14,884 research outputs found
Syntactic Abstraction of B Models to Generate Tests
In a model-based testing approach as well as for the verification of
properties, B models provide an interesting solution. However, for industrial
applications, the size of their state space often makes them hard to handle. To
reduce the amount of states, an abstraction function can be used, often
combining state variable elimination and domain abstractions of the remaining
variables. This paper complements previous results, based on domain abstraction
for test generation, by adding a preliminary syntactic abstraction phase, based
on variable elimination. We define a syntactic transformation that suppresses
some variables from a B event model, in addition to a method that chooses
relevant variables according to a test purpose. We propose two methods to
compute an abstraction A of an initial model M. The first one computes A as a
simulation of M, and the second one computes A as a bisimulation of M. The
abstraction process produces a finite state system. We apply this abstraction
computation to a Model Based Testing process.Comment: Tests and Proofs 2010, Malaga : Spain (2010
The abstraction effect on logic rules application
The aim of this study is to analyze the relationship between training on abstraction and the comprehension of logic rules. In order to evaluate the possibility of improvement on logic performance we have selected the particular case of the DeMorganâs laws. The dispute between the natural logic approach and the mental models theory is analyzed from the perspective of such abstraction effect. Two experiments are reported. The first one suggests that the presentation of a formal proof promotes a better comprehension of DeMorganÂŽs laws than the use of visual resources or colloquial examples. The second one offers a stronger test for the same abstraction effect. Some limitations concerned with the syntactic meaning of negation and the differences between constructive and evaluative conditions are discussed. Since the meaning of abstraction for the psychology of reasoning is pointed out as critical some suggestions for further research and possible educational applications are mentioned.Fil: Macbeth, Guillermo Eduardo. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; Argentina. Universidad Nacional de Entre RĂos. Facultad de Ciencias de la EducaciĂłn; ArgentinaFil: Razumiejczyk, Eugenia. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; Argentina. Universidad Nacional de Entre RĂos. Facultad de Ciencias de la EducaciĂłn; ArgentinaFil: Campitelli, Guillermo Jorge. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; Argentina. Edith Cowan University; Australi
Reusing Test-Cases on Different Levels of Abstraction in a Model Based Development Tool
Seamless model based development aims to use models during all phases of the
development process of a system. During the development process in a
component-based approach, components of a system are described at qualitatively
differing abstraction levels: during requirements engineering component models
are rather abstract high-level and underspecified, while during implementation
the component models are rather concrete and fully specified in order to enable
code generation. An important issue that arises is assuring that the concrete
models correspond to abstract models. In this paper, we propose a method to
assure that concrete models for system components refine more abstract models
for the same components. In particular we advocate a framework for reusing
testcases at different abstraction levels. Our approach, even if it cannot
completely prove the refinement, can be used to ensure confidence in the
development process. In particular we are targeting the refinement of
requirements which are represented as very abstract models. Besides a formal
model of our approach, we discuss our experiences with the development of an
Adaptive Cruise Control (ACC) system in a model driven development process.
This uses extensions which we implemented for our model-based development tool
and which are briefly presented in this paper.Comment: In Proceedings MBT 2012, arXiv:1202.582
Semantic Ambiguity and Perceived Ambiguity
I explore some of the issues that arise when trying to establish a connection
between the underspecification hypothesis pursued in the NLP literature and
work on ambiguity in semantics and in the psychological literature. A theory of
underspecification is developed `from the first principles', i.e., starting
from a definition of what it means for a sentence to be semantically ambiguous
and from what we know about the way humans deal with ambiguity. An
underspecified language is specified as the translation language of a grammar
covering sentences that display three classes of semantic ambiguity: lexical
ambiguity, scopal ambiguity, and referential ambiguity. The expressions of this
language denote sets of senses. A formalization of defeasible reasoning with
underspecified representations is presented, based on Default Logic. Some
issues to be confronted by such a formalization are discussed.Comment: Latex, 47 pages. Uses tree-dvips.sty, lingmacros.sty, fullname.st
Experiences modelling and using object-oriented telecommunication service frameworks in SDL
This paper describes experiences in using SDL and its associated tools to create telecommunication services by producing and specialising object-oriented frameworks. The chosen approach recognises the need for the rapid creation of validated telecommunication services. It introduces two stages to service creation. Firstly a software expert produces a service framework, and secondly a telecommunications âbusiness consultant' specialises the framework by means of graphical tools to rapidly produce services. Here the focus is given to the underlying technology required. In particular, the advantages and disadvantages of SDL and tools for this purpose are highlighted
An Exploratory Study of Forces and Frictions affecting Large-Scale Model-Driven Development
In this paper, we investigate model-driven engineering, reporting on an
exploratory case-study conducted at a large automotive company. The study
consisted of interviews with 20 engineers and managers working in different
roles. We found that, in the context of a large organization, contextual forces
dominate the cognitive issues of using model-driven technology. The four forces
we identified that are likely independent of the particular abstractions chosen
as the basis of software development are the need for diffing in software
product lines, the needs for problem-specific languages and types, the need for
live modeling in exploratory activities, and the need for point-to-point
traceability between artifacts. We also identified triggers of accidental
complexity, which we refer to as points of friction introduced by languages and
tools. Examples of the friction points identified are insufficient support for
model diffing, point-to-point traceability, and model changes at runtime.Comment: To appear in proceedings of MODELS 2012, LNCS Springe
A matter of time: Implicit acquisition of recursive sequence structures
A dominant hypothesis in empirical research on the evolution of language is the following: the fundamental difference between animal and human communication systems is captured by the distinction between regular and more complex non-regular grammars. Studies reporting successful artificial grammar learning of nested recursive structures and imaging studies of the same have methodological shortcomings since they typically allow explicit problem solving strategies and this has been shown to account for the learning effect in subsequent behavioral studies. The present study overcomes these shortcomings by using subtle violations of agreement structure in a preference classification task. In contrast to the studies conducted so far, we use an implicit learning paradigm, allowing the time needed for both abstraction processes and consolidation to take place. Our results demonstrate robust implicit learning of recursively embedded structures (context-free grammar) and recursive structures with cross-dependencies (context-sensitive grammar) in an artificial grammar learning task spanning 9 days. Keywords: Implicit artificial grammar learning; centre embedded; cross-dependency; implicit learning; context-sensitive grammar; context-free grammar; regular grammar; non-regular gramma
B Model Slicing and Predicate Abstraction to Generate Tests
Accepted manuscript. Revised and extended version of a TAP'10 paper. To appear.International audienceIn a model-based testing approach as well as for the verification of properties, B models provide an interesting modeling solution. However, for industrial applications, the size of their state space often makes them hard to handle. To reduce the amount of states, an abstraction function can be used. The abstraction is often a domain abstraction of the state variables that requires many proof obligations to be discharged, which can be very time-consuming for real applications. This paper presents a contribution to this problem that complements an approach based on domain abstraction for test generation, by adding a preliminary syntactic abstraction phase, based on variable elimination. We define a syntactic transformation that suppresses some variables from a B event model, in addition to three methods that choose relevant variables according to a test purpose. In this way, we propose a method that computes an abstraction of a source model {\mathsf{M}} according to a set of selected relevant variables. Depending on the method used, the abstraction can be computed as a simulation or as a bisimulation of {\mathsf{M}}. With this approach, the abstraction process produces a finite state system. We apply this abstraction computation to a model-based testing process. We evaluate experimentally the impact of the model simplification by variables' elimination on the size of the models, on the number of proof obligations to discharge, on the precision of the abstraction and on the coverage achieved by the test generation
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
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