Frama-C is a source code analysis platform that aims at conducting verification of industrial-size C programs. It provides its users with a collection of plug-ins that perform static analysis, deductive verification, and testing, for safety- and security-critical software. Collaborative verification across cooperating plug-ins is enabled by their integration on top of a shared kernel and datastructures, and their compliance to a common specification language. This foundational article presents a consolidated view of the platform, its main and composite analyses, and some of its industrial achievements.

Frama-C: A software analysis perspective

Control: A perspective

Runtime property checking (as implemented in tools like Purify or Valgrind) checks whether a program execution satisfies a property. Active property checking extends runtime checking by checking whether the property is satisfied by all program executions that follow the same program path. This check is performed on a symbolic execution of the given program path using a constraint solver. If the check fails, the constraint solver generates an alternative program input triggering a new program execution that follows the same program path but exhibits a property violation. Combined with systematic dynamic test generation, which attempts to exercise all feasible paths in a program, active property checking defines a new form of dynamic software model checking (program verification). In this paper, we formalize and study active property checking. We show how static and dynamic type checking can be extended with active type checking. Then, we discuss how to implement active property checking efficiently. Finally, we discuss results of experiments with media playing applications on Windows, where active property checking was able to detect several new security-related bugs.

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Active property checking

Designing a new domain specific language is as any other complex task sometimes error-prone and usually time consuming, especially if the language shall be of high-quality and comfortably usable. Existing tool support focuses on the simplification of technical aspects but lacks support for an enforcement of principles for a good language design. In this paper we investigate guidelines that are useful for designing domain specific languages, largely based on our experience in developing languages as well as relying on existing guidelines on general purpose (GPLs) and modeling languages. We defined guidelines to support a DSL developer to achieve better quality of the language design and a better acceptance among its users.

/pdf/design-guidelines-for-domain-specific-languages-5giieherx6.pdf

Design Guidelines for Domain Specific Languages

In this paper, we explain how to achieve deterministic execution of FMUs (Functional Mockup Units) under the FMI (Functional Mockup Interface) standard In particular, we focus on co-simulation, where an FMU either contains its own internal simulation algorithm or serves as a gateway to a simulation tool We give conditions on the design of FMUs and master algorithms (which orchestrate the execution of FMUs) to achieve deterministic co-simulation We show that with the current version of the standard, these conditions demand capabilities from FMUs that are optional in the standard and rarely provided by an FMU in practice When FMUs lacking these required capabilities are used to compose a model, many basic modeling capabilities become unachievable, including simple discrete-event simulation and variable-step-size numerical integration algorithms We propose a small extension to the standard and a policy for designing FMUs that enables deterministic execution for a much broader class of models The extension enables a master algorithm to query an FMU for the time of events that are expected in the future We show that a model can be executed deterministically if all FMUs in the model are either memoryless or implement one of rollback or step-size prediction We show further that such a model can contain at most one "legacy" FMU that is not memoryless and provides neither rollback nor step-size prediction

Determinate composition of FMUs for co-simulation

We present a formal operational semantics for Stateflow, the graphical Statecharts-like language of the Matlab/Simulink tool suite that is widely used in model-based development of embedded systems. Stateflow has many tricky features but our operational treatment yields a surprisingly simple semantics for the subset that is generally recommended for industrial applications. We have validated our semantics by developing an interpreter that allows us to compare its behavior against the Matlab simulator. We have used the semantics as a foundation for developing prototype tools for formal analysis of Stateflow designs.

/pdf/an-operational-semantics-for-stateflow-39aaeh2may.pdf

An Operational Semantics for Stateflow

An operational semantics for stateflow

Formal and semi-formal tools are now being used in large projects both for development and certification. A typical project integrates many diverse tools such as static analyzers, model checkers, test generators, and constraint solvers. These tools are usually integrated in an ad hoc manner. There is, however, a need for a tool integration framework that can be used to systematically create workflows, to generate claims along with supporting evidence, and to maintain the claims and evidence as the inputs change. We present the Evidential Tool Bus ETB as a tool integration framework for constructing claims supported by evidence. ETB employs a variant of Datalog as a metalanguage for representing claims, rules, and evidence, and as a scripting language for capturing distributed workflows. ETB can be used to develop assurance cases for certifying complex systems that are developed and assured using a range of tools. We describe the design and prototype implementation of the ETB architecture, and present examples of formal verification workflows defined using ETB.

Tool Integration with the Evidential Tool Bus

The invention relates to the use of model checkers to generate efficient test sets for hardware and software systems. The method provides for extending existing tests to reach new coverage targets; searching *to* some or all of the uncovered targets in parallel; searching in parallel *from* some or all of the states reached in previous tests; and slicing the model relative to the current set of coverage targets. The invention provides efficient test case generation and test set formation. Deep regions of the state space can be reached within allotted time and memory. The approach has been applied to use of the model checkers of SRI's SAL system and to model-based designs developed in Stateflow. Stateflow models achieving complete state and transition coverage in a single test case are reported.

/pdf/formal-methods-for-test-case-generation-4p0x4x5ylk.pdf

Formal methods for test case generation

We describe sal-atg, a tool for automated test generation that will be distributed as part of the next release of SAL. Given a SAL specification augmented with Boolean trap variables representing test goals, sal-atg generates an efficient set of tests to drive the trap variables to TRUE; SAL specifications are typically instrumented with trap variables representing structural coverage criteria during automatic translation from a higher-level source notation, such as RSML−e or Stateflow. We describe extensions to the method of test generation that use conjunctions of trap variables; we show how these can be used to provide boundary coverage and to encode test purposes. We also describe how the output of the tool can be customized to the requirements of the test harness concerned. We describe experiments with sal-atg on realistic examples and preparations for evaluating the quality of tests generated using the experimental framework of Heimdahl, George and Weber [HGW04].

/pdf/automated-test-generation-with-sal-ogb6xwoc33.pdf

Automated Test Generation with SAL

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