reuse multiple times” methodology with either no or minor modifications. The model has been markedly successful in large enterprise applications with companies deriving benefits from shorter development time, increased productivity and better quality product. This research paper focuses and discusses Empirical Study of an Improved Component Based Software Development (ICBD) Model using Expert Opinion Technique which covers both component based software development as well as Component development phases. ICBD Model tries to overcome some of the issues in the contemporary CBD Models. A case study was conducted to investigate and evaluate our model by experienced professionals working in the IT industry. Results have shown that our improved model registers significant improvement over previous models suggested by other researchers

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