3,287 research outputs found
A Historical Perspective on Runtime Assertion Checking in Software Development
This report presents initial results in the area of software testing and analysis produced as part of the Software Engineering Impact Project. The report describes the historical development of runtime assertion checking, including a description of the origins of and significant features associated with assertion checking mechanisms, and initial findings about current industrial use. A future report will provide a more comprehensive assessment of development practice, for which we invite readers of this report to contribute information
Diagnosing Errors in DbC Programs Using Constraint Programming
Model-Based Diagnosis allows to determine why a correctly
designed system does not work as it was expected. In this paper, we propose
a methodology for software diagnosis which is based on the combination
of Design by Contract, Model-Based Diagnosis and Constraint
Programming. The contracts are specified by assertions embedded in the
source code. These assertions and an abstraction of the source code are
transformed into constraints, in order to obtain the model of the system.
Afterwards, a goal function is created for detecting which assertions or
source code statements are incorrect. The application of this methodology
is automatic and is based on Constraint Programming techniques.
The originality of this work stems from the transformation of contracts
and source code into constraints, in order to determine which assertions
and source code statements are not consistent with the specification.Ministerio de Ciencia y TecnologĂa DPI2003-07146-C02-0
Predicate Abstraction for Linked Data Structures
We present Alias Refinement Types (ART), a new approach to the verification
of correctness properties of linked data structures. While there are many
techniques for checking that a heap-manipulating program adheres to its
specification, they often require that the programmer annotate the behavior of
each procedure, for example, in the form of loop invariants and pre- and
post-conditions. Predicate abstraction would be an attractive abstract domain
for performing invariant inference, existing techniques are not able to reason
about the heap with enough precision to verify functional properties of data
structure manipulating programs. In this paper, we propose a technique that
lifts predicate abstraction to the heap by factoring the analysis of data
structures into two orthogonal components: (1) Alias Types, which reason about
the physical shape of heap structures, and (2) Refinement Types, which use
simple predicates from an SMT decidable theory to capture the logical or
semantic properties of the structures. We prove ART sound by translating types
into separation logic assertions, thus translating typing derivations in ART
into separation logic proofs. We evaluate ART by implementing a tool that
performs type inference for an imperative language, and empirically show, using
a suite of data-structure benchmarks, that ART requires only 21% of the
annotations needed by other state-of-the-art verification techniques
Your Proof Fails? Testing Helps to Find the Reason
Applying deductive verification to formally prove that a program respects its
formal specification is a very complex and time-consuming task due in
particular to the lack of feedback in case of proof failures. Along with a
non-compliance between the code and its specification (due to an error in at
least one of them), possible reasons of a proof failure include a missing or
too weak specification for a called function or a loop, and lack of time or
simply incapacity of the prover to finish a particular proof. This work
proposes a new methodology where test generation helps to identify the reason
of a proof failure and to exhibit a counter-example clearly illustrating the
issue. We describe how to transform an annotated C program into C code suitable
for testing and illustrate the benefits of the method on comprehensive
examples. The method has been implemented in STADY, a plugin of the software
analysis platform FRAMA-C. Initial experiments show that detecting
non-compliances and contract weaknesses allows to precisely diagnose most proof
failures.Comment: 11 pages, 10 figure
Automated Fixing of Programs with Contracts
This paper describes AutoFix, an automatic debugging technique that can fix
faults in general-purpose software. To provide high-quality fix suggestions and
to enable automation of the whole debugging process, AutoFix relies on the
presence of simple specification elements in the form of contracts (such as
pre- and postconditions). Using contracts enhances the precision of dynamic
analysis techniques for fault detection and localization, and for validating
fixes. The only required user input to the AutoFix supporting tool is then a
faulty program annotated with contracts; the tool produces a collection of
validated fixes for the fault ranked according to an estimate of their
suitability.
In an extensive experimental evaluation, we applied AutoFix to over 200
faults in four code bases of different maturity and quality (of implementation
and of contracts). AutoFix successfully fixed 42% of the faults, producing, in
the majority of cases, corrections of quality comparable to those competent
programmers would write; the used computational resources were modest, with an
average time per fix below 20 minutes on commodity hardware. These figures
compare favorably to the state of the art in automated program fixing, and
demonstrate that the AutoFix approach is successfully applicable to reduce the
debugging burden in real-world scenarios.Comment: Minor changes after proofreadin
Automating Deductive Verification for Weak-Memory Programs
Writing correct programs for weak memory models such as the C11 memory model
is challenging because of the weak consistency guarantees these models provide.
The first program logics for the verification of such programs have recently
been proposed, but their usage has been limited thus far to manual proofs.
Automating proofs in these logics via first-order solvers is non-trivial, due
to reasoning features such as higher-order assertions, modalities and rich
permission resources. In this paper, we provide the first implementation of a
weak memory program logic using existing deductive verification tools. We
tackle three recent program logics: Relaxed Separation Logic and two forms of
Fenced Separation Logic, and show how these can be encoded using the Viper
verification infrastructure. In doing so, we illustrate several novel encoding
techniques which could be employed for other logics. Our work is implemented,
and has been evaluated on examples from existing papers as well as the Facebook
open-source Folly library.Comment: Extended version of TACAS 2018 publicatio
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