1,721,251 research outputs found
CVS-Vintage: A dataset of 14 CVS repositories of java software
Get PDF<p>CVS-Vintage is a dataset of 14 CVS repositories of Java applications. This dataset aims at supporting the replication of early papers in the field of software evolution and mining software repositories. By building this dataset, we saved some CVS repositories from a probable death by deletion.</p>
<pre>@techreport{monperrus:hal-00769121,
title = {CVS-Vintage: A Dataset of 14 CVS Repositories of Java Software},
author = {Monperrus, Martin and Martinez, Matias},
url = {https://hal.archives-ouvertes.fr/hal-00769121/file/paper.pdf},
year = {2012},
number = {hal-00769121},
institution = {HAL},
}</pre>
<p>A Git version is available at https://github.com/monperrus/cvs-vintage/</p>
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
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
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
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
Automatic program repair for breaking dependency updates with large language models
Get PDFLAUREA MAGISTRALELe librerie esterne sono ampiamente utilizzate per accelerare lo sviluppo software. Tuttavia, come qualsiasi componente software, vengono aggiornate nel tempo, introducendo nuove funzionalità e sconsigliando o rimuovendo quelle obsolete. Quando una libreria introduce cambiamenti non retro-compatibili (breaking changes), tutti i suoi client devono essere aggiornati per evitare errori o bug. Questo aggiornamento è definito Breaking Dependency Update. Risolvere tali errori è complesso e richiede tempo, poiché l'errore ha origine nella libreria, mentre la correzione deve essere applicata al codice del client.
L'Automatic Program Repair (APR) è un'area di ricerca focalizzata sullo sviluppo di tecniche per correggere errori di codice senza intervento umano. Con l'avvento dei Large Language Models (LLM), le tecniche APR basate sull'apprendimento automatico hanno notevolmente migliorato le attività di riparazione del software. Tuttavia, la loro efficacia sui Breaking Dependency Updates rimane inesplorata.
Questa tesi mira a indagare l'efficacia di un approccio APR basato su LLM nei Breaking Dependency Updates e a esaminare l'impatto dei diversi componenti sulle prestazioni e sull'efficienza del modello. L'attenzione è rivolta alle differenze di API tra le varie versioni della dipendenza e a una serie di strategie di risoluzione specifiche per tipo di errore.
Gli esperimenti condotti su un sottoinsieme di BUMP, un nuovo benchmark per i Breaking Dependency Updates con un forte focus su errori in fase di compilazione, dimostrano che l'approccio tipicamente usato in APR è insufficiente per questo tipo di errori. È necessario un contesto aggiuntivo relativo alle modifiche della dipendenza. Inoltre, strategie di risoluzione specifiche per tipo di errore sono essenziali per superare alcuni ostacoli che impediscono allo strumento di riparare completamente i progetti.
Infine, la nostra ricerca ha rilevato che GPT-4, Gemini e Llama mostrano livelli di efficacia simili, ma differiscono significativamente in termini di efficienza dei costi, con GPT-4 che presenta il costo più elevato per errore riparato tra i modelli testati, risultando quasi 30 volte superiore a Gemini.External libraries are widely used to expedite software development, but like any software component, they are updated over time, introducing new features and deprecating or removing old ones. When a library introduces breaking changes, all its clients must be updated to avoid disruptions. This update, when it introduces a breaking change, is defined as a Breaking Dependency Update. Repairing such breakages is challenging and time-consuming because the error originates in the dependency, while the fix must be applied to the client codebase. Automatic Program Repair (APR) is a research area focused on developing techniques to repair code failures without human intervention. With the advent of Large Language Models (LLMs), learning-based APR techniques have significantly improved in software repair tasks. However, their effectiveness on Breaking Dependency Updates remains unexplored. This thesis aims to investigate the efficacy of an LLM-based APR approach to Breaking Dependency Updates and to examine the impact of different components on the model’s performance and efficiency. The focus is on the API differences between the old and new versions of the dependency and a set of error-type specific repair strategies. Experiments conducted on a subset of BUMP, a new benchmark for Breaking Dependency Updates, with a strong focus on build failures, demonstrate that a naive approach to these client breakages is insufficient. Additional context from the dependency changes is necessary. Furthermore, error-type specific repair strategies are essential to repair some blocking failures that prevent the tool from completely repairing the projects. Finally, our research found that GPT-4, Gemini, and Llama exhibit similar efficacy levels but differ significantly in cost-efficiency, with GPT-4 having the highest cost per repaired failure among the tested models, almost 30 times higher than Gemini
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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