Abstract:

This paper sets out from the agentoriented software engineering paradigm, proposes an requirement analysis methodology integrating with agent, goal and scenario technology. In the proposed approach, system inputs are textual descriptions of the interactions between various agents within the system and the environment, annotated with informations on intended purpose of the scenarios. At the beginning stage of the proposed AOA method, original scenarios in SSDL are described by endusers. These scenarios are then transformed into an internal representation  ScenarioTree. Then an inductive learning procedure will be started, during which the scenario descriptions are decomposed, clustered, and generalised. The learning result is an abstract grammar  an attribute grammar. The attributes and attribute computing rules are used to reinforce the expressiveness of the grammar.

Key words: oftware agents;scenario;formal specification;inductive grammar learning