129,111 research outputs found
A Model-Derivation Framework for Software Analysis
Model-based verification allows to express behavioral correctness conditions
like the validity of execution states, boundaries of variables or timing at a
high level of abstraction and affirm that they are satisfied by a software
system. However, this requires expressive models which are difficult and
cumbersome to create and maintain by hand. This paper presents a framework that
automatically derives behavioral models from real-sized Java programs. Our
framework builds on the EMF/ECore technology and provides a tool that creates
an initial model from Java bytecode, as well as a series of transformations
that simplify the model and eventually output a timed-automata model that can
be processed by a model checker such as UPPAAL. The framework has the following
properties: (1) consistency of models with software, (2) extensibility of the
model derivation process, (3) scalability and (4) expressiveness of models. We
report several case studies to validate how our framework satisfies these
properties.Comment: In Proceedings MARS 2017, arXiv:1703.0581
Consistent SDNs through Network State Fuzzing
The conventional wisdom is that a software-defined network (SDN) operates under the premise that the logically centralized control plane has an accurate representation of the actual data plane state. Nevertheless, bugs, misconfigurations, faults or attacks can introduce inconsistencies that undermine correct operation. Previous work in this area, however, lacks a holistic methodology to tackle this problem and thus, addresses only certain parts of the problem. Yet, the consistency of the overall system is only as good as its least consistent part. Motivated by an analogy of network consistency checking with program testing, we propose to add active probe-based network state fuzzing to our consistency check repertoire. Hereby, our system, PAZZ, combines production traffic with active probes to continuously test if the actual forwarding path and decision elements (on the data plane) correspond to the expected ones (on the control plane). Our insight is that active traffic covers the inconsistency cases beyond the ones identified by passive traffic. PAZZ prototype was built and evaluated on topologies of varying scale and complexity. Our results show that PAZZ requires minimal network resources to detect persistent data plane faults through fuzzing and localize them quickly
Consistent SDNs through Network State Fuzzing
The conventional wisdom is that a software-defined network (SDN) operates
under the premise that the logically centralized control plane has an accurate
representation of the actual data plane state. Unfortunately, bugs,
misconfigurations, faults or attacks can introduce inconsistencies that
undermine correct operation. Previous work in this area, however, lacks a
holistic methodology to tackle this problem and thus, addresses only certain
parts of the problem. Yet, the consistency of the overall system is only as
good as its least consistent part. Motivated by an analogy of network
consistency checking with program testing, we propose to add active probe-based
network state fuzzing to our consistency check repertoire. Hereby, our system,
PAZZ, combines production traffic with active probes to periodically test if
the actual forwarding path and decision elements (on the data plane) correspond
to the expected ones (on the control plane). Our insight is that active traffic
covers the inconsistency cases beyond the ones identified by passive traffic.
PAZZ prototype was built and evaluated on topologies of varying scale and
complexity. Our results show that PAZZ requires minimal network resources to
detect persistent data plane faults through fuzzing and localize them quickly
while outperforming baseline approaches.Comment: Added three extra relevant references, the arXiv later was accepted
in IEEE Transactions of Network and Service Management (TNSM), 2019 with the
title "Towards Consistent SDNs: A Case for Network State Fuzzing
Thread-Modular Static Analysis for Relaxed Memory Models
We propose a memory-model-aware static program analysis method for accurately
analyzing the behavior of concurrent software running on processors with weak
consistency models such as x86-TSO, SPARC-PSO, and SPARC-RMO. At the center of
our method is a unified framework for deciding the feasibility of inter-thread
interferences to avoid propagating spurious data flows during static analysis
and thus boost the performance of the static analyzer. We formulate the
checking of interference feasibility as a set of Datalog rules which are both
efficiently solvable and general enough to capture a range of hardware-level
memory models. Compared to existing techniques, our method can significantly
reduce the number of bogus alarms as well as unsound proofs. We implemented the
method and evaluated it on a large set of multithreaded C programs. Our
experiments showthe method significantly outperforms state-of-the-art
techniques in terms of accuracy with only moderate run-time overhead.Comment: revised version of the ESEC/FSE 2017 pape
A Model-Derivation Framework for Software Analysis
Model-based verification allows to express behavioral correctness conditions
like the validity of execution states, boundaries of variables or timing at a
high level of abstraction and affirm that they are satisfied by a software
system. However, this requires expressive models which are difficult and
cumbersome to create and maintain by hand. This paper presents a framework that
automatically derives behavioral models from real-sized Java programs. Our
framework builds on the EMF/ECore technology and provides a tool that creates
an initial model from Java bytecode, as well as a series of transformations
that simplify the model and eventually output a timed-automata model that can
be processed by a model checker such as UPPAAL. The framework has the following
properties: (1) consistency of models with software, (2) extensibility of the
model derivation process, (3) scalability and (4) expressiveness of models. We
report several case studies to validate how our framework satisfies these
properties.Comment: In Proceedings MARS 2017, arXiv:1703.0581
Functional Requirements-Based Automated Testing for Avionics
We propose and demonstrate a method for the reduction of testing effort in
safety-critical software development using DO-178 guidance. We achieve this
through the application of Bounded Model Checking (BMC) to formal low-level
requirements, in order to generate tests automatically that are good enough to
replace existing labor-intensive test writing procedures while maintaining
independence from implementation artefacts. Given that existing manual
processes are often empirical and subjective, we begin by formally defining a
metric, which extends recognized best practice from code coverage analysis
strategies to generate tests that adequately cover the requirements. We then
formulate the automated test generation procedure and apply its prototype in
case studies with industrial partners. In review, the method developed here is
demonstrated to significantly reduce the human effort for the qualification of
software products under DO-178 guidance
Efficient parameter search for qualitative models of regulatory networks using symbolic model checking
Investigating the relation between the structure and behavior of complex
biological networks often involves posing the following two questions: Is a
hypothesized structure of a regulatory network consistent with the observed
behavior? And can a proposed structure generate a desired behavior? Answering
these questions presupposes that we are able to test the compatibility of
network structure and behavior. We cast these questions into a parameter search
problem for qualitative models of regulatory networks, in particular
piecewise-affine differential equation models. We develop a method based on
symbolic model checking that avoids enumerating all possible parametrizations,
and show that this method performs well on real biological problems, using the
IRMA synthetic network and benchmark experimental data sets. We test the
consistency between the IRMA network structure and the time-series data, and
search for parameter modifications that would improve the robustness of the
external control of the system behavior
Supporting user-oriented analysis for multi-view domain-specific visual languages
This is the post-print version of the final paper published in Information and Software Technology. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2008 Elsevier B.V.The integration of usable and flexible analysis support in modelling environments is a key success factor in Model-Driven Development. In this paradigm, models are the core asset from which code is automatically generated, and thus ensuring model correctness is a fundamental quality control activity. For this purpose, a common approach is to transform the system models into formal semantic domains for verification. However, if the analysis results are not shown in a proper way to the end-user (e.g. in terms of the original language) they may become useless.
In this paper we present a novel DSVL called BaVeL that facilitates the flexible annotation of verification results obtained in semantic domains to different formats, including the context of the original language. BaVeL is used in combination with a consistency framework, providing support for all steps in a verification process: acquisition of additional input data, transformation of the system models into semantic domains, verification, and flexible annotation of analysis results.
The approach has been validated analytically by the cognitive dimensions framework, and empirically by its implementation and application to several DSVLs. Here we present a case study of a notation in the area of Digital Libraries, where the analysis is performed by transformations into Petri nets and a process algebra.Spanish Ministry of Education and Science and MODUWEB
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