Your browser doesn't support javascript.
loading
Statistical analysis of software development models by six-pointed star framework.
Alam, Intakhab; Sarwar, Nadeem; Noreen, Iram.
Afiliación
  • Alam I; Department of Computer Science, Bahria University, Lahore, Pakistan.
  • Sarwar N; Department of Computer Science, Bahria University, Lahore, Pakistan.
  • Noreen I; Department of Computer Science, Bahria University, Lahore, Pakistan.
PLoS One ; 17(4): e0264420, 2022.
Article en En | MEDLINE | ID: mdl-35363771
Software Development Process Model (SDPM) develops software according to the needs of the client within the defined budget and time. There are many software development models such as waterfall, Iterative, Rapid Application Development (RAD), Spiral, Agile, Z, and AZ model. Each development model follows a series of steps to develop a product. Each model has its strengths and weaknesses. In this study, we have investigated different software development process models using the six-pointed star framework. Six-point star is a framework of project management industry standards maintained by Project Management Body of Knowledge (PMBOK). A survey is designed to evaluate the performance of well-known software process models in the context of factors defined by the six-point star framework. The survey is conducted with experienced users of the software industry. The statistical analysis and comparison of results obtained by the survey are further used to examine the effectiveness of each model for the development of high-quality software concerning lightweight and heavyweight methodologies for small, medium and large scale projects. After exploring the results of all factors of the six-pointed star model, we conclude that lightweight methodology easily handles small-scale projects. The heavyweight methodology is suitable for medium and large-scale projects, whereas the AZ model, which is one of the latest models, works efficiently with both small-scale and large-scale categories of projects.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Industrias Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: Pakistán

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Industrias Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: Pakistán