Hasil untuk "French literature - Italian literature - Spanish literature - Portuguese literature"

Edvaldo Wassouf, Débora Paiva, Kiev Gama et al.

Research on underrepresented populations is essential for fostering greater diversity within the software industry. Team diversity is important for reasons that go beyond ethics. Diversity contributes to greater innovation and productivity, helping decrease turnover rates and reduce team conflicts. Within this context, LGBTQIA+ software engineering professionals face unique challenges, e.g., self-isolation and invisibility feeling. Developer Experience (DX) encompasses cognitive, emotional, and motivational considerations, supporting the idea that improving how DX can enhance team performance, strengthen collaboration, and lead to more successful software projects. This study aimed to examine traditional and grey literature data through a Multivocal Literature Review focused on the DX of LGBTQIA+ professionals in agile teams. Our findings reveal that issues such as invisibility, prejudice, and discrimination adversely affect their experiences, compounded by the predominance of heterosexual males in the field. Conversely, professionals who feel welcomed by their teams and organizations, especially in processes tailored to their needs, report more positive team dynamics and engagement.

Jungsoo Park, Junmo Kang, Gabriel Stanovsky et al.

The surge of LLM studies makes synthesizing their findings challenging. Analysis of experimental results from literature can uncover important trends across studies, but the time-consuming nature of manual data extraction limits its use. Our study presents a semi-automated approach for literature analysis that accelerates data extraction using LLMs. It automatically identifies relevant arXiv papers, extracts experimental results and related attributes, and organizes them into a structured dataset, LLMEvalDB. We then conduct an automated literature analysis of frontier LLMs, reducing the effort of paper surveying and data extraction by more than 93% compared to manual approaches. We validate LLMEvalDB by showing that it reproduces key findings from a recent manual analysis of Chain-of-Thought (CoT) reasoning and also uncovers new insights that go beyond it, showing, for example, that in-context examples benefit coding & multimodal tasks but offer limited gains in math reasoning tasks compared to zero-shot CoT. Our automatically updatable dataset enables continuous tracking of target models by extracting evaluation studies as new data becomes available. Through LLMEvalDB and empirical analysis, we provide insights into LLMs while facilitating ongoing literature analyses of their behavior.

Adrian Farid Freja de la Hoz

Este artículo analiza las adaptaciones del relato grecolatino de Cupido y Psique en la tradición oral campesina colombiana. Se destaca cómo esta narrativa clásica, que ha sido transformada y apropiada en diferentes contextos culturales, ha encontrado variaciones significativas en Colombia. Estas adaptaciones son entendidas como “topologías literarias”, un concepto que resalta las dependencias entre las versiones locales de las obras literarias tradicionales y los territorios específicos donde se desarrollan. El texto explora cómo estas versiones se alejan de la narrativa original de Apuleyo, incorporando elementos propios de la cultura y geografía colombianas. Asimismo, el artículo subraya la importancia de la oralidad en la transmisión de estos relatos, lo que permite una constante actualización y reelaboración de las historias según los valores y necesidades de cada comunidad.

Calderaro, Michela A.

Review of Goodison, L. (2025). Dante's Inferno. A New Translation. Manchester: Carcanet Classics, 224 pp.

Ali Kazemi Arani, Triet Huynh Minh Le, Mansooreh Zahedi et al.

Context: Machine learning (ML) and deep learning (DL) analyze raw data to extract valuable insights in specific phases. The rise of continuous practices in software projects emphasizes automating Continuous Integration (CI) with these learning-based methods, while the growing adoption of such approaches underscores the need for systematizing knowledge. Objective: Our objective is to comprehensively review and analyze existing literature concerning learning-based methods within the CI domain. We endeavour to identify and analyse various techniques documented in the literature, emphasizing the fundamental attributes of training phases within learning-based solutions in the context of CI. Method: We conducted a Systematic Literature Review (SLR) involving 52 primary studies. Through statistical and thematic analyses, we explored the correlations between CI tasks and the training phases of learning-based methodologies across the selected studies, encompassing a spectrum from data engineering techniques to evaluation metrics. Results: This paper presents an analysis of the automation of CI tasks utilizing learning-based methods. We identify and analyze nine types of data sources, four steps in data preparation, four feature types, nine subsets of data features, five approaches for hyperparameter selection and tuning, and fifteen evaluation metrics. Furthermore, we discuss the latest techniques employed, existing gaps in CI task automation, and the characteristics of the utilized learning-based techniques. Conclusion: This study provides a comprehensive overview of learning-based methods in CI, offering valuable insights for researchers and practitioners developing CI task automation. It also highlights the need for further research to advance these methods in CI.

Roman Bögli, Leandro Lerena, Christos Tsigkanos et al.

TLA+ is a formal specification language used for designing, modeling, documenting, and verifying systems through model checking. Despite significant interest from the research community, knowledge about usage of the TLA+ ecosystem in practice remains scarce. Industry reports suggest that software engineers could benefit from insights, innovations, and solutions to the practical challenges of TLA+. This paper explores this development by conducting a systematic literature review of TLA+'s industrial usage over the past decade. We analyze the trend in industrial application, characterize its use, examine whether its promised benefits resonate with practitioners, and identify challenges that may hinder further adoption.

Stefan Graser, Stephan Böhm

Augmented Reality (AR) is an emerging technology that ranks among the top innovations in interactive media. With the emergence of new technologies, the question about the factors influencing user acceptance arises. Many research models on the user acceptance of technologies were developed and extended to answer this question in the last decades. This research paper provides an overview of the current state in the scientific literature on user acceptance factors of AR in training and education. We conducted a systematic literature review, identifying 45 scientific papers on technology acceptance of augmented reality. Twenty-two papers refer more specifically to the field of training and education. Overall, 33 different technology acceptance models and 34 acceptance variables were identified. Based on the results, there is a great potential for further research.

Akari Asai, Jacqueline He, Rulin Shao et al.

Scientific progress depends on researchers' ability to synthesize the growing body of literature. Can large language models (LMs) assist scientists in this task? We introduce OpenScholar, a specialized retrieval-augmented LM that answers scientific queries by identifying relevant passages from 45 million open-access papers and synthesizing citation-backed responses. To evaluate OpenScholar, we develop ScholarQABench, the first large-scale multi-domain benchmark for literature search, comprising 2,967 expert-written queries and 208 long-form answers across computer science, physics, neuroscience, and biomedicine. On ScholarQABench, OpenScholar-8B outperforms GPT-4o by 5% and PaperQA2 by 7% in correctness, despite being a smaller, open model. While GPT4o hallucinates citations 78 to 90% of the time, OpenScholar achieves citation accuracy on par with human experts. OpenScholar's datastore, retriever, and self-feedback inference loop also improves off-the-shelf LMs: for instance, OpenScholar-GPT4o improves GPT-4o's correctness by 12%. In human evaluations, experts preferred OpenScholar-8B and OpenScholar-GPT4o responses over expert-written ones 51% and 70% of the time, respectively, compared to GPT4o's 32%. We open-source all of our code, models, datastore, data and a public demo.

Gauri Shankar, Md Raihan Uddin, Saddam Mukta et al.

Blockchain technology is an emerging digital innovation that has gained immense popularity in enhancing individual security and privacy within Information Systems (IS). This surge in interest is reflected in the exponential increase in research articles published on blockchain technology, highlighting its growing significance in the digital landscape. However, the rapid proliferation of published research presents significant challenges for manual analysis and synthesis due to the vast volume of information. The complexity and breadth of topics, combined with the inherent limitations of human data processing capabilities, make it difficult to comprehensively analyze and draw meaningful insights from the literature. To this end, we adopted the Computational Literature Review (CLR) to analyze pertinent literature impact and topic modelling using the Latent Dirichlet Allocation (LDA) technique. We identified 10 topics related to security and privacy and provided a detailed description of each topic. From the critical analysis, we have observed several limitations, and several future directions are provided as an outcome of this review.

Renata Ferreira Costa

Este artigo apresenta uma investigação dos documentos de natureza autobiográfica contidos no arquivo pessoal do escritor sergipano Manuel dos Passos de Oliveira Telles, atualmente preservado no Fundo Oliveira Telles do Instituto Histórico e Geográfico de Sergipe, batizado de Dossiê Autobiográfico. Composto por uma variedade de textos, o dossiê oferece fragmentos de memória e confissões que revelam como o autor se via e se sentia, desempenhando um papel fundamental na determinação de sua identidade pessoal e literária. A abordagem metodológica deste trabalho é fundamentada em teorias relativas aos arquivos pessoais e à escrita autobiográfica. Essa base teórica proporciona um quadro conceitual sólido para a análise do dossiê, possibilitando uma compreensão do estilo do autor, de sua análise crítica social, das características de sua subjetividade e da construção de uma imagem pública. Ademais, a pesquisa lança luz sobre a importância dos arquivos pessoais e dos documentos autobiográficos como fontes valiosas para a pesquisa histórica e literária. Os resultados evidenciam a relevância do estudo dos documentos autobiográficos para desvendar os processos de construção identitária de escritores e para enriquecer o panorama da história e literatura regionais.

Rosalba Lendo Fuentes

El presente artículo analiza el desarrollo del destino del rey Arturo en el Otro Mundo y las distintas representaciones de este lugar feérico (Avalón, la Isla Encantada, el universo maravilloso bajo el agua en la Laguna Blanca, las entrañas de la tierra en el Etna o en la cima de una montaña), a partir de las alusiones de Geoffrey de Monmouth en la Vita Merlini, que encontramos también en textos de los siglos XII y XIII , como el Draco Normanicus de Étienne de Rouen, Otia Imperalia de Gervasio de Tilbury, los ciclos artúricos franceses (la trilogía atribuida a Robert de Boron, la Vulgata y la Post-Vulgata), y sus adaptaciones castellanas, así como en algunos textos españoles que desarrollaron el tema de distintas maneras, como La faula de Guillem de Torroella, Florambel de Francisco Enciso Zárate, y Espejo de caballerías de Pedro López de Santa Catalina.

Saara Tenhunen, Tomi Männistö, Matti Luukkainen et al.

Tertiary education institutions aim to prepare their computer science and software engineering students for working life. While much of the technical principles are covered in lower-level courses, team-based capstone projects are a common way to provide students with hands-on experience and teach soft skills. This paper explores the characteristics of software engineering capstone courses presented in the literature. The goal of this work is to understand the pros and cons of different approaches by synthesising the various aspects of software engineering capstone courses and related experiences. In a systematic literature review for 2007-2022, we identified 127 primary studies. These studies were analysed based on their presented course characteristics and the reported course outcomes. The characteristics were synthesised into a taxonomy consisting of duration, team sizes, client and project sources, project implementation, and student assessment. We found out that capstone courses generally last one semester and divide students into groups of 4-5 where they work on a project for a client. For a slight majority of courses, the clients are external to the course staff and students are often expected to produce a proof-of-concept level software product as the main end deliverable. The courses also offer versatile assessments for students throughout the project. This paper provides researchers and educators with a classification of characteristics of software engineering capstone courses based on previous research. We further synthesise insights on the reported outcomes of capstone courses. Our review study aims to help educators to identify various ways of organising capstones and effectively plan and deliver their own capstone courses. The characterisation also helps researchers to conduct further studies on software engineering capstones.

Federico Quin, Danny Weyns, Matthias Galster et al.

In A/B testing two variants of a piece of software are compared in the field from an end user's point of view, enabling data-driven decision making. While widely used in practice, no comprehensive study has been conducted on the state-of-the-art in A/B testing. This paper reports the results of a systematic literature review that analyzed 141 primary studies. The results shows that the main targets of A/B testing are algorithms and visual elements. Single classic A/B tests are the dominating type of tests. Stakeholders have three main roles in the design of A/B tests: concept designer, experiment architect, and setup technician. The primary types of data collected during the execution of A/B tests are product/system data and user-centric data. The dominating use of the test results are feature selection, feature rollout, and continued feature development. Stakeholders have two main roles during A/B test execution: experiment coordinator and experiment assessor. The main reported open problems are enhancement of proposed approaches and their usability. Interesting lines for future research include: strengthen the adoption of statistical methods in A/B testing, improving the process of A/B testing, and enhancing the automation of A/B testing.

Andreas G. Koutoupis, Christos G. Kampouris, Athanasia V. Sakellaridou

Research Question: Can the F-Score predict the stock market returns in the cross section of international stock markets? Motivation: The majority of the literature, in the area of the F-Score metric, has examined whether it can be used to predict future financial profitability, the relationship of F-Score with book-to-value metrics and the momentum premium and whether it can be used as a successful investment strategy tool. There only three studies that examine the relationship between the F-Score and future stock returns, without the use of complementary variables, and in other countries except Europe. This paper seeks to fill this gap. Data: The dataset of the present research consists of listed European companies from 21 countries (in random order: Finland, United Kingdom, Switzerland, Turkey, Hungary, Portugal, Spain, Poland, Norway, Luxembourg, Italy, Netherlands, Ireland, Greece, Belgium Germany, Denmark, France Czech Republic, Sweden, Austria), from 1989 to 2016. We collect firm-level accounting information as provided by Worldscope, as well as the monthly total returns for common stocks from Datastream. Tools: With the use of a dataset consisting of European companies from 21 countries, portfolio analysis and time series regressions are performed using abnormal monthly returns (monthly returns minus risk-free interest rates). Findings: We find that the F-Score is a statistically significant predictor as well as an economically meaningful index. Its performance forecasting ability is visible in developed Europe, both in small and large companies, and remains stable after controlling for established cross-sectional determinants (such as book market, investment, and company size). Contribution: This study seeks to fill the gap in the stock return and F-Score relationship in a European setting controlling for the other financial variables. Our empirical models are tested across a number of different economic and stock market backgrounds and the implications of our results are of particular interest for academics, for investors (retail and institutional) and for policy makers.

Lucas Francisco da Matta Vegi, Marco Tulio Valente

Elixir is a new functional programming language whose popularity is rising in the industry. However, there are few works in the literature focused on studying the internal quality of systems implemented in this language. Particularly, to the best of our knowledge, there is currently no catalog of code smells for Elixir. Therefore, in this paper, through a grey literature review, we investigate whether Elixir developers discuss code smells. Our preliminary results indicate that 11 of the 22 traditional code smells cataloged by Fowler and Beck are discussed by Elixir developers. We also propose a list of 18 new smells specific for Elixir systems and investigate whether these smells are currently identified by Credo, a well-known static code analysis tool for Elixir. We conclude that only two traditional code smells and one Elixir-specific code smell are automatically detected by this tool. Thus, these early results represent an opportunity for extending tools such as Credo to detect code smells and then contribute to improving the internal quality of Elixir systems.

Mariam Guizani

Information Architecture (IA) is a blueprint for the information system in websites or other information-rich environments. It corresponds to how we organize, label and structure information. The importance of Information Architecture and its influence on a system's usability is vastly discussed in literature. Because of the inherent connection between Information Architecture concepts and the Human Computer Interaction (HCI) field, we decided to investigate how previous research has used Information Architecture in the context of Human Computer Interaction (IAinHCI). In order to do that, we followed a two phase process. First, we conducted a Systematic Literature Review (SLR). We queried both the ACM and IEEE databases. We filtered and assessed 311 papers that spanned a decade of research on Information Architecture. We found 25 papers that utilized Information Architecture in the context of Human Computer Interaction. Then, we followed a Background Reference Search process using the SLR resulting papers as a starting set. We assessed the eligibility of the reference list of all 25 papers and found eight additional papers that were relevant to our research question. Results of our review show that, IAinHCI papers fall under seven main categories, from IoT to the semantic web and ubiquitous technology. The website category, however, was both the most consistent over the years and the most prevalent category accounting for 67% of the papers. Our findings suggest that IA has not yet uncovered its full potential and there is still room for research to leverage and expend the IA knowledge base promising a prosperous future for Information Architecture.

Anderson Yoshiaki Iwazaki, Vinicius dos Santos, Katia Romero Felizardo et al.

Graduate courses can provide specialized knowledge for Ph.D. and Master's students and contribute to develop their hard and soft skills. At the same time, Systematic Literature Review (SLR) has been increasingly adopted in the computing area as a valuable technique to synthesize the state of the art of a given research topic. However, there is still a poor understanding of the real benefits and drawbacks of offering the SLR course for graduate students. This paper reports an experience that examines such benefits and drawbacks, the difficulties for professors (i.e., educators), and the essential SLR topics to be taught as well as a way to better teach them. We also surveyed computer science graduate students who attended the SLR course, which we have offered for almost ten years for Ph.D. and Master's students in our institution. We found the attendance to the SLR course is a valuable opportunity for graduate students to conduct the required deep literature review of their research topic, improve their research skills, and increase their formation. Hence, we recommend that Ph.D. and Masters' programs offer the SLR course to contribute to their academic achievement.

Nicolas Six, Nicolas Herbaut, Camille Salinesi

A software pattern is a reusable solution to address a commonly occurring problem within a given context when designing software. Using patterns is a common practice for software architects to ensure software quality. Many pattern collections have been proposed for a large number of application domains. However, because of the technology's recentness, there are only a few available collections with a lack of extensive testing in industrial blockchain applications. It is also difficult for software architects to adequately apply blockchain patterns in their applications, as it requires deep knowledge of blockchain technology. Through a systematic literature review, this paper has identified 120 unique blockchain-related patterns and proposes a pattern taxonomy composed of multiple categories, built from the extracted pattern collection. The purpose of this collection is to map, classify, and describe all available patterns across the literature to help readers make adequate decisions regarding blockchain pattern selection. This study also shows potential applications of those patterns and identifies the relationships between blockchain patterns and other non-blockchain software patterns.

Fernando García Naharro

Introducción al dossier.

Almudena Mata-Núñez

En el presente trabajo se examinan las razones que han llevado a las relaciones de sucesos a ser consideradas literatura marginal y, por tanto, a encontrarse fuera del canon literario medieval. La exposición teórica se ejemplifica con la edición, el análisis de la producción y del contenido de la Relación breve del raro y lastimoso caso que sucedió en la isla de San Miguel, en dos de setiembre, lunes a mediodía después de comer.