The software model checker BLAST: Applications to software engineering

BLAST is an automatic verification tool for checking temporal safety properties of C programs. Given a C program and a temporal safety property, BLAST either statically proves that the program satisfies the safety property, or provides an execution path that exhibits a violation of the property (or, since the problem is undecidable, does not terminate). BLAST constructs, explores, and refines abstractions of the program state space based on lazy predicate abstraction and interpolation-based predicate discovery. This paper gives an introduction to BLAST and demonstrates, through two case studies, how it can be applied to program verification and test-case generation. In the first case study, we use BLAST to statically prove memory safety for C programs. We use CCURED, a type-based memory-safety analyzer, to annotate a program with run-time assertions that check for safe memory operations. Then, we use BLAST to remove as many of the run-time checks as possible (by proving that these checks never fail), and to generate execution scenarios that violate the assertions for the remaining run-time checks. In our second case study, we use BLAST to automatically generate test suites that guarantee full coverage with respect to a given predicate. Given a C program and a target predicate p, BLAST determines the program locations q for which there exists a program execution that reaches q with p true, and automatically generates a set of test vectors that generate such executions. Our experiments show that BLAST can provide automated, precise, and scalable analysis for C programs

Lazy Shape Analysis

Many software model checkers are based on predicate abstraction. If the verification goal depends on pointer structures, the approach does not work well, because it is difficult to find adequate predicate abstractions for the heap. In contrast, shape analysis, which uses graph-based heap abstractions, can provide a compact representation of recursive data structures. We integrate shape analysis into the software model checker BLAST. Because shape analysis is expensive, we do not apply it globally. Instead, we ensure that, like predicates, shape graphs are computed and stored locally, only where necessary for proving the verification goal. To achieve this, we extend lazy abstraction refinement, which so far has been used only for predicate abstractions, to three-valued logical structures. This approach does not only increase the precision of model checking, but it also increases the efficiency of shape analysis. We implemented the technique by extending BLAST with calls to TVLA

Software Model Checking via Large-Block Encoding

The construction and analysis of an abstract reachability tree (ART) are the basis for a successful method for software verification. The ART represents unwindings of the control-flow graph of the program. Traditionally, a transition of the ART represents a single block of the program, and therefore, we call this approach single-block encoding (SBE). SBE may result in a huge number of program paths to be explored, which constitutes a fundamental source of inefficiency. We propose a generalization of the approach, in which transitions of the ART represent larger portions of the program; we call this approach large-block encoding (LBE). LBE may reduce the number of paths to be explored up to exponentially. Within this framework, we also investigate symbolic representations: for representing abstract states, in addition to conjunctions as used in SBE, we investigate the use of arbitrary Boolean formulas; for computing abstract-successor states, in addition to Cartesian predicate abstraction as used in SBE, we investigate the use of Boolean predicate abstraction. The new encoding leverages the efficiency of state-of-the-art SMT solvers, which can symbolically compute abstract large-block successors. Our experiments on benchmark C programs show that the large-block encoding outperforms the single-block encoding.Comment: 13 pages (11 without cover), 4 figures, 5 table

Development of a framework for automated systematic testing of safety-critical embedded systems

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.”In this paper we introduce the development of a framework for testing safety-critical embedded systems based on the concepts of model-based testing. In model-based testing the test cases are derived from a model of the system under test. In our approach the model is an automaton model that is automatically extracted from the C-source code of the system under test. Beside random test data generation the test case generation uses formal methods, in detail model checking techniques. To find appropriate test cases we use the requirements defined in the system specification. To cover further execution paths we developed an additional, to our best knowledge, novel method based on special structural coverage criteria. We present preliminary results on the model extraction using a concrete industrial case study from the automotive domain

Model Checking with Program Slicing Based on Variable Dependence Graphs

In embedded control systems, the potential risks of software defects have been increasing because of software complexity which leads to, for example, timing related problems. These defects are rarely found by tests or simulations. To detect such defects, we propose a modeling method which can generate software models for model checking with a program slicing technique based on a variable dependence graph. We have applied the proposed method to one case in automotive control software and demonstrated the effectiveness of the method. Furthermore, we developed a software tool to automate model generation and achieved a 35% decrease in total verification time on model checking.Comment: In Proceedings FTSCS 2012, arXiv:1212.657

Model Checker Execution Reports

Software model checking constitutes an undecidable problem and, as such, even an ideal tool will in some cases fail to give a conclusive answer. In practice, software model checkers fail often and usually do not provide any information on what was effectively checked. The purpose of this work is to provide a conceptual framing to extend software model checkers in a way that allows users to access information about incomplete checks. We characterize the information that model checkers themselves can provide, in terms of analyzed traces, i.e. sequences of statements, and safe cones, and present the notion of execution reports, which we also formalize. We instantiate these concepts for a family of techniques based on Abstract Reachability Trees and implement the approach using the software model checker CPAchecker. We evaluate our approach empirically and provide examples to illustrate the execution reports produced and the information that can be extracted