In this paper, we present SeaHorn, a software verification framework. The key distinguishing feature of SeaHorn is its modular design that separates the concerns of the syntax of the programming language, its operational semantics, and the verification semantics. Sea-Horn encompasses several novelties: it (a) encodes verification conditions using an efficient yet precise inter-procedural technique, (b) provides flexibility in the verification semantics to allow different levels of precision, (c) leverages the state-of-the-art in software model checking and abstract interpretation for verification, and (d) uses Horn-clauses as an intermediate language to represent verification conditions which simplifies interfacing with multiple verification tools based on Horn-clauses. SeaHorn provides users with a powerful verification tool and researchers with an extensible and customizable framework for experimenting with new software verification techniques. The effectiveness and scalability of SeaHorn are demonstrated by an extensive experimental evaluation using benchmarks from SV-COMP 2015 and real avionics code.

Abstract. We present a static analysis that infers both upper and lower bounds on the usage that a logic program makes of a set of user-definable resources. The inferred bounds will in general be functions of input data sizes. A resource in our approach is a quite general, user-defined notion which associates a basic cost function with elementary operations. The analysis then derives the related (upper-and lower-bound) resource usage functions for all predicates in the program. We also present an assertion language which is used to define both such resources and resourcerelated properties that the system can then check based on the results of the analysis. We have performed some preliminary experiments with some concrete resources such as execution steps, bytes sent or received by an application, number of files left open, number of accesses to a database, number of calls to a procedure, number of asserts/retracts, etc. Applications of our analysis include resource consumption verification and debugging (including for mobile code), resource control in parallel/distributed computing, and resource-oriented specialization.

Abstract. Static analyses of object-oriented programs usually rely on intermediate representations that respect the original semantics while having a more uniform and basic syntax. Most of the work involving object-oriented languages and abstract interpretation usually omits the description of that language or just refers to the Control Flow Graph (CFG) it represents. However, this lack of formalization on one hand results in an absence of assurances regarding the correctness of the transformation and on the other it typically strongly couples the analysis to the source language. In this work we present a framework for analysis of object-oriented languages in which in a first phase we transform the input program into a representation based on Horn clauses. This allows on one hand proving the transformation correct attending to a simple condition and on the other being able to apply an existing analyzer for (constraint) logic programming to automatically derive a safe approximation of the semantics of the original program. The approach is flexible in the sense that the first phase decouples the analyzer from most languagedependent features, and correct because the set of Horn clauses returned by the transformation phase safely approximates the standard semantics of the input program. The resulting analysis is also reasonably scalable due to the use of mature, modular (C)LP-based analyzers. The overall approach allows us to report results for medium-sized programs.

Abstract. We present TRACER, a verifier for safety properties of sequential C programs. It is based on symbolic execution (SE) and its unique features are in how it makes SE finite in presence of unbounded loops and its use of interpolants from infeasible paths to tackle the path-explosion problem.

Abstract. Symbolic execution with interpolation is emerging as an alternative to CEGAR for software verification. The performance of both methods relies critically on interpolation in order to obtain the most general abstraction of the current symbolic or abstract state which can be shown to remain error-free. CEGAR naturally handles unbounded loops because it is based on abstract interpretation. In contrast, symbolic execution requires a special extension for such loops. In this paper, we present such an extension. Its main characteristic is that it performs eager subsumption, that is, it always attempts to perform abstraction in order to avoid exploring other symbolic states. It balances this primary desire for more abstraction with the secondary desire to maintain the strongest loop invariant, for earlier detection of infeasible paths, which entails less abstraction. Occasionally certain abstractions are not permitted because of the reachability of error states; this is the underlying mechanism which then causes selective unrolling, that is, the unrolling of a loop along relevant paths only.