Indirect variation. We consider this type as a point out of quality attributes due to the relationship with functional variability too. - Impacts: Functional or quality variability can indirectly cause variation in the quality or functional requirements. Taking into account the three vertices of variability, several requirements, considered important for modelling quality attribute variability, are described below: • Modelling and automatic reasoning: To provide a way to represent quality attribute variability in order to analyze and reason about the model. Because if so interesting information is captured, it is very reasonable to use it when deriving or taking other type of decisions. Different reasoning tasks should be interesting: get an approximate value or level for several quality attribute starting from a set of functional requirements, detect impossible configurations starting from a set of functional and quality requirements, detect conflicts among qualities and provide help to performance a trade off analysis... Due to the complexity of this analysis and reasoning, it is very advisable to make it automatic. To achieve automatic reasoning artificial intelligence techniques are need. Three well known problems in the area of automated reasoning are Constraint Satisfaction Problems (CSP), Boolean Satisfiability Problems (SAT) and Binary Decision Diagrams (BDD) [37]. • Quality attribute characterization: Quality attributes have vague definitions. In different domains, one quality attribute may not mean exactly the same or different names are used for the same concept. So it is necessary to concretize and make quality attributes more specific. A mechanism for describing and explaining a quality attribute adequately must be provided: A structure where a quality attribute may be explained through refinement among different levels. • Optionality: In one product one attribute may be important and in another this attribute not be required. So this attribute is optional in the product line. This may happen at quality attribute level but also at lower level, in the refinements of this quality attribute. For instance, in a quality attribute (performance) that is decomposed into two concerns (“Data latency” and “Transaction throughput”). Those concerns can also be optional or variant. This variability must be represented and not only at product level. It is not enough with specifying this optionality when deriving products.
