Discovery of Invariants through Automated Theory Formation
Llano, Maria Teresa, Ireland, Andrew, Pease, Alison
–arXiv.org Artificial Intelligence
Refinement is a powerful mechanism for mastering the complexities that arise when formally modelling systems. Refinement also brings with it additional proof obligations -- requiring a developer to discover properties relating to their design decisions. With the goal of reducing this burden, we have investigated how a general purpose theory formation tool, HR, can be used to automate the discovery of such properties within the context of Event-B. Here we develop a heuristic approach to the automatic discovery of invariants and report upon a series of experiments that we undertook in order to evaluate our approach. The set of heuristics developed provides systematic guidance in tailoring HR for a given Event-B development. These heuristics are based upon proof-failure analysis, and have given rise to some promising results.
arXiv.org Artificial Intelligence
Jun-21-2011
- Country:
- North America > United States
- California > San Francisco County > San Francisco (0.04)
- Europe
- Ireland (0.06)
- United Kingdom > England
- Cambridgeshire > Cambridge (0.04)
- Poland > Podlaskie Province
- Bialystok (0.04)
- North America > United States
- Genre:
- Research Report (0.82)
- Technology: