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Quantitative WinWin - a new method for decision support in requirements negotiation

Ruhe, Günther; Eberlein, Armin and Pfahl, Dietmar LU (2002) 14th international conference on Software engineering and knowledge engineering (2002) In [Host publication title missing] 27. p.159-166
Abstract
Defining, prioritizing, and selecting requirements are problems of tremendous importance. In this paper, a new approach called Quantitative WinWin for decision support in requirements negotiation is studied. The difference to Boehm's WinWin groupware-based negotiation support is the inclusion of quantitative methods as a backbone for better and more objective decisions. Like Boehm's original WinWin, Quantitative WinWin uses an iterative approach, with the aim to increase knowledge about the requirements during each iteration. The novelty of the presented idea is three-fold. Firstly, it uses the Analytical Hierarchy Process for a stepwise determination of the stakeholders' preferences in quantitative terms. Secondly, these results are... (More)
Defining, prioritizing, and selecting requirements are problems of tremendous importance. In this paper, a new approach called Quantitative WinWin for decision support in requirements negotiation is studied. The difference to Boehm's WinWin groupware-based negotiation support is the inclusion of quantitative methods as a backbone for better and more objective decisions. Like Boehm's original WinWin, Quantitative WinWin uses an iterative approach, with the aim to increase knowledge about the requirements during each iteration. The novelty of the presented idea is three-fold. Firstly, it uses the Analytical Hierarchy Process for a stepwise determination of the stakeholders' preferences in quantitative terms. Secondly, these results are combined with methods for early effort estimation, in our case using the simulation prototype GENSIM, to evaluate the feasibility of alternative requirements subsets in terms of their related implementation efforts. Thirdly, it reflects the increasing knowledge gained about the requirements during each iteration, in a similar way as it is done in Boehm's spiral model for software development. As main result, quantitative WinWin offers decision support for selecting the most appropriate requirements based on the preferences of the stakeholders, the business value of requirements and a given maximum development effort. Copyright 2002 ACM. (Less)
Please use this url to cite or link to this publication:
author
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Software design, Decision support systems, Estimation, decision support, requirements negotiation, Knowledge engineering, quantitative methods, effort estimation, easy winwin, analytical hierarchy process, simulation, Quantitative method, Win-win, Computer software selection and evaluation
in
[Host publication title missing]
volume
27
pages
159 - 166
publisher
ACM
conference name
14th international conference on Software engineering and knowledge engineering (2002)
external identifiers
  • scopus:34250214043
ISBN
1-58113-556-4
DOI
10.1145/568760.568789
language
English
LU publication?
no
id
c8947f00-8d47-4151-89cb-b3465f4eab94 (old id 1662690)
date added to LUP
2010-10-12 14:00:58
date last changed
2017-07-23 05:06:09
@inproceedings{c8947f00-8d47-4151-89cb-b3465f4eab94,
  abstract     = {Defining, prioritizing, and selecting requirements are problems of tremendous importance. In this paper, a new approach called Quantitative WinWin for decision support in requirements negotiation is studied. The difference to Boehm's WinWin groupware-based negotiation support is the inclusion of quantitative methods as a backbone for better and more objective decisions. Like Boehm's original WinWin, Quantitative WinWin uses an iterative approach, with the aim to increase knowledge about the requirements during each iteration. The novelty of the presented idea is three-fold. Firstly, it uses the Analytical Hierarchy Process for a stepwise determination of the stakeholders' preferences in quantitative terms. Secondly, these results are combined with methods for early effort estimation, in our case using the simulation prototype GENSIM, to evaluate the feasibility of alternative requirements subsets in terms of their related implementation efforts. Thirdly, it reflects the increasing knowledge gained about the requirements during each iteration, in a similar way as it is done in Boehm's spiral model for software development. As main result, quantitative WinWin offers decision support for selecting the most appropriate requirements based on the preferences of the stakeholders, the business value of requirements and a given maximum development effort. Copyright 2002 ACM.},
  author       = {Ruhe, Günther and Eberlein, Armin and Pfahl, Dietmar},
  booktitle    = {[Host publication title missing]},
  isbn         = {1-58113-556-4},
  keyword      = {Software design,Decision support systems,Estimation,decision support,requirements negotiation,Knowledge engineering,quantitative methods,effort estimation,easy winwin,analytical hierarchy process,simulation,Quantitative method,Win-win,Computer software selection and evaluation},
  language     = {eng},
  pages        = {159--166},
  publisher    = {ACM},
  title        = {Quantitative WinWin - a new method for decision support in requirements negotiation},
  url          = {http://dx.doi.org/10.1145/568760.568789},
  volume       = {27},
  year         = {2002},
}