English

Discovery of Invariants through Automated Theory Formation

Logic in Computer Science 2011-06-22 v1 Artificial Intelligence Software Engineering

Abstract

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.

Keywords

Cite

@article{arxiv.1106.4090,
  title  = {Discovery of Invariants through Automated Theory Formation},
  author = {Maria Teresa Llano and Andrew Ireland and Alison Pease},
  journal= {arXiv preprint arXiv:1106.4090},
  year   = {2011}
}

Comments

In Proceedings Refine 2011, arXiv:1106.3488