Formal Methods (FMs) radically improve the quality of the code artefacts they help to produce. They are simple, probably accessible to first-year undergraduate students and certainly to second-year students and beyond. Nevertheless, in many cases, they are not part of a general recommendation for course curricula, i.e., they are not taught — and yet they are valuable. One reason for this is that teaching “Formal Methods” is often confused with teaching logic and theory. This article advocates what we call FM thinking : the application of ideas from Formal Methods applied in informal, lightweight, practical and accessible ways. We will argue here that FM thinking should be part of the recommended curriculum for every Computer Science student, for even students who train only in that “thinking” will become much better programmers. However, there will be others who, exposed to those ideas, will be ideally positioned to go further into the more theoretical background: why the techniques work, how they can be automated, and how new ones can be developed. Those students would follow subsequently a specialised, more theoretical stream, including topics such as semantics, logics, verification and proof-automation techniques.

Abstract We address automated testing and interactive proving of properties involving complex data structures with constraints, like the ones studied in enumerative combinatorics, e.g., permutations and maps. In this paper we show testing techniques to check properties of custom data generators for these structures. We focus on random property-based testing and bounded exhaustive testing, to find counterexamples for false conjectures in the Coq proof assistant. For random testing we rely on the existing Coq plugin QuickChick and its toolbox to write random generators. For bounded exhaustive testing, we use logic programming to generate all the data up to a given size. We also propose an extension of QuickChick with bounded exhaustive testing based on generators developed inside Coq, but also on correct-by-construction generators developed with Why3. These tools are applied to an original Coq formalization of the combinatorial structures of permutations and rooted maps, together with some operations on them and properties about them. Recursive generators are defined for each combinatorial family. They are used for debugging properties which are finally proved in Coq. This large case study is also a contribution in enumerative combinatorics.

In order to check requirement specifications written in natural language, we have chosen to model domain knowledge through an ontology and to formally represent user requirements by its population. Our approach of ontology population focuses on instance property identification from texts. We do so using extraction rules automatically acquired from a training corpus and a bootstrapping terminology. These rules aim at identifying instance property mentions represented by triples of terms, using lexical, syntactic and semantic levels of analysis. They are generated from recurrent syntactic paths between terms denoting instances of concepts and properties. We show how focusing on instance property identification allows us to precisely identify concept instances explicitly or implicitly mentioned in texts.

We present the extensional polymorphism, a framework to type check ad hoc polymorphic functions. This formalism is compatible with parametric polymorphism, and supports a large class of functions defined by structural pattern matching on types.