ML Dependency Analysis for Assessors

François Pessaux (1) , Vincent Benayoun (2) , Catherine Dubois (3, 4, 2) , Philippe Ayrault (5)

1 SFL - Sûreté et Fiabilité des Logiciels
2 CEDRIC - Centre d'études et de recherche en informatique et communications
3 DEDUCTEAM - Deduction modulo, interopérabilité et démonstration automatique
4 ENSIIE - Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise
5 SPI - Sémantiques, preuves et implantation

Critical software needs to obtain an assessment before com- missioning. This assessment is given after a long task of software analysis performed by assessors. They may be helped by tools, used interactively, to build models using information-flow analysis. Tools like SPARK-Ada exist for Ada subsets used for critical software. But some emergent lan- guages such as those of the ML family lack such adapted tools. Pro- viding similar tools for ML languages requires special attention on spe- cific features such as higher-order functions and pattern-matching. This paper presents an information-flow analysis for such a language specifi- cally designed according to the needs of assessors. This analysis can be parametrized to allow assessors getting a view of dependencies at several levels of abstraction and gives the basis for an efficient fault tolerance analysis.

Domaines: Langage de programmation [cs.PL]

François Pessaux, Vincent Benayoun, Catherine Dubois, Philippe Ayrault. ML Dependency Analysis for Assessors. Software Engineering and Formal Methods (SEFM) 2012, Oct 2012, Thessaloniki, Greece. pp.278-292, ⟨10.1007/978-3-642-33826-7_19⟩. ⟨hal-01203505⟩