2010
DOI: 10.1007/s11590-010-0243-5
View full text |Buy / Rent full text
|
Sign up to set email alerts
|

Abstract: In this paper, we introduce fuzzy mathematical programming (FMP) for decision-making related to software creation by selecting optimal commercial-off-theshelf (COTS) products in a modular software system. Each module in such software systems have different alternatives with variations in their properties, for example, quality, reliability, execution time, size and cost. Due to these variations, componentbased software developers generally deals with the problem of selecting appropriate COTS products. The devel… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
22
0

Year Published

2015
2015
2017
2017

Publication Types

Select...
3

Relationship

1
2

Authors

Journals

citations
Cited by 24 publications
(22 citation statements)
references
References 25 publications
(31 reference statements)
0
22
0
Order By: Relevance
“…COTS are defined as the software pieces that can be further reused by the software developers to build the new software systems (Firesmith, 2005;Vigder et al, 1996). Gupta et al (2012) described the COTS products that are available for purchase, lease or license to the general public. The COTS products are ready made and can be used by the software developers "as it is" and can be easily installed and incorporated with the existing system components.…”
Section: Fig 1 Cots-based Software Development Processmentioning
confidence: 99%
“…COTS are defined as the software pieces that can be further reused by the software developers to build the new software systems (Firesmith, 2005;Vigder et al, 1996). Gupta et al (2012) described the COTS products that are available for purchase, lease or license to the general public. The COTS products are ready made and can be used by the software developers "as it is" and can be easily installed and incorporated with the existing system components.…”
Section: Fig 1 Cots-based Software Development Processmentioning
confidence: 99%
“…Ibrahim et al (2011) proposed a hybrid model UnHOS (Uncertainty Handling in COTS Selection) by combining AHP and BBN followed by the sensitivity analysis to solve the COTS component selection problem. Gupta et al (2012) introduced fuzzy mathematical programming (FMP) for the COTS component evaluation and selection. Ravichandran et al (2012) adopted Neuro-fuzzy approach and presented an effective methodology ANFIS for the selection and evaluation of COTS components.…”
Section: Literature Reviewmentioning
confidence: 99%
“…The existing COTS products selection models under a fuzzy environment, for example, Bali et al [1], Gupta et al [8], Gupta et al [10], Jha et al [14] and Mehlawat and Gupta [25], are based on minimizing the distance from the PIS with respect to each goal or criterion; however, in real-world applications, it is desirable to consider deviations from both PIS and NIS for better decision making. This is the motivation to study the multiobjective COTS products selection problem using an approach that is based on a compromising principle whereby we not only minimize the distance from PIS but also maximize the distance from NIS.…”
Section: Shortcomings Of the Existing Approaches And Motivation For Tmentioning
confidence: 99%
“…Additionally, most of the parameters embedded in the COTS products selection problem are frequently vague/uncertain in nature because of the incompleteness or unavailability of required data over the planning horizon, and thus, these parameters can only be obtained subjectively. This motivate us to use fuzzy model parameters rather than the crisp model parameters used for COTS selection in the existing literature, for example, Gupta et al [8], Gupta et al [10], Jha et al [14], Jung and Choi [15] and Shen et al [31]. This is done to provide greater flexibility for treating different possible scenarios of input data uncertainty in the COTS selection problem.…”
Section: The Credibilistic Cots Selection Model Presented Inmentioning
confidence: 99%
See 1 more Smart Citation