Symbolic Execution Debugger (SED)

Hentschel, Martin; Bubel, Richard; Hähnle, Reiner

doi:10.1007/978-3-319-11164-3_21

Cited by 12 publications

(5 citation statements)

References 9 publications

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“…One of the reasons for this is that conditionals and loops may create state explosion, and long (possibly infinite) traces of configurations. To improve this situation we extend relational symbolic execution with loop invariants Hentschel et al (2014) so that the symbolic execution of a loop can be performed by jumping over the loop in one step and by adding an invariant to the path condition. We design two rules for unary and relational invariants which allow one to reason in one step about loops both for proving and for finding counterexamples.…”

Section: Relational Symbolic Execution: Informallymentioning

confidence: 99%

Relational Symbolic Execution

Farina

Chong

Gaboardi

2019

Proceedings of the 21st International Symposium on Principles and Practice of Declarative Programming

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Symbolic execution is a classical program analysis technique used to show that programs satisfy or violate given specifications. In this work we generalize symbolic execution to support program analysis for relational specifications in the form of relational properties -these are properties about two runs of two programs on related inputs, or about two executions of a single program on related inputs. Relational properties are useful to formalize notions in security and privacy, and to reason about program optimizations. We design a relational symbolic execution engine, named RelSym which supports interactive refutation, as well as proving of relational properties for programs written in a language with arrays and for-like loops.

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Section: Relational Symbolic Execution: Informallymentioning

confidence: 99%

Relational Symbolic Execution

Farina

Chong

Gaboardi

2019

Proceedings of the 21st International Symposium on Principles and Practice of Declarative Programming

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“…The emerging integration of verification, test generation, and debugging aspects into single tool chains, as described above, is an encouraging development. We begin to see deductive verification tools that are intentionally presented as enhanced software development environments, for example, the Symbolic Execution Debugger (SED) [56] based on Eclipse or the Dafny IDE [91] based on MS Visual Studio.…”

Section: Integrationmentioning

confidence: 99%

“…Systems, such as KeY [3], can provide symbolic counter examples, and SED [56] computes symbolic backward slices from failure nodes in symbolic evaluation trees. The system StaDy [109] goes beyond this and uses dynamic verification to analyze failed proofs.…”

Section: Integrationmentioning

confidence: 99%

Deductive Software Verification: From Pen-and-Paper Proofs to Industrial Tools

Hähnle

Huisman

2019

Lecture Notes in Computer Science

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Deductive software verification aims at formally verifying that all possible behaviors of a given program satisfy formally defined, possibly complex properties, where the verification process is based on logical inference. We follow the trajectory of the field from its inception in the late 1960s via its current state to its promises for the future, from pen-and-paper proofs for programs written in small, idealized languages to highly automated proofs of complex library or system code written in mainstream languages. We take stock of the state-of-art and give a list of the most important challenges for the further development of the field of deductive software verification.

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“…The (semi-)procedure described in the previous section has been implemented in the Python language as a proof of concept named DataMin.We rely on the Symbolic Execution Engine of the KeY Project [16]. This symbolic executor is run against a program P written in Java source code for which a minimiser should be generated.…”

Section: Datamin Implementationmentioning

confidence: 99%

Data Minimisation: A Language-Based Approach

Antignac

Sands

Schneider

2017

IFIP Advances in Information and Communication Technology

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Data minimisation is a privacy-enhancing principle considered as one of the pillars of personal data regulations. This principle dictates that personal data collected should be no more than necessary for the specific purpose consented by the user. In this paper we study data minimisation from a programming language perspective. We assume that a given program embodies the purpose of data collection, and define a data minimiser as a pre-processor for the input which reduces the amount of information available to the program without compromising its functionality. In this context we study formal definitions of data minimisation, present different mechanisms and architectures to ensure data minimisation, and provide a procedure to synthesise a correct data minimiser for a given program.

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Symbolic Execution Debugger (SED)

Cited by 12 publications

References 9 publications

Relational Symbolic Execution

Relational Symbolic Execution

Deductive Software Verification: From Pen-and-Paper Proofs to Industrial Tools

Data Minimisation: A Language-Based Approach

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