KAOS is one of the most well-known goal-oriented requirements engineering approaches. Nevertheless, building large KAOS models sometimes results in incomplete and/or complex requirements models that are difficult to understand and maintain. These shortcomings often lead to an increase in costs of product development and evolution. Therefore, for large-scale systems, the ability to manage the complexity and completeness of KAOS models is essential. In this paper, we propose a metrics suite for supporting the quantitative assessment of KAOS models complexity and completeness, in order to support their early identification. We apply the metrics to an example taken from a health club system specification.
|Title of host publication||International Workshop on Empirical Requirements Engineering (EmpiRE)|
|Pages||29 - 32|
|Publication status||Published - 1 Jan 2011|
|Event||International Workshop on Empirical Requirements Engineering (EmpiRE 2011) - |
Duration: 1 Jan 2011 → …
|Conference||International Workshop on Empirical Requirements Engineering (EmpiRE 2011)|
|Period||1/01/11 → …|