Article
Chemistry, Multidisciplinary
Jia Ren, Nan Xu, Yani Cui
Summary: This paper predicts the path of typhoons formed in the South China Sea based on deep learning, combining the CNN network and the LSTM network to build a C-LSTM typhoon path prediction model. It has been proved that the prediction results of the model have smaller errors compared to the LSTM typhoon path prediction model.
APPLIED SCIENCES-BASEL
(2022)
Article
Mathematics, Applied
Massimiliano Zanin
Summary: We propose a novel methodology based on continuous ordinal patterns to preprocess time series and uncover the non-linear temporal structures within them. Through synthetic and real-world examples, we demonstrate how this transformation overcomes a major limitation of the Granger Causality test and efficiently detects non-linear causality relations without any prior assumptions. We also show that this transformation can be optimized based on the specific time series under study, or random ordinal patterns can be used to achieve good results, similar to Reservoir Computing.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2024)
Article
Operations Research & Management Science
Salma Mefteh-Wali, Hassen Rais, Guillaume Schier
Summary: This paper extends the research on the impact of corporate social responsibility (CSR) on firm risk and discusses the integration of CSR as insurance in global risk management strategy. The empirical analysis on European-listed firms shows a directional causality effect between CSR and idiosyncratic risk, and successful modeling of the dependence structure between them.
ANNALS OF OPERATIONS RESEARCH
(2022)
Review
Mathematics, Applied
Tom Edinburgh, Stephen J. Eglen, Ari Ercole
Summary: Inferring nonlinear and asymmetric causal relationships between multivariate longitudinal data is crucial in various fields such as clinical medicine, mathematical biology, economics, and environmental research. Evaluation of ten prominent causality indices showed strong agreement between methods in general, but they may not always be robust to real-world relevant transformations.
Article
Multidisciplinary Sciences
Manuel Castro, Pedro Ribeiro Mendes Junior, Aurea Soriano-Vargas, Rafael de Oliveira Werneck, Maiara Moreira Goncalves, Leopoldo Lusquino Filho, Renato Moura, Marcelo Zampieri, Oscar Linares, Vitor Ferreira, Alexandre Ferreira, Alessandra Davolio, Denis Schiozer, Anderson Rocha
Summary: In this study, we propose using ensemble models (such as Random Forest) to assess the importance of input features in machine learning models, in order to establish causal relationships between variables. By analyzing oil field production data, we find that our results align with confirmed tracer information, demonstrating the effectiveness of our proposed methodology.
SCIENTIFIC REPORTS
(2023)
Article
Economics
Yijia Zhang, Lu Cheng
Summary: Since 2015, the UK has increased investment in transportation infrastructure to compensate for previous underinvestment. However, there is limited research on the impact of this policy adjustment on economic growth in the UK. This paper investigates the relationship between transport infrastructure development and economic growth in the UK using principal component analysis and Vector Error Correction Model. The results show a long-term positive effect of transportation infrastructure on economic development, but a significantly negative short-term effect.
Article
Economics
Hakon Otneim, Dag Tjostheim
Summary: This article introduces a new measure of conditional dependence called the local Gaussian partial correlation (LGPC). Compared to traditional partial correlation coefficients, LGPC can better describe conditional dependence in a wide range of populations and has some useful and novel properties. LGPC can also be used to study departures from conditional independence in specific parts of the distribution.
JOURNAL OF BUSINESS & ECONOMIC STATISTICS
(2022)
Article
Energy & Fuels
Chaiwat Klinlampu, Namchok Chimprang, Roengchai Tansuchat
Summary: This study investigates the relationship between WTE and representative factors in the social, economic, and environmental dimensions in the EU-28 sample group, and finds that WTE's change has an impact on energy consumption and environmental tax revenue.
Article
Geosciences, Multidisciplinary
Filipi N. Silva, Didier A. Vega-Oliveros, Xiaoran Yan, Alessandro Flammini, Filippo Menczer, Filippo Radicchi, Ben Kravitz, Santo Fortunato
Summary: This study introduces a novel method using Granger causality to study climate system teleconnections, which can recover known seasonal precipitation responses and identify candidates for unexplored teleconnection responses.
GEOPHYSICAL RESEARCH LETTERS
(2021)
Article
Economics
Xian Cheng, Peng Wu, Stephen Shaoyi Liao, Xuelian Wang
Summary: In this study, a two-stage model is proposed to optimize the selection of driving predictors for crude oil price forecasting. The model integrates Granger causality test (GCT) and stochastic frontier analysis (SFA). The empirical results demonstrate that the two-stage model outperforms eight competing models in terms of four forecasting techniques.
Article
Mathematics
Xiuping Ji, Sujuan Wang, Honggen Xiao, Naipeng Bu, Xiaonan Lin
Summary: This study uses the DCC-MGARCH model to examine the contagion effects in financial markets during crises. The findings suggest that the financial crisis and COVID-19 pandemic have increased the connection between the Chinese and US stock markets, with higher dynamic conditional correlations observed during the pandemic compared to the 2008 financial crisis. Additionally, there is a unidirectional contagion effect between the Chinese market and US market, and the Hong Kong stock market contributes to risk spillover.
Article
Business, Finance
Tiago Mota Dutra, Jose Carlos Dias, Joao C. A. Teixeira
Summary: This study identifies share prices as the most accurate proxy for measuring financial cycles through comparing different financial variables. Share prices have a higher predictive capacity for financial and economic crises compared to GDP, which explains the increasing interest of macroprudential policymakers in financial cycles. The conclusions are robust to different time periods and alternative filtering procedures.
INTERNATIONAL REVIEW OF ECONOMICS & FINANCE
(2022)
Article
Green & Sustainable Science & Technology
Yonglian Wang, Lijun Wang, Changchun Pan
Summary: This paper contributes to the tourism-growth literature by using a new vector autoregressive-based Granger causality test to reassess the relationship between tourism and economic growth in Hong Kong. The results indicate that the tourism-led economic growth hypothesis and the economy-driven tourism growth hypothesis are both unstable. However, the vector autoregressive-based Granger causality test shows that there is generally bidirectional causality between tourism and economic growth, with the relationship being vulnerable to major political incidents, public health incidents, and financial crises. Political events have long-term effects on the relationship, while economic policies, financial crises, and public health emergencies have short-term impacts.
Article
Economics
Massimiliano Caporin, Michele Costola
Summary: The analysis of causality between oil prices and financial/economic variables is important in applied economic studies. Lu et al. (2014) propose a new causality test, the DCC-MGARCH Hong test. In order to avoid potential errors, it is necessary to evaluate the critical values of the test statistic through simulations. Rolling Hong tests are a more viable solution for short-lived causality periods.
Article
Green & Sustainable Science & Technology
Zhipeng Zhu, Yuxuan Qiao, Qunyue Liu, Conghua Lin, Emily Dang, Weicong Fu, Guangyu Wang, Jianwen Dong
Summary: The study found that the overall air quality index level in Taipei was good, with PM2.5 being the main pollutant. The AQI values varied in different areas, with downtown Zhongshan > suburbs of Shilin > outskirts of Yangmingshan. There were different dynamic relationships between meteorological factors and AQI in different regions, requiring targeted control and management to improve urban air quality.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2021)
Article
Computer Science, Software Engineering
Andre Hora, Romain Robbes, Marco Tulio Valente, Nicolas Anquetil, Anne Etien, Stephane Ducasse
SOFTWARE QUALITY JOURNAL
(2018)
Article
Computer Science, Software Engineering
Luciana L. Silva, Marco Tulio Valente, Marcelo A. Maia
JOURNAL OF SYSTEMS AND SOFTWARE
(2019)
Article
Computer Science, Software Engineering
Aline Brito, Marco Tulio Valente, Laerte Xavier, Andre Hora
EMPIRICAL SOFTWARE ENGINEERING
(2020)
Article
Computer Science, Information Systems
Jailton Coelho, Marco Tulio Valente, Luciano Milen, Luciana L. Silva
INFORMATION AND SOFTWARE TECHNOLOGY
(2020)
Article
Computer Science, Information Systems
Joao Eduardo Montandon, Marco Tulio Valente, Luciana L. Silva
Summary: This paper investigates machine-learning based approaches to automatically identify the technical roles of open source developers. By building machine-learning models to identify different roles, the study shows that programming languages are the most relevant feature for predicting roles.
INFORMATION AND SOFTWARE TECHNOLOGY
(2021)
Article
Computer Science, Software Engineering
Laerte Xavier, Joao Eduardo Montandon, Fabio Ferreira, Rodrigo Brito, Marco Tulio Valente
Summary: Self-Admitted Technical Debt (Satd) refers to developers reporting their sub-optimal technical solutions through source code comments or labeled issues. The study found that developers introduce technical debt to deliver products faster, with design flaws being the major cause. Additionally, most developers pay off technical debt to reduce its costs or interests. However, the research also discovered that developers are not interested in automatically transforming comments into issues, and it may not be feasible to create a tool to recommend explicit links between comments and issues.
EMPIRICAL SOFTWARE ENGINEERING
(2022)
Article
Computer Science, Software Engineering
Gabriel Darbord, Benoit Verhaeghe, Anne Etien, Nicolas Anquetil, Anas Shatnawi, Abderrahmane Seriai, Mustapha Derras
Summary: This paper presents a collaboration project with Berger-Levrault, an international IT company, to migrate client-server applications to Angular 14 and Spring Boot. It focuses on the migration of client-server communication from RMI and GWT-RPC to REST architectural style and proposes a tool-based approach to address the issues. The migration involves identifying existing services and data structures, migrating the services and data structures on the new client side, and reducing exchanged data if needed. The approach was experimented on four applications currently using RMI or GWT-RPC.
Proceedings Paper
Computer Science, Software Engineering
Mahugnon Honore Houekpetodji, Nicolas Anquetil, Stephane Ducasse, Fatiha Djareddir, Jerome Sudich
Summary: The success of software development companies lies in their ability to deliver high-quality products quickly and adopt agile development practices. The impact of COVID-19 on employees, such as dealing with obsolete technologies and outdated standards during the modernization process, adds extra challenges.
2021 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE AND EVOLUTION (ICSME 2021)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Julien Delplanque, Anne Etien, Nicolas Anquetil, Stephane Ducasse
ADVANCED INFORMATION SYSTEMS ENGINEERING, CAISE 2020
(2020)
Review
Business
Diego Souza Silva, Antonio Ghezzi, Rafael Barbosa de Aguiar, Marcelo Nogueira Cortimiglia, Carla Schwengber ten Caten
INTERNATIONAL JOURNAL OF ENTREPRENEURIAL BEHAVIOR & RESEARCH
(2020)
Proceedings Paper
Automation & Control Systems
Benoit Verhaeghe, Christopher Fuhrman, Latifa Guerrouj, Nicolas Anquetil, Stephane Ducasse
34TH IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING (ASE 2019)
(2019)
Proceedings Paper
Computer Science, Software Engineering
Nicolas Anquetil, Anne Etien, Gaelle Andreo, Stephane Ducasse
2019 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE AND EVOLUTION (ICSME 2019)
(2019)
Proceedings Paper
Computer Science, Software Engineering
Benoit Verhaeghe, Anne Etien, Nicolas Anquetil, Abderrahmane Seriai, Laurent Deruelle, Stephane Ducasse, Mustapha Derras
2019 IEEE 26TH INTERNATIONAL CONFERENCE ON SOFTWARE ANALYSIS, EVOLUTION AND REENGINEERING (SANER)
(2019)
Proceedings Paper
Computer Science, Software Engineering
Julien Delplanque, Anne Etien, Nicolas Anquetil, Olivier Auverlot
PROCEEDINGS 2018 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE AND EVOLUTION (ICSME)
(2018)
Proceedings Paper
Computer Science, Software Engineering
Leonardo Humberto Silva, Marco Tulio Valente, Alexandre Bergel
2017 IEEE 24TH INTERNATIONAL CONFERENCE ON SOFTWARE ANALYSIS, EVOLUTION, AND REENGINEERING (SANER)
(2017)
Review
Computer Science, Software Engineering
Orvila Sarker, Asangi Jayatilaka, Sherif Haggag, Chelsea Liu, M. Ali Babar
Summary: This study provides a comprehensive view of the challenges and critical success factors in the design, implementation, and evaluation stages of phishing education, training, and awareness (PETA). The findings highlight the need to address human-centric issues, bridge users' knowledge gaps, and adopt personalized approaches to enhance defense against phishing attacks.
JOURNAL OF SYSTEMS AND SOFTWARE
(2024)
Article
Computer Science, Software Engineering
Carlos Araujo, Meuse Oliveira Jr., Bruno Nogueira, Paulo Maciel, Eduardo Tavares
Summary: This paper proposes a method based on stochastic Petri nets for evaluating the consistency levels of storage systems based on NoSQL DBMS. The method takes into account different consistency levels and redundant nodes, and estimates the system's availability, throughput, and the probability of accessing the newest data. Experimental results demonstrate the practical feasibility of this approach.
JOURNAL OF SYSTEMS AND SOFTWARE
(2024)
Review
Computer Science, Software Engineering
L. Giamattei, A. Guerriero, R. Pietrantuono, S. Russo, I. Malavolta, T. Islam, M. Dinga, A. Koziolek, S. Singh, M. Armbruster, J. M. Gutierrez-Martinez, S. Caro-Alvaro, D. Rodriguez, S. Weber, J. Henss, E. Fernandez Vogelin, F. Simon Panojo
Summary: This article presents the results of a systematic study on the available monitoring tools for DevOps and microservices. It provides a classification and analysis of these tools, aiming to be a useful reference for researchers and practitioners in this field.
JOURNAL OF SYSTEMS AND SOFTWARE
(2024)
Article
Computer Science, Software Engineering
Jessica Diaz, Jorge Perez, Isaque Alves, Fabio Kon, Leonardo Leite, Paulo Meirelles, Carla Rocha
Summary: This paper presents empirical research on the structure of DevOps teams in software-producing organizations to better understand the organizational structure and characteristics of teams adopting DevOps. A theory of DevOps taxonomies is built through analysis, and its consistency with other taxonomies is tested.
JOURNAL OF SYSTEMS AND SOFTWARE
(2024)
Article
Computer Science, Software Engineering
Sinan Sigurd Tanilkan, Jo Erskine Hannay
Summary: When deciding to develop new software, it is important to have a clear understanding of the intended benefits. However, our research shows that stakeholders' understanding of benefits often fluctuates during the development process, leading to uncertainty. Therefore, we recommend focusing on helping practitioners embrace changes in their understanding of benefits.
JOURNAL OF SYSTEMS AND SOFTWARE
(2024)
Article
Computer Science, Software Engineering
Pingyan Wang, Shaoying Liu, Ai Liu, Wen Jiang
Summary: This paper presents an approach that combines static analysis tools and manual audits to effectively detect various types of security vulnerabilities. By using a special Petri net representation, the proposed method is able to assist in the detection of taint-style vulnerabilities.
JOURNAL OF SYSTEMS AND SOFTWARE
(2024)
Article
Computer Science, Software Engineering
Edgar Sarmiento-Calisaya, Julio Cesar Sampaio do Prado Leite
Summary: This research introduces an automated requirements analysis approach that combines natural language processing, Petri-nets, and visualization techniques to improve the quality of scenario-based specifications, identify defects, and anticipate inconsistencies.
JOURNAL OF SYSTEMS AND SOFTWARE
(2024)
Article
Computer Science, Software Engineering
Jian Hu
Summary: This paper proposes a two-stage trace matrix optimization method for fault localization, which addresses the challenges of coincidental correctness and data imbalance in the current trace matrix. Through extensive experiments, significant improvements in fault localization effectiveness are demonstrated.
JOURNAL OF SYSTEMS AND SOFTWARE
(2024)
Article
Computer Science, Software Engineering
Fan Zhang, Manman Peng, Yuanyuan Shen, Qiang Wu
Summary: This study proposes a novel method called HFEDR that utilizes the hierarchical features of Transformer models and reorganizes training data to improve code search performance. Experimental results demonstrate the effectiveness and rationality of the proposed approach.
JOURNAL OF SYSTEMS AND SOFTWARE
(2024)
Article
Computer Science, Software Engineering
Tong Wang, Bixin Li
Summary: Software architecture erosion has a negative impact on software quality, performance, and evolution cost. This paper proposes an approach called EsArCost to locate the causes of architecture erosion and estimate the repair cost of each erosion problem. Experimental results show that EsArCost can effectively and efficiently estimate repair costs.
JOURNAL OF SYSTEMS AND SOFTWARE
(2024)
Article
Computer Science, Software Engineering
Xiajing Wang, Rui Ma, Wei Huo, Zheng Zhang, Jinyuan He, Chaonan Zhang, Donghai Tian
Summary: This paper proposes a new potential-aware fuzzing scheme called SYNTONY that measures seed potential using multiple objectives and prioritizes promising seeds to increase the number of unique crashes and coverage. Experimental results show that SYNTONY outperforms other fuzzing tools and has high compatibility and expansibility.
JOURNAL OF SYSTEMS AND SOFTWARE
(2024)
Article
Computer Science, Software Engineering
Stefano Lambiase, Gemma Catolino, Fabiano Pecorelli, Damian A. Tamburri, Fabio Palomba, Willem-Jan van den Heuvel, Filomena Ferrucci
Summary: This paper contributes to the existing body of knowledge on factors affecting productivity in software development by studying the cultural and geographical dispersion of a development community. The results show that cultural and geographical dispersion significantly impact productivity, suggesting that managers and practitioners should consider these aspects throughout the software development lifecycle.
JOURNAL OF SYSTEMS AND SOFTWARE
(2024)
Article
Computer Science, Software Engineering
Elaine Venson, Bradford Clark, Barry Boehm
Summary: The software industry has been under pressure to adopt security practices and reduce software vulnerabilities. This study quantifies the effort required to develop secure software in increasing levels of rigor and scope and provides validated cost multipliers for practitioners to estimate proper resources for adopting security practices.
JOURNAL OF SYSTEMS AND SOFTWARE
(2024)
Article
Computer Science, Software Engineering
Yangyang Zhao, Mingyue Jiang, Yibiao Yang, Yuming Zhou, Hanjie Ma, Zuohua Ding
Summary: Previous studies have ignored the potential associations between modules involved in the same defect, and this comprehensive study explores the implications of intra-defect associations for defect prediction. The majority of defects occur across functions, with implicit dependencies between the modules. By considering intra-defect associations and merging modules, the proposed data processing approach significantly improves defect prediction performance.
JOURNAL OF SYSTEMS AND SOFTWARE
(2024)
Article
Computer Science, Software Engineering
Meira Levy, Irit Hadar
Summary: This research sheds new light on how students learn and practice hybrid work in educational settings through two educational studies. The findings show the benefits of new educational programs in fostering empathy and innovation among students, while also highlighting the challenges and opportunities in addressing real challenges.
JOURNAL OF SYSTEMS AND SOFTWARE
(2024)