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ETAPS 2014


Model-based information flow analysis to support software certification
Leon Moonen (Simula Research Laboratory)

The research presented in this talk is part of an ongoing industrial collaboration with Kongsberg Maritime (KM), one of the largest suppliers of maritime systems worldwide. The division that we work with specializes in computerized systems for safety monitoring and automatic corrective actions on unacceptable hazardous situations. The overall goal of the collaboration is to provide our partner with software analysis tooling that provides source based evidence to support software certification. In particular, we study a family of complex safety-critical embedded software systems that connect software control components to physical sensors and mechanical actuators.
A frequently advocated approach to manage the development of such complex software systems is to compose them from reusable components, instead of starting from scratch. Components may be implemented in different programming languages and are tied together using configuration files, or glue code, defining instantiation, initialization and interconnections. Although correctly engineering the composition and configuration of components is crucial for the overall behavior, there is surprisingly little support for incorporating this information in the static verification and validation of these systems. Analyzing the properties of programs within closed code boundaries has been studied for some decades and is well-established.
The presentation will discuss the techniques we developed to support analysis across the components of a component-based system. We build upon OMG's Knowledge Discovery Metamodel to reverse engineer fine-grained homogeneous models for systems composed of heterogeneous artifacts. Next, we track the information flow in these models using slicing, and apply several transformations that enable us to visualize the information flow at various levels of abstraction, trading off between scope and detail and aimed to serve both safety domain experts as well as developers. Our techniques are implemented in a prototype toolset that has been successfully used to answer software certification questions of our industrial partner.

Verifying Programs by Evolving (Under)-Approximations
Arie Gurfinkel (Carnegie Mellon University)

Program verification, i.e., synthesis of safe inductive invariants, is a long standing challenge in Computer Science. While the problem is undecidable in general, there are many existing automated techniques that perform well in practice. In this talk, I will describe our recent work on verifying programs by a series of evolving approximations. The basic idea is that instead of verifying a target program P, we verify its "simpler-to-verify" approximation A, and adapt the proof or the counterexample to safety of A to P. Unlike many other existing approaches, our approximations are neither over- nor under-approximations of the target program. I will present two variants of this idea, for synthesizing invariants over linear arithmetic and over the theory of bit-vectors, respectively. The talk is based on the joint work with Anvesh Komuravelli, Anton Belov, Sagar Chaki, Joao Marques-Silva, and Edmund M. Clarke

Program Repair without Regret
Barbara Jobstmann (Verimag)

When fixing programs, we usually fix bugs one by one; at the same time, we try to leave as many parts of the program unchanged as possible. In this talk, I will present a new approach to repair reactive programs with respect to a specification that aims to support this incremental method. The specification is given in linear-temporal logic. Like in previous approaches, we aim for a repaired program that satisfies the specification and is syntactically close to the faulty program. The novelty of our approach is that it produces a program that is also semantically close to the original program by enforcing that a subset of the original traces is preserved. Intuitively, the faulty program is considered to be a part of the specification, which enables us to synthesize meaningful repairs, even for incomplete specifications. Our approach is based on synthesizing a program with a set of behaviors that stay within a lower and an upper bound. We provide an algorithm to decide if a program is repairable with respect to our new notion, and synthesize a repair if one exists. We analyze several ways to choose the set of traces to leave intact and show the boundaries they impose on repairability. We have evaluated the approach on several small examples.
This is joint work with Christian von Essen.

Verification-Aided Regression Testing
Fabrizio Pastore (Università degli Studi di Milano-Bicocca)

This talk presents Verification-Aided Regression Testing (VART), a novel extension of regression testing that uses model checking to increase the fault revealing capability of existing test suites. The key idea in VART is to extend the use of test case executions from the conventional direct fault discovery to the generation of behavioral properties specific to the upgrade, by (i) automatically producing properties that are proved to hold for the base version of a program, (ii) automatically identifying and checking on the upgraded program only the properties that, according to the developers? intention, must be preserved by the upgrade, and (iii) reporting the faults and the corresponding counter-examples that are not revealed by the regression tests.
The talk will detail the empirical results obtained with both open source and industrial software systems. These results show that VART automatically produces properties that increase the effectiveness of testing by timely and automatically detecting faults unnoticed by the existing regression test suites.
The talk will finally include a live demo of the Eclipse plug-in that implements VART. The demo will show how software engineers can identify regression faults with VART and fix these faults by inspecting the counter-examples produced by the tool.

Applications of Symbolic Finite Automata
Margus Veanes (Microsoft Research)

Symbolic automata theory lifts classical automata theory to rich alphabet theories. It does so by replacing an explicit alphabet with an alphabet described implicitly by a Boolean algebra. How does this lifting affect the basic algorithms that lay the foundation for modern automata theory and what is the incentive for doing this? We investigate these questions here from the point of view of program trace analysis and how such analysis can be used to perform evolution analysis of code. In our approach we use state-of-the-art constraint solving techniques for automata analysis that are both expressive and efficient and can handle very large alphabets.

Programming in Stages
K. Rustan M. Leino (Microsoft Research)

A major issue facing software development and maintenance is the sheer complexity of programs. Even software designs that start off simple often evolve into programs that are both brittle and hard to understand. When we explain a design or algorithm to a colleague, we do so by gradually introducing more details in our descriptions. Wouldn't it be nice if we could stage our programs in the same way?
In this talk, I consider the use of staging features in a programming language, in particular the way they are designed into the programming language Dafny, which is mostly based on the old theory of superposition refinement. The hope is that such features would let us program in stages, but putting the nice concepts into a language has been harder than expected. Perhaps we don't yet have the right feature set?

Producing Effective Interpolants for SAT-based Incremental Verification and Upgrade Checking
Grigory Fedyukovich (University of Lugano)

Propositional interpolation is widely used as a means of abstraction to achieve efficient SAT-based symbolic model checking. In particular, we use it as a main concept in two software bounded model checking techniques: 1) verification of a given source code incrementally with respect to various properties, and 2) verification of software upgrades with respect to a fixed set of properties.
In this talk, we describe the PeRIPLO framework, an interpolating SAT-solver that implements a set of techniques to generate and manipulate interpolants for different model checking tasks. Our systematic experimental investigation shows that size and logical strength of interpolants significantly affect the performance of verification, and that these characteristics depend on the role interpolants play in the verification process.