KIV: overview and VerifyThis competition

Ernst, Gerhard; Pfähler, Jörg; Schellhorn, Gerhard; Haneberg, Dominik; Reif, Wolfgang

doi:10.1007/s10009-014-0308-3

Cited by 45 publications

(22 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our tool is the interactive theorem prover KIV [35,12]. For a detailed description of the specification language see for example [13] (this volume) and [38].…”

Section: Modelsmentioning

confidence: 99%

Development of a Verified Flash File System

Schellhorn

Ernst

Pfähler

et al. 2014

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

Abstract. This paper gives an overview over the development of a formally verified file system for flash memory. We describe our approach that is based on Abstract State Machines and incremental modular refinement. Some of the important intermediate levels and the features they introduce are given. We report on the verification challenges addressed so far, and point to open problems and future work. We furthermore draw preliminary conclusions on the methodology and the required tool support.

show abstract

“…Our tool is the interactive theorem prover KIV [35,12]. For a detailed description of the specification language see for example [13] (this volume) and [38].…”

Section: Modelsmentioning

confidence: 99%

Development of a Verified Flash File System

Schellhorn

Ernst

Pfähler

et al. 2014

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…For object-oriented programming in general, there exist a number of alternatives. The KIV system [19] can be employed for the develop-ment of safety-related software, is also based on a dynamic logic, and primarily focuses on strong proof support. ESC/Java2 [16] is a static checker that finds common runtime-errors in JML-specified programs.…”

Section: Related Workmentioning

confidence: 99%

Experience Report on Formally Verifying Parts of OpenJDK's API with KeY

Knüppel¹,

Thüm²,

Pardylla³

et al. 2018

Electron. Proc. Theor. Comput. Sci.

View full text Add to dashboard Cite

Deductive verification of software has not yet found its way into industry, as complexity and scalability issues require highly specialized experts. The long-term perspective is, however, to develop verification tools aiding industrial software developers to find bugs or bottlenecks in software systems faster and more easily. The KeY project constitutes a framework for specifying and verifying software systems, aiming at making formal verification tools applicable for mainstream software development. To help the developers of KeY, its users, and the deductive verification community, we summarize our experiences with KeY 2.6.1 in specifying and verifying real-world Java code from a users perspective. To this end, we concentrate on parts of the Collections-API of OpenJDK 6, where an informal specification exists. While we describe how we bridged informal and formal specification, we also exhibit accompanied challenges that we encountered. Our experiences are that (a) in principle, deductive verification for API-like code bases is feasible, but requires high expertise, (b) developing formal specifications for existing code bases is still notoriously hard, and (c) the under-specification of certain language constructs in Java is challenging for tool builders. Our initial effort in specifying parts of OpenJDK 6 constitutes a stepping stone towards a case study for future research.

show abstract

“…At the other end of the spectrum are interactive approaches to verification-which include tools such as KIV [15]-where the user is ultimately responsible for providing input to the prover on demand, whenever it needs guidance through a successful correctness proof; in principle, this makes it possible to verify arbitrarily complex properties, but it is approachable only by highly trained verification experts. The classification into automatic and interactive is ultimately fuzzy, but it is nonetheless practically useful to assess the level of abstraction at which the user/tool interaction takes place.…”

Section: Auto-active Functional Verification Of Object-oriented Programsmentioning

confidence: 99%

“…For complete descriptions see the references (and [42] for our solutions to problems [13][14][15][16][17][18][19][20]. The table is partitioned into three groups: the first group (1-11) includes mainly algorithmic problems; the second group (13)(14)(15)(16)(17)(18)(19)(20) includes object-oriented design challenges that require complex invariant and framing methodologies; the third group (21-30) targets data structure-related problems that combine algorithmic and invariant-based reasoning. The second and third group include cutting-edge challenges of reasoning about functional properties of objects in the heap; for example, pip describes a data structure whose node invariant depends on objects not directly accessible from the node in the physical heap.…”

Section: Benchmarks Descriptionmentioning

confidence: 99%

“…The CodeContract static checker (formerly known as Clousot [37]) is a powerful static analyzer for .NET languages that belongs to the former category of fully automatic tools (and hence it is limited to properties expressible in its abstract domains). The KIV environment [15] for Java belongs to the latter category: its full-fledged usage requires explicit user interaction to guide the prover through the verification process.…”

mentioning

confidence: 99%

See 1 more Smart Citation

AutoProof: auto-active functional verification of object-oriented programs

Furia

Nordio

Polikarpova³

et al. 2016

Int J Softw Tools Technol Transfer

View full text Add to dashboard Cite

Auto-active verifiers provide a level of automation intermediate between fully automatic and interactive: users supply code with annotations as input while benefiting from a high level of automation in the back-end. This paper presents AutoProof, a state-of-the-art auto-active verifier for object-oriented sequential programs with complex functional specifications. AutoProof fully supports advanced objectoriented features and a powerful methodology for framing and class invariants, which make it applicable in practice to idiomatic object-oriented patterns. The paper focuses on describing AutoProof's interface, design, and implementation features, and demonstrates AutoProof's performance on a rich collection of benchmark problems. The results attest AutoProof's competitiveness among tools in its league on cutting-edge functional verification of object-oriented programs.

show abstract

KIV: overview and VerifyThis competition

Cited by 45 publications

References 21 publications

Development of a Verified Flash File System

Development of a Verified Flash File System

Experience Report on Formally Verifying Parts of OpenJDK's API with KeY

AutoProof: auto-active functional verification of object-oriented programs

Contact Info

Product

Resources

About