AI4FM / 2014

A satellite workshop of FM 2014, Singapore, 13th May 2014

13th May 2014, Singapore

In association with FM 2014.

Previous Events


This workshop will bring together researchers from formal methods and AI; it will address the issue of how AI can be used to support the formal software development process, including modelling and proof. Previous AI4FM workshops have included a mix of industrial and academic participants and we anticipate attracting a similarly diverse audience.

Industrial use of formal methods is certainly increasing but, in order to make it more mainstream, the cost of applying formal methods, in terms of mathematical skill level and development time, must be reduced — we believe that AI can help with these issues.

Rigorous software development using formal methods allows the construction of an accurate characterisation of a problem domain that is firmly based on mathematics; by applying standard mathematical analyses, these methods can be used to prove that systems satisfy formal specifications. A recent paper in ACM Computing Surveys describes over sixty industrial projects and discusses the effect formal methods have on time, cost and quality. It shows that with tools backed by mature theory, formal methods are becoming cost effective and their use is easier to justify, not as an academic exercise or legal requirement, but as part of a business case. Furthermore, the use of such formal methods is no longer confined to safety critical systems: the list of industrial partners in the EU-funded DEPLOY project is one indication of this broader use. Most methods tend to fit a “posit-and-prove” paradigm where the user posits a development step (expressed in terms of specifications of yet-to-be-realised components) that has to be justified by proofs. The associated properties that must be verified are often called proof obligations (POs) or verification conditions. In most cases, such proofs require mechanical support by theorem provers.

One can distinguish between automatic and interactive provers, where the latter are generally more expressive but require user interaction. AI has had a large impact on the development of provers. In fact, some of the first AI applications were in theorem proving and all theorem provers now contain heuristics to reduce the search space that can be attributed to AI. Nevertheless, theorem proving research and (pure) AI research have diverged and theorem proving is barely considered to be AI-related anymore.

The aim of this workshop is to close this gap by bringing together expert users and developers of theorem provers, formal methods and artificial intelligence. Particular areas of interest include, but are not limited to:

  • The use of machine learning to support interactive theorem proving;
  • The use of machine learning to enhance automated theorem proving;
  • The development of search heuristics;
  • The use of AI for term synthesis, invariant generation, lemma discovery and concept invention;
  • The use of AI for counter-example generation;
  • The use of AI to support and guide the formal modelling process;
  • The role of AI planning for formal systems developments, from requirements to the end product (including software and hardware);
  • The interplay between reasoning and modelling and the role of AI in this framework;
  • Ontologies in the formal engineering process;
  • The use of AI to reuse formal models, programs and proofs.


  • Leo Freitas (Newcastle University, UK)
  • Gudmund Grov (Heriot-Watt University, UK)
  • Iain Whiteside (University of Edinburgh, UK)