1,721,157 research outputs found
Michael Sutton, Charles Maunas et les catholiques français (1890-1914). Nationalisme et positivisme, 1994
No full textCaron Jean-Claude. Michael Sutton, Charles Maunas et les catholiques français (1890-1914). Nationalisme et positivisme, 1994. In: Revue d'histoire du XIXe siècle, Tome 12, 1996/1. L'incendie. pp. 79-81
Learning natural coding conventions
Full text linkCoding conventions are ubiquitous in software engineering practice. Maintaining a uniform
coding style allows software development teams to communicate through code by
making the code clear and, thus, readable and maintainable—two important properties
of good code since developers spend the majority of their time maintaining software
systems. This dissertation introduces a set of probabilistic machine learning models
of source code that learn coding conventions directly from source code written in a
mostly conventional style. This alleviates the coding convention enforcement problem,
where conventions need to first be formulated clearly into unambiguous rules and then
be coded in order to be enforced; a tedious and costly process.
First, we introduce the problem of inferring a variable’s name given its usage context
and address this problem by creating Naturalize — a machine learning framework
that learns to suggest conventional variable names. Two machine learning models, a
simple n-gram language model and a specialized neural log-bilinear context model are
trained to understand the role and function of each variable and suggest new stylistically
consistent variable names. The neural log-bilinear model can even suggest previously
unseen names by composing them from subtokens (i.e. sub-components of code identifiers).
The suggestions of the models achieve 90% accuracy when suggesting variable
names at the top 20% most confident locations, rendering the suggestion system usable
in practice.
We then turn our attention to the significantly harder method naming problem.
Learning to name methods, by looking only at the code tokens within their body, requires
a good understating of the semantics of the code contained in a single method.
To achieve this, we introduce a novel neural convolutional attention network that learns
to generate the name of a method by sequentially predicting its subtokens. This is
achieved by focusing on different parts of the code and potentially directly using body
(sub)tokens even when they have never been seen before. This model achieves an F1
score of 51% on the top five suggestions when naming methods of real-world open-source
projects.
Learning about naming code conventions uses the syntactic structure of the code
to infer names that implicitly relate to code semantics. However, syntactic similarities
and differences obscure code semantics. Therefore, to capture features of semantic
operations with machine learning, we need methods that learn semantic continuous
logical representations. To achieve this ambitious goal, we focus our investigation on
logic and algebraic symbolic expressions and design a neural equivalence network architecture
that learns semantic vector representations of expressions in a syntax-driven
way, while solely retaining semantics. We show that equivalence networks learn significantly
better semantic vector representations compared to other, existing, neural
network architectures.
Finally, we present an unsupervised machine learning model for mining syntactic
and semantic code idioms. Code idioms are conventional “mental chunks” of code that
serve a single semantic purpose and are commonly used by practitioners. To achieve
this, we employ Bayesian nonparametric inference on tree substitution grammars. We
present a wide range of evidence that the resulting syntactic idioms are meaningful,
demonstrating that they do indeed recur across software projects and that they occur
more frequently in illustrative code examples collected from a Q&A site. These syntactic
idioms can be used as a form of automatic documentation of coding practices
of a programming language or an API. We also mine semantic loop idioms, i.e. highly
abstracted but semantic-preserving idioms of loop operations. We show that semantic
idioms provide data-driven guidance during the creation of software engineering tools
by mining common semantic patterns, such as candidate refactoring locations. This
gives data-based evidence to tool, API and language designers about general, domain
and project-specific coding patterns, who instead of relying solely on their intuition, can
use semantic idioms to achieve greater coverage of their tool or new API or language
feature. We demonstrate this by creating a tool that suggests loop refactorings into
functional constructs in LINQ. Semantic loop idioms also provide data-driven evidence
for introducing new APIs or programming language features
M. Sutton, Charles Maurras et les catholiques français 1890-1914. Nationalisme et positivisme. Traduit de l'anglais par G. Mosseray. Paris, Beauchesne, 1994 (« Bibliothèque Beauchesne Religions Société Politique »)
No full textGoichot Emile. M. Sutton, Charles Maurras et les catholiques français 1890-1914. Nationalisme et positivisme. Traduit de l'anglais par G. Mosseray. Paris, Beauchesne, 1994 (« Bibliothèque Beauchesne Religions Société Politique »). In: Revue d'histoire et de philosophie religieuses, 75e année n°3, Juillet-août-septembre 1995. p. 369
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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