Improving the Component Discovery Process by Leveraging Automatic Sensitive Analysis

  • Romina Torres Universidad Técnica Federico Santa María
  • Hernán Astudillo Universidad Técnica Federico Santa María

Resumo


Component-based approaches have acquired a prominent role in development of complex software systems. Successful reuse of existing components requires being able to first identify, and then distinguish among, functionally (near-) equivalent elements of large component collections. Similar components can be ranked using quality criteria, thus, some goal-oriented techniques attempt to quantify components quality by indicating valid ranges for their properties and behavior, like stability, latency and so on. Unfortunately, most current techniques yield non-robust ranges, and most tools do not allow architects to observe the range selection during the process. This paper presents a technique for sensitivity analysis of components discovery, built over fuzzy sets. A prototypical tool has been built, and use of the technique and tool are illustrated with an example. This iterative approach allows evaluators to compare "what if" scenarios for alternative component quality criteria, supporting requirements evolution without continuous expert support to recalibrate valid property ranges.
Palavras-chave: Fuzzy sets, Web services, Proposals, Measurement, Pragmatics, Shape, discovery, fuzzy sets, sensitive analysis
Publicado
26/09/2011
TORRES, Romina; ASTUDILLO, Hernán. Improving the Component Discovery Process by Leveraging Automatic Sensitive Analysis. In: SIMPÓSIO BRASILEIRO DE COMPONENTES, ARQUITETURAS E REUTILIZAÇÃO DE SOFTWARE (SBCARS), 5. , 2011, São Paulo/SP. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2011 . p. 81-89.