74,912 research outputs found
BlogForever D2.6: Data Extraction Methodology
This report outlines an inquiry into the area of web data extraction, conducted within the context of blog preservation. The report reviews theoretical advances and practical developments for implementing data extraction. The inquiry is extended through an experiment that demonstrates the effectiveness and feasibility of implementing some of the suggested approaches. More specifically, the report discusses an approach based on unsupervised machine learning that employs the RSS feeds and HTML representations of blogs. It outlines the possibilities of extracting semantics available in blogs and demonstrates the benefits of exploiting available standards such as microformats and microdata. The report proceeds to propose a methodology for extracting and processing blog data to further inform the design and development of the BlogForever platform
Synthesis of Attributed Feature Models From Product Descriptions: Foundations
Feature modeling is a widely used formalism to characterize a set of products
(also called configurations). As a manual elaboration is a long and arduous
task, numerous techniques have been proposed to reverse engineer feature models
from various kinds of artefacts. But none of them synthesize feature attributes
(or constraints over attributes) despite the practical relevance of attributes
for documenting the different values across a range of products. In this
report, we develop an algorithm for synthesizing attributed feature models
given a set of product descriptions. We present sound, complete, and
parametrizable techniques for computing all possible hierarchies, feature
groups, placements of feature attributes, domain values, and constraints. We
perform a complexity analysis w.r.t. number of features, attributes,
configurations, and domain size. We also evaluate the scalability of our
synthesis procedure using randomized configuration matrices. This report is a
first step that aims to describe the foundations for synthesizing attributed
feature models
Semantics-based Automated Web Testing
We present TAO, a software testing tool performing automated test and oracle
generation based on a semantic approach. TAO entangles grammar-based test
generation with automated semantics evaluation using a denotational semantics
framework. We show how TAO can be incorporated with the Selenium automation
tool for automated web testing, and how TAO can be further extended to support
automated delta debugging, where a failing web test script can be
systematically reduced based on grammar-directed strategies. A real-life
parking website is adopted throughout the paper to demonstrate the effectivity
of our semantics-based web testing approach.Comment: In Proceedings WWV 2015, arXiv:1508.0338
Mastering Heterogeneous Behavioural Models
Heterogeneity is one important feature of complex systems, leading to the
complexity of their construction and analysis. Moving the heterogeneity at
model level helps in mastering the difficulty of composing heterogeneous models
which constitute a large system. We propose a method made of an algebra and
structure morphisms to deal with the interaction of behavioural models,
provided that they are compatible. We prove that heterogeneous models can
interact in a safe way, and therefore complex heterogeneous systems can be
built and analysed incrementally. The Uppaal tool is targeted for
experimentations.Comment: 16 pages, a short version to appear in MEDI'201
- âŠ