eprintid: 13381
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/33/81
datestamp: 2023-11-10 03:27:56
lastmod: 2023-11-10 03:27:56
status_changed: 2023-11-10 01:51:01
type: article
metadata_visibility: show
creators_name: Hassan, I.
creators_name: Latif, A.
creators_name: Khan, K.
creators_name: Hassan, F.
creators_name: Saeed, M.
title: Accurate cost estimation for software with volatile requirements
ispublished: pub
note: cited By 0
abstract: Requirements volatility in the software development lifecycle is considered to be one of the biggest risks during development. Countering this is mandatory in order to achieve success in a software project. Such requirements if they exist and not handled at an appropriate time can also result in a huge amount of error in estimation, whether it relates to cost or time. This paper first provides a clear understanding of requirements volatility along with its major contributors. The paper then mentions some widely-used techniques to achieve maximum accuracy in software costing. In section 4, the paper highlights how costing accuracy can be achieved if the software has volatile requirements by measuring an existing survey's result costing impact on the project. Finally, the paper concludes that volatile requirements cannot be eliminated but can be minimized using the approaches mentioned in the paper. © 2020 The Authors.
date: 2020
publisher: Institute of Advanced Science Extension (IASE)
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150496109&doi=10.21833%2fijaas.2020.03.001&partnerID=40&md5=481375741b42e13bc67d0e02084b38a0
id_number: 10.21833/ijaas.2020.03.001
full_text_status: none
publication: International Journal of Advanced and Applied Sciences
volume: 7
number: 3
pagerange: 1-8
refereed: TRUE
issn: 2313626X
citation:   Hassan, I. and Latif, A. and Khan, K. and Hassan, F. and Saeed, M.  (2020) Accurate cost estimation for software with volatile requirements.  International Journal of Advanced and Applied Sciences, 7 (3).  pp. 1-8.  ISSN 2313626X