1,720,974 research outputs found
Virtual Assistant
No full textThis document is the final report of the Virtual Assistant application, which has been given AssisTU as a project name, a Bachelor Final Project performed by Arnaud Hambenne and Soheil Jahanshahi in assignment of the TU Delft Library. The AssisTU application is created to help students write academic documents.Computer Science & EngineeringElectrical Engineering, Mathematics and Computer Scienc
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
fine-GRAPE: Fine-Grained APi usage Extractor An Approach and Dataset to Investigate API Usage
No full textAn Application Programming Interface (API) provides a specific set of functionalities to a developer, with the aim of enabling reuse. APIs have been investigated from different angles such as popularity usage and evolution, to get a better understanding of their various characteristics. For such studies software repositories are mined for API usage examples. However, the mining algorithms used for such purposes do not take type information into account, thus making the results imprecise. In this thesis, we aim to rectify this by introducing fine-GRAPE, an approach that produces fine-grained API usage information by taking advantage of type information while mining API method invocations and annotations. fine-GRAPE establishes a connection between a method invocation and the class of the API to which the method belongs. By means of fine-GRAPE, we investigate API usages from Java projects hosted on GitHub. We select five of the most popular APIs across GitHub Java projects and collect historical API usage information by mining both the release history of these APIs and the code history of every project that uses them. We use the resulting dataset to perform four separate analyses. The first measures the lag time of each client by leveraging the version information that has been collected. We see that in most cases clients do not upgrade the version of the API that they are using to the latest version. The consequence of this is that the lag time that each client displays is quite high. The second study investigates the percentage of API features that are used by using the type information in the dataset. The results of this study show that a very small percentage of an API is actually used by clients in the real world. Our third study aims to show the relation between popular features and software quality. Finally, the fourth study analyzes the reaction of clients to the deprecation of API artifacts. Our deprecation study shows that most clients do not really react to deprecated entities.Software EngineeringElectrical Engineering, Mathematics and Computer Scienc
Empirical Software Linguistics: An Investigation of Code Reviews, Recommendations and Faults
No full textCommunication is fundamental to human nature and underlies many of its successes as a species. In recent decades, the adoption of increasingly abstract software languages has supported many advances in computer science and software engineering. Although in many regards distinct from natural language, software language has proven surprisingly similar to it as well and has been studied successfully using natural language models. Recent studies have investigated this "naturalness" property of software in relation to a variety of applications including code completion, fault detection, and language migration. In this thesis, based on three research papers, we investigate three main aspects of software naturalness. Firstly, we investigate the relation between perceived (un)naturalness of source code (according to the statistical model) and the reaction to such code by software developers. In open-source projects, we find that those contributions which contain code that (statistically speaking) fits in less well are also subject to more scrutiny from reviewers and are rejected more often. Secondly, we investigate an application of highly predictable code: code completion. Previous work had evaluated the performance of language models in this application in isolation; we compare the language model approach to a commonly used code completion engine. We find that it compares favorably, achieving substantially higher accuracy scores. In particular, a combination of the two approaches yielded the best results. Finally, we investigate instances of highly unpredictable code in order to automatically detect faults. We find that buggy lines of code are substantially less predictable, becoming more predictable after a bug is fixed. Our bug detection approach yields performance comparable to popular static bug finders, such as FindBugs and PMD. Our results further confirm that statistical (ir)regularity of source code from a natural language perspectives reflects real-world phenomena.Software EngineeringComputer ScienceElectrical Engineering, Mathematics and Computer Scienc
Variations on the Author
Get PDF“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
Octopull: Integrating Static Analysis with Code Reviews
No full textTeams using modern day software engineering practices often incorporate code reviews as a quality assurance step in their development. These code reviews are intended to uncover software quality defects before code changes are incorporated into the project. Certain classes of these software quality defects can be detected by so-called static analysis tools. These tools have seen increasing uptake and are found to be effective at finding relevant quality defects in these classes. Several tools to integrate the static analysis results into code review have been created, such as SCRUB and Review Bot. However, these tools were created specifically for internally used platforms and their source is not made available. In this thesis, we propose and implement a tool called Octopull, which is an open-source implementation that incorporates static analysis results in the user-interface of the GitHub platform. We evaluate the tool by performing a user-study on undergraduate students. Our study shows no significant effect of using the tool on the effectiveness of their code review sessions.Software EngineeringElectrical Engineering, Mathematics and Computer Scienc
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe 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
Get PDFWe 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
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