1,720,958 research outputs found
Rubbing salt in the wound? A large-scale investigation into the effects of refactoring on security
No full textSoftware refactoring is a behavior-preserving activity to improve the source code quality without changing its external behavior. Unfortunately, it is often a manual and error-prone task that may induce regressions in the source code. Researchers have provided initial compelling evidence of the relation between refactoring and defects, yet little is known about how much it may impact software security. This paper bridges this knowledge gap by presenting a large-scale empirical investigation into the effects of refactoring on the security profile of applications. We conduct a three-level mining software repository study to establish the impact of 14 refactoring types on (i) security-related metrics, (ii) security technical debt, and (iii) the introduction of known vulnerabilities. The study covers 39 projects and a total amount of 7,708 refactoring commits. The key results show that refactoring has a limited connection to security. However, Inline Method and Extract Interface statistically contribute to improving some security aspects connected to encapsulating security-critical code components. Extract Superclass and Pull Up Attribute refactoring are commonly found in commits violating specific security best practices for writing secure code. Finally, Extract Superclass and Extract & Move Method refactoring tend to occur more often in commits contributing to the introduction of vulnerabilities. We conclude by distilling lessons learned and recommendations for researchers and practitioners
Toward Understanding the Impact of Refactoring on Program Comprehension
No full textSoftware refactoring is the activity associated with developers changing the internal structure of source code without modifying its external behavior. The literature argues that refactoring might have beneficial and harmful implications for software maintainability, primarily when performed without the support of automated tools. This paper continues the narrative on the effects of refactoring by exploring the dimension of program comprehension, namely the property that describes how easy it is for developers to understand source code. We start our investigation by assessing the basic unit of program comprehension, namely program readability. Next, we set up a large-scale empirical investigation - conducted on 156 open-source projects - to quantify the impact of refactoring on program readability. First, we mine refactoring data and, for each commit involving a refactoring, we compute (i) the amount and type(s) of refactoring actions performed and (ii) eight state-of-the-art program comprehension metrics. Afterwards, we build statistical models relating the various refactoring operations to each of the readability metrics considered to quantify the extent to which each refactoring impacts the metrics in either a positive or negative manner. The key results are that refactoring has a notable impact on most of the readability metrics considered
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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