Database Reference
In-Depth Information
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Methods and techniques have not been characterized and classifi ed beyond the typi-
cal division into structured, real-time and object-oriented methods and techniques,
although the particularities (prescribed process, models used, stakeholders involved,
etc.) of each individual method and technique are usually well known. Some papers
that attempt to undertake a classifi cation are Webster (1988), Zave (1990) and Firth,
Pethia, Roberts, Mosley and Dolce (1987). However, these papers do not agree on
either the classifi cation criteria or the methods and techniques considered, which
means that they are only partially useful. There being no satisfactory classifi cation, it
is enormously diffi cult to identify the fi tness of methods and techniques to problems,
as each method and technique has to be worked on individually, which is not very
systematic, diffi cult to extrapolate and very costly in terms of time and effort. There
is no categorization and classifi cation of problems. This means that the problem do-
main aspects that are relevant for examining fi tness are not known (Glass & Vessey,
1995).
Because of the above-mentioned diffi culties, that is, the absence of satisfactory cata-
logues of methods and techniques and of problems, it is far from easy to identify criteria of
correspondence that can be used to relate methods and techniques to problem domains. With
some simplifi cations, however, it is possible to come up with a strategy that can be used to
establish the correspondence between methods and techniques and problems. The strategy
proposed here has been formalized as a method for calculating method and technique fi tness,
as discussed in the following section.
PROPOSAL FOR DETERMINING
METHOD AND TECHNIQUE FITNESS
Due to the diffi culties discussed in the preceding section, some simplifi cations need to be
made with regard to how to establish a correspondence between a set P of problems and a set
M of methods and techniques. These simplifi cations, as shown in Figure 2, are as follows:
1. Rather than working on the set M, opt to use the set of conceptual models (CM) used
by the methods and techniques in set M. This means that much fewer elements need to
be considered, as many of the methods and techniques use the same, or very similar,
conceptual models, which means that the number of elements is smaller in set CM
than in set M (Dieste, Moreno & López, 1999).
2. Identify the fundamental elements of the problems belonging to P. Fundamental ele-
ments should be taken to mean the aspects that characterize each problem, that is,
partially or totally differentiate one problem from another. To identify the fundamental
elements of a problem, the problem needs to be examined and understood or, in other
words, modeled. Ordinary modeling is no good, however. Indeed, we would be going
around in circles, as explained later on, if we used the classical conceptual models,
like the data fl ow diagram, the class diagram or the state transition diagram to model
a problem P. Therefore, we need a new model type, which has been termed generic
conceptual model and which can model the problem without overlooking any of its
characteristics or forcing it to fi t any particular conceptual model. Using the generic
conceptual model, the problems in P can be mapped to a set of models of P (PM).
