Hardware Reference
In-Depth Information
we made in order to test the model and discusses the results we obtained. Finally, we
present the conclusions in Section 5.
2 Optimum Measures Set Decision (OMSD) Model
The Optimum Measures Set Decision (OMSD) Model [14], which is extending the
GQM approach, is based on a heuristics approach. Heuristics is defined as a technique
which seeks near optimal solution at a reasonable cost [15]. It is a rather flexible, easy
to understand and implement technique. Constraints [16] regarding the costs and
resources are defined early in the measurement process and it plays an important role
during the final decision making on an optimum measures set selection. These con-
straints act as thresholds which are utilized as process terminators in OMSD Model.
The constraints for the heuristics rules are collected after the first level of GQM is
implemented; i.e. when the goals are identified. After implementing levels in GQM,
all the measures decided are ensured to be collected for a purpose and hence also
reflect interesting and useful measurements for an organization. OMSD consists of
five main steps shown as follows (Fig. 1 below):
•
Category Selection
•
Attributes Identification
•
Measures Selection
•
Collecting Data on the Measures Based on Factors
•
Decision Making
2.1 Category Selection
In order to perform any measurement activity we need to identify the entity to be
measured and the associated attributes [17]. This step involves mapping of the
questions identified in the questions level of GQM paradigm on their respective entity
categories. In [17], three main categories of entities are defined as: Process, Product
and Resource.
Process category includes different activities and these activities are associated
with a timescale. There is a particular order defined for these activities which means
activity B requires the completion of activity A. This timing could be implicit or
explicit. Resources and Product categories are associated with the process category.
Every process has certain resources and products that it utilizes. This step results in
the identification of measurement entities (questions) on their respective classes
which serves as input to the next phase of 'Attribute Identification'.
2.2 Attribute Identification
Attributes associated with the entities are identified that can be divided into two main
categories as external and internal attributes [17]. Internal attributes are those which
could be measured only by observing the product. External attributes include proc-
esses, products, resources and its behavior which tells how these attributes relate to
the environment. Category selection and attributes identification provide deep under-
standing regarding behavior of the respective questions.
