464 research outputs found

    A Survey of Symbolic Execution Techniques

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    Many security and software testing applications require checking whether certain properties of a program hold for any possible usage scenario. For instance, a tool for identifying software vulnerabilities may need to rule out the existence of any backdoor to bypass a program's authentication. One approach would be to test the program using different, possibly random inputs. As the backdoor may only be hit for very specific program workloads, automated exploration of the space of possible inputs is of the essence. Symbolic execution provides an elegant solution to the problem, by systematically exploring many possible execution paths at the same time without necessarily requiring concrete inputs. Rather than taking on fully specified input values, the technique abstractly represents them as symbols, resorting to constraint solvers to construct actual instances that would cause property violations. Symbolic execution has been incubated in dozens of tools developed over the last four decades, leading to major practical breakthroughs in a number of prominent software reliability applications. The goal of this survey is to provide an overview of the main ideas, challenges, and solutions developed in the area, distilling them for a broad audience. The present survey has been accepted for publication at ACM Computing Surveys. If you are considering citing this survey, we would appreciate if you could use the following BibTeX entry: http://goo.gl/Hf5FvcComment: This is the authors pre-print copy. If you are considering citing this survey, we would appreciate if you could use the following BibTeX entry: http://goo.gl/Hf5Fv

    Obtaining Real-World Benchmark Programs from Open-Source Repositories Through Abstract-Semantics Preserving Transformations

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    Benchmark programs are an integral part of program analysis research. Researchers use benchmark programs to evaluate existing techniques and test the feasibility of new approaches. The larger and more realistic the set of benchmarks, the more confident a researcher can be about the correctness and reproducibility of their results. However, obtaining an adequate set of benchmark programs has been a long-standing challenge in the program analysis community. In this thesis, we present the APT tool, a framework we designed and implemented to automate the generation of realistic benchmark programs suitable for program analysis evaluations. Our tool targets intra-procedural analyses that operate on an integer domain, specifically symbolic execution. The framework is composed of three main stages. In the first stage, the tool extracts potential benchmark programs from open-source repositories suitable for symbolic execution. In the second stage, the tool transforms the extracted programs into compilable, stand-alone benchmarks by removing external dependencies and nonlinear expressions. In the third stage, the benchmarks are verified and made available for the user. We have designed our transformation algorithms to remove program dependencies and nonlinear expressions while preserving their semantics-equivalence in the abstraction of symbolic analysis. That is, we want the information the analysis computes on the original program and its transformed version to be equivalent. Our work provides static analysis researchers with concise, compilable benchmark programs that are relevant to symbolic execution, allowing them to focus their efforts on advancing analysis techniques. Furthermore, our work benefits the software engineering community by enabling static analysis researchers to perform benchmarking with a large, realistic set of programs, thus strengthening the empirical evidence of the advancements in static program analysis

    Towards Symbolic Execution in Erlang

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    The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-662-46823-4_28The concurrent functional language Erlang [1] has a number of distinguishing features, like dynamic typing, concurrency via asynchronous message passing or hot code loading, that make it especially appropriate for distributed, faulttolerant, soft real-time applications. The success of Erlang is witnessed by the increasing number of its industrial applications. For instance, Erlang has been used to implement Facebook’s chat back-end, the mobile application Whatsapp or Twitterfall—a service to view trends and patterns from Twitter—, to name a few. The success of the language, however, also requires the development of powerful testing and verification techniques. Symbolic execution is at the core of many program analysis and transformation techniques, like partial evaluation, test-case generation or model checking. In this paper, we introduce a symbolic execution technique for Erlang. We discuss how both an overapproximation and an underapproximation of the concrete semantics can be obtained. We illustrate our approach through some examples. To the best of our knowledge, this is the first attempt to formalize symbolic execution in the context of this language, where previous approaches have only considered exploring different schedulings but have not dealt with symbolic data. More details can be found in the companion technical reportThis work has been partially supported by the Spanish Ministerio de Economía y Competitividad (Secretaría de Estado de Investigación, Desarrollo e Innovación) under grant TIN2013-44742-C4-1-R and by the Generalitat Valenciana under grant PROMETEO/2011/052.Vidal Oriola, GF. (2015). Towards Symbolic Execution in Erlang. En Perspectives of System Informatics. Springer. 351-360. https://doi.org/10.1007/978-3-662-46823-4_28S35136

    Multi-run side-channel analysis using Symbolic Execution and Max-SMT

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    Proceedings of the First NASA Formal Methods Symposium

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    Topics covered include: Model Checking - My 27-Year Quest to Overcome the State Explosion Problem; Applying Formal Methods to NASA Projects: Transition from Research to Practice; TLA+: Whence, Wherefore, and Whither; Formal Methods Applications in Air Transportation; Theorem Proving in Intel Hardware Design; Building a Formal Model of a Human-Interactive System: Insights into the Integration of Formal Methods and Human Factors Engineering; Model Checking for Autonomic Systems Specified with ASSL; A Game-Theoretic Approach to Branching Time Abstract-Check-Refine Process; Software Model Checking Without Source Code; Generalized Abstract Symbolic Summaries; A Comparative Study of Randomized Constraint Solvers for Random-Symbolic Testing; Component-Oriented Behavior Extraction for Autonomic System Design; Automated Verification of Design Patterns with LePUS3; A Module Language for Typing by Contracts; From Goal-Oriented Requirements to Event-B Specifications; Introduction of Virtualization Technology to Multi-Process Model Checking; Comparing Techniques for Certified Static Analysis; Towards a Framework for Generating Tests to Satisfy Complex Code Coverage in Java Pathfinder; jFuzz: A Concolic Whitebox Fuzzer for Java; Machine-Checkable Timed CSP; Stochastic Formal Correctness of Numerical Algorithms; Deductive Verification of Cryptographic Software; Coloured Petri Net Refinement Specification and Correctness Proof with Coq; Modeling Guidelines for Code Generation in the Railway Signaling Context; Tactical Synthesis Of Efficient Global Search Algorithms; Towards Co-Engineering Communicating Autonomous Cyber-Physical Systems; and Formal Methods for Automated Diagnosis of Autosub 6000

    Combining Model Checking and Testing

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    Abstract Model checking and testing have a lot in common. Over the last two decades, significant progress has been made on how to broaden the scope of model checking from finite-state abstractions to actual software implementations. One way to do this consists of adapting model checking into a form of systematic testing that is applicable to industrial-size software. This chapter presents an overview of this strand of software model checking

    Model checking a model checker: A code contract combined approach

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