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On Goal-based Variability Acquisition and Analysis

by: Sotirios Liaskos, Alexei Lapouchnian, Yijun Yu, Eric Yu, and John Mylopoulos

In: Intl. Conf. Req. Engineering (September 2006) .

Resources (URL, PDF, PS...)

URL:	http://www.cs.toronto.edu/~jaranda/draftpapers/VarInt.pdf

We introduce a variability-intensive approach to goal decomposition, which enables the identification of more complete requirements for customizable software. The approach is based on the semantic characterization of ORdecompositions of goals. We first show that each high-level goal can be associated with a set of concerns in response to which alternative refinements of the goal can be introduced. A text corpus relevant to the domain of discourse can be used to derive such variability concerns that are specific to the problem. In parallel, non-intentional background facts that can vary while a goal is being fulfilled are modeled. Then, a high-variability goal model is constructed aiming at responding to the predefined variability concerns completely, while non-intentional factors are used to test whether the result addresses all realistic background circumstances. We apply our approach in a study from the geriatric health care domain.

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BibTeX record

@inproceedings{liaskos06,
  abstract = {We introduce a variability-intensive approach to goal decomposition,
	which enables the identification of more complete requirements for
	customizable software. The approach is based on the semantic characterization
	of ORdecompositions of goals. We first show that each high-level
	goal can be associated with a set of concerns in response to which
	alternative refinements of the goal can be introduced. A text corpus
	relevant to the domain of discourse can be used to derive such variability
	concerns that are specific to the problem. In parallel, non-intentional
	background facts that can vary while a goal is being fulfilled are
	modeled. Then, a high-variability goal model is constructed aiming
	at responding to the predefined variability concerns completely,
	while non-intentional factors are used to test whether the result
	addresses all realistic background circumstances. We apply our approach
	in a study from the geriatric health care domain.},
  added-at = {2006-09-18T06:26:07.000+0200},
  author = {Liaskos, Sotirios and Lapouchnian, Alexei and Yu, Yijun and Yu, Eric and Mylopoulos, John},
  biburl = {http://www.bibsonomy.org/bibtex/2828365e255d8ef8a076d827bfc60a6d4/neilernst},
  booktitle = {Intl. Conf. Req. Engineering},
  citeulike-article-id = {738306},
  description = {Not previously uploaded},
  interhash = {c1531273cae02f80574cd1e419b60917},
  intrahash = {828365e255d8ef8a076d827bfc60a6d4},
  keywords = {goal variability},
  month = {September},
  priority = {0},
  timestamp = {2006-09-18T06:26:07.000+0200},
  title = {On Goal-based Variability Acquisition and Analysis},
  url = {http://www.cs.toronto.edu/~jaranda/draftpapers/VarInt.pdf},
  year = 2006
}

Endnote record

%0 Conference Paper
%1 liaskos06
%A Liaskos, Sotirios
%A Lapouchnian, Alexei
%A Yu, Yijun
%A Yu, Eric
%A Mylopoulos, John
%B Intl. Conf. Req. Engineering
%D 2006
%K 
%T On Goal-based Variability Acquisition and Analysis
%U http://www.cs.toronto.edu/~jaranda/draftpapers/VarInt.pdf
%X We introduce a variability-intensive approach to goal decomposition,
	which enables the identification of more complete requirements for
	customizable software. The approach is based on the semantic characterization
	of ORdecompositions of goals. We first show that each high-level
	goal can be associated with a set of concerns in response to which
	alternative refinements of the goal can be introduced. A text corpus
	relevant to the domain of discourse can be used to derive such variability
	concerns that are specific to the problem. In parallel, non-intentional
	background facts that can vary while a goal is being fulfilled are
	modeled. Then, a high-variability goal model is constructed aiming
	at responding to the predefined variability concerns completely,
	while non-intentional factors are used to test whether the result
	addresses all realistic background circumstances. We apply our approach
	in a study from the geriatric health care domain.