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Modeling and Selection of Interdependent Software Requirements Using Fuzzy Graphs

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Abstract

Software requirement selection is to find an optimal set of requirements that gives the highest value for a release of software while keeping the cost within the budget. However, value-related dependencies among software requirements may impact the value of an optimal set. Moreover, value-related dependencies can be of varying strengths. Hence, it is important to consider both the existence and the strengths of value-related dependencies during a requirement selection. The existing selection models, however, either assume that software requirements are independent or they ignore strengths of requirement dependencies. This paper presents a cost-value optimization model that considers the impacts of value-related requirement dependencies on the value of selected requirements (optimal set). We have exploited algebraic structure of fuzzy graphs for modeling value-related requirement dependencies and their strengths. Validity and practicality of the work are verified through carrying out several simulations and studying a real world software project.

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Abbreviations

NRP:

Next release problem

BKP:

Binary knapsack problem

AV:

Accumulated value

EV:

Estimated value

CV:

Customer value

SDP:

Selection deficiency problem

OV:

Overall value

GORS:

Graph-oriented requirement selection

FRIG:

Fuzzy requirement interdependency graph

LOI:

Level of interdependency

RAN:

Radio access network

PMR:

Performance management traffic recording

PMS:

Precious messaging system

R :

Set of requirements

\(r_i\) :

Requirement \(r_i \in R\)

\(v_i\) :

Estimated value of \(r_i\)

\(c_i\) :

Estimated cost of \(r_i\)

b :

Available budget

\(x_i\) :

Selection variable (\(ri_2 \in R\) is selected or not)

D :

Set of explicit value-related dependencies

O :

Optimal set

\({{\tilde{O}}}\) :

Set of excluded requirements

G :

A fuzzy requirement interdependency graph

\(\mu\) :

Fuzzy membership function of requirements

\(\rho\) :

Fuzzy membership function of dependencies

\(\wedge\) :

Fuzzy AND operator

\(I_i\) :

Impact of excluded requirements on \(r_i\)

\(\vee\) :

Fuzzy OR operator

\(\eta\) :

Pearl’s measure of causal strength

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Funding

This research is supported by Australian Government Research Training Program Scholarship-International. Funding was provided by Flinders University.

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  1. College of Science and Engineering, Flinders University, Adelaide, Australia

    Davoud Mougouei & David M. W. Powers

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  1. Davoud Mougouei
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Correspondence to Davoud Mougouei.

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Mougouei, D., Powers, D.M.W. Modeling and Selection of Interdependent Software Requirements Using Fuzzy Graphs. Int. J. Fuzzy Syst. 19, 1812–1828 (2017). https://doi.org/10.1007/s40815-017-0364-4

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