ASTRÉE is an abstract interpretation-based static program analyzer aiming at proving automatically the absence of run time errors in programs written in the C programming language. It has been applied with success to large embedded control-command safety critical realtime software generated automatically from synchronous specifications, producing a correctness proof for complex software without any false alarm in a few hours of computation. This work was supported in part by the French exploratory project ASTRÉE of the Réseau National de recherche et d'innovation en Technologies Logicielles (RNTL).

We show that abstract interpretation-based static program analysis can be made efficient and precise enough to formally verify a class of properties for a family of large programs with few or no false alarms. This is achieved by refinement of a general purpose static analyzer and later adaptation to particular programs of the family by the end-user through parametrization. This is applied to the proof of soundness of data manipulation operations at the machine level for periodic synchronous safety critical embedded software.The main novelties are the design principle of static analyzers by refinement and adaptation through parametrization (Sect. 3 and 7), the symbolic manipulation of expressions to improve the precision of abstract transfer functions (Sect. 6.3), the octagon (Sect. 6.2.2), ellipsoid (Sect. 6.2.3), and decision tree (Sect. 6.2.4) abstract domains, all with sound handling of rounding errors in floating point computations, widening strategies (with thresholds: Sect. 7.1.2, delayed: Sect. 7.1.3) and the automatic determination of the parameters (parametrized packing: Sect. 7.2).

We show that abstract interpretation-based static program analysis can be made efficient and precise enough to formally verify a class of properties for a family of large programs with few or no false alarms. This is achieved by refinement of a general purpose static analyzer and later adaptation to particular programs of the family by the end-user through parametrization. This is applied to the proof of soundness of data manipulation operations at the machine level for periodic synchronous safety critical embedded software.The main novelties are the design principle of static analyzers by refinement and adaptation through parametrization (Sect. 3 and 7), the symbolic manipulation of expressions to improve the precision of abstract transfer functions (Sect. 6.3), the octagon (Sect. 6.2.2), ellipsoid (Sect. 6.2.3), and decision tree (Sect. 6.2.4) abstract domains, all with sound handling of rounding errors in floating point computations, widening strategies (with thresholds: Sect. 7.1.2, delayed: Sect. 7.1.3) and the automatic determination of the parameters (parametrized packing: Sect. 7.2).

We show that abstract interpretation-based static program analysis can be made efficient and precise enough to formally verify a class of properties for a family of large programs with few or no false alarms. This is achieved by refinement of a general purpose static analyzer and later adaptation to particular programs of the family by the end-user through parametrization. This is applied to the proof of soundness of data manipulation operations at the machine level for periodic synchronous safety critical embedded software. The main novelties are the design principle of static an-alyzers by refinement and adaptation through parametriza-tion (Sect. 3 and 7), the symbolic manipulation of expressions to improve the precision of abstract transfer functions (Sect. 6.3), the octagon (Sect. 6.2.2), ellipsoid (Sect. 6.2.3), and decision tree (Sect. 6.2.4) abstract domains, all with sound handling of rounding errors in floating point computations , widening strategies (with thresholds: Sect. 7.1.2, delayed: Sect. 7.1.3) and the automatic determination of the parameters (parametrized packing: Sect. 7.2).

We report on a successful preliminary experience in the design and implementation of a special-purpose Abstract Interpretation based static program analyzer for the verification of safety critical embedded real-time software. The analyzer is both precise (zero false alarm in the considered experiment) and efficient (less than one minute of analysis for 10,000 lines of code). Even if it is based on a simple interval analysis, many features have been added to obtain the desired precision: expansion of small arrays, widening with several thresholds, loop unrolling, trace partitioning, relations between loop counters and other variables. The efficiency of the tool mainly comes from a clever representation of abstract environments based on balanced binary search trees.Nous rapportons sur une expérience préliminaire fructueuse sur la conceptionet l'implantation d'un analyseur statique de programmes, basé sur l'interprétation abstraite, pour la vérification de l'absence d'erreurs à l'exécution dans des logiciels critiques embarqués temps-réel. L'analyseur est à la fois précis (aucune fausse alarme dans l'expérimentation considérée) et efficace (moins d'une minute de temps d'analyse pour 10 000 lignes de code). Même s'il est basé sur une simple analyse d'intervalles, de nombreuses extensions à cette analyse classique ont été introduites pour obtenir de telles performances : expansion des petits tableaux, élargissements étagés, dépliages de boucles, partitionnement de traces, relation entre compteurs de boucle et autres variables. L'efficacité de l'outil vient d'une représentation astucieuse des environnements abstraits basée sur des applications fonctionnelles implantées par des arbres binaires de recherche équilibrés

Following earlier models, we lift standard deterministic and nondeterministic semantics of imperative programs to probabilistic semantics. This semantics allows for random external inputs of known or unknown probability and random number generators. We then propose a method of analysis of programs according to this semantics, in the general framework of abstract interpretation. This method lifts an "ordinary" abstract lattice, for non-probabilistic programs, to one suitable for probabilistic programs. Our construction is highly generic. We discuss the influence of certain parameters on the precision of the analysis, basing ourselves on experimental results.

Abstract. We describe the structure of the abstract domains in the Astrée static analyzer, their modular organization into a hierarchical network, their cooperation to over-approximate the conjunction/reduced product of different abstractions and to ensure termination using collaborative widenings and narrowings. This separation of the abstraction into a combination of cooperative abstract domains makes Astrée extensible, an essential feature to cope with false alarms and ultimately provide sound formal verification of the absence of runtime errors in very large software.

Current critical systems often use a lot of floating-point computations, and thus the testing or static analysis of programs containing floatingpoint operators has become a priority. However, correctly defining the semantics of common implementations of floating-point is tricky, because semantics may change according to many factors beyond source-code level, such as choices made by compilers. We here give concrete examples of problems that can appear and solutions for implementing in analysis software.