Lightweight analysis of operational specifications using inference graphs

  • Authors:

  • Laura K. Dillon;R. E. Kurt Stirewalt

  • Affiliations:

  • Department of Computer Science and Engineering, Michigan State University, East Lansing, MI;Department of Computer Science and Engineering, Michigan State University, East Lansing, MI

  • Venue:
  • ICSE '01 Proceedings of the 23rd International Conference on Software Engineering
  • Year:
  • 2001

Quantified Score

Hi-index 0.00

Visualization

Abstract

The Amalia framework generates lightweight components that automate the analysis of operational specifications and designs [16]. A key concept is the step analyzer, which enables Amalia to automatically tailor high-level analyses, such as behavior simulation and model checking, to different specification languages and representations. A step analyzer uses a new abstraction, called an inference graph, for the analysis. It creates and evaluates an inference graph on-the-fly during a top-down traversal of a specification to deduce the specification's local behaviors (called steps). The nodes of an inference graph directly reify the rules in an operational semantics, enabling Amalia to automatically generate a step analyzer from an operational description of a notation's semantics. Inference graphs are a clean abstraction that can be formally defined. The paper provides a detailed, but informal, introduction to inference graphs. It uses example specifications written in LOTOS for purposes of illustration.