Search · four archives
Search · four archives
20 papers · ranked by Valyu relevance
Quentin Perez, Christelle Urtado, Sylvain Vauttier
Developers are extracted from 17 open-source projects from GitHub. Projects are chosen that use the java programming language, the Spring framework and Maven/Gradle build tools. Along with these developers, 24 software engineering metrics are extracted for each of them. These metrics are either calculated by analyzing…
Ozren Dabić, Rosalia Tufano, Gabriele Bavota
Pre-Processing Authors: ['Ozren Dabić' 'Rosalia Tufano' 'Gabriele Bavota'] Abstract—Large-scale code datasets have acquired an increasingly central role in software engineering (SE) research. This is the result of (i) the success of the mining software repositories (MSR) community, that pushed the standards of…
Arjumand Fatima, Onaiza Maqbool
Developer discussions particularly on programming related questions answering (Q&A) sites, contain useful information, which, if mined and analysed carefully can be transformed into insightful recommendations for developers about which software to use or prefer over others, matching with one’s requirements for…
Fahad H. Alshammari
In recent years, numerous studies have successfully implemented machine learning strategies in a wide range of application areas. Therefore, several different deep learning models exist, each one tailored to a certain software task. Using deep learning models provides numerous advantages for the software development…
Hao-Nan Zhu, Robert M. Furth, Michael Pradel, Cindy Rubio-González
Software defect datasets, which are collections of software bugs and their associated information, are essential resources for researchers and practitioners in software engineering and beyond. Such datasets facilitate empirical research and enable standardized benchmarking for a wide range of techniques, including…
Ratnadira Widyasari, Zhou Yang, Ferdian Thung, Sheng Qin Sim + 7 more
'Fiona Wee' 'Camellia Lok' 'Jack Phan' 'Haodi Qi' 'Constance Tan' 'Qijin Tay' 'David Lo'] Abstract—Machine learning (ML) has gained much attention and been incorporated into our daily lives. While there are numerous publicly available ML projects on open source platforms such as GitHub, there have been limited attempts…
Zeeshan Anwar, Hammad Afzal, Naima Altaf, Seifedine Kadry + 2 more
Software engineers post their opinions about various topics on social media that can be collectively mined using Sentiment Analysis. Analyzing this opinion is useful because it can provide insight into developers’ feedback about various tools and topics. General-purpose sentiment analysis tools do not work well in the…
Yanming Yang, Xin Xia, David Lo, Tingting Bi + 2 more
'Xiaohu Yang'] Predictive models are one of the most important techniques that are widely applied in many areas of software engineering. There have been a large number of primary studies that apply predictive models and that present well-preformed studies and well-desigeworks in various research domains, including…
Michael Franklin Bosu, Stephen G. MacDonell
Context: The utility of prediction models in empirical software engineering (ESE) is heavily reliant on the quality of the data used in building those models. Several data quality challenges such as noise, incompleteness, outliers and duplicate data points may be relevant in this regard. Objective: We investigate the…
Michael Franklin Bosu, Stephen G. MacDonell
Reliable empirical models such as those used in software effort estimation or defect prediction are inherently dependent on the data from which they are built. As demands for process and product improvement continue to grow, the quality of the data used in measurement and prediction systems warrants increasingly close…
Nayyar Iqbal, Jun Sang, Jing Chen, Xiaofeng Xia
Software products in the market are changing due to changes in business processes, technology, or new requirements from the customers. Maintainability of legacy systems has always been an inspiring task for the software companies. In order to determine whether the software requires maintainability by reverse…
Hashim Ali, Raja Sarath Kumar Boddu, Umer Tanveer, Aamir Saeed + 4 more
Software requirements classification remains one of the important challenges in requirements engineering. Engineering that affects the smoothness of project success about software development life cycles. in this paper, a novel hybrid solution is being presented that beats the benchmarks set by previous approaches…
Sana Gul, Rizwan Bin Faiz, Mohammad Aljaidi, Ghassan Samara + 2 more
Cross-project defect prediction (CPDP) is a significant way of defect identification in the project. In cross-project defect prediction, we extract knowledge from the source project and apply that learned knowledge to predict labels for the target project. However, the model performance can be affected by features that…
Authors not listed
The increasing importance and predictive power of modern molecular modeling, driven by physics- and machine learning-based methods, necessitates a new collaborative architecture to replace the isolated, traditional model of software development. The traditional approach often led to redundant engineering effort, high…
Adrian Zapletal, Dimitri Höhler, Carsten Sinz, Alexandros Stamatakis
Scientific software from all areas of scientific research is pivotal to obtaining novel insights. Yet the quality of scientific software is rarely assessed, even though it might lead to incorrect scientific results in the worst case. Therefore, we have developed an open source tool and benchmark called SoftWipe, that…
Bilal I. Al-Ahmad, Ala’ A. Al-Zoubi, Md Faisal Kabir, Marwan Al-Tawil + 2 more
'Marwan Al-Tawil' 'Ibrahim Aljarah' 'Chi-Hua Chen'] Software engineering is one of the most significant areas, which extensively used in educational and industrial fields. Software engineering education plays an essential role in keeping students up to date with software technologies, products, and processes that are…
Ihsan Tolga Medeni, Metehan Ünal, Roberto Galizi, Bryan Bartley + 4 more
Large language models have transformed software engineering practices. However, generated artefacts are not always developer-friendly and may partially meet complex requirements. As the need to standardise, integrate, and develop tools in engineering biology increases, novel approaches are needed to create and maintain…
Authors not listed
The scarcity and expense of fatigue data limits optimal design of components and constrains companies to a few well qualified materials when safety-critical applications are concerned. This research investigates different strategies to improve extraction of structured information from unstructured scientific…
Katalin Ferenc, Konrad Otto, Francisco Gomes de Oliveira Neto, Marcela Dávila López + 2 more
Software quality in computational tools impacts research output in a variety of scientific disciplines. Biology is one of these fields, especially for High Throughput Sequencing (HTS) data, such tools play an important role. This study therefore characterises the overall quality of a selection of tools which are…
Jeremy Li, Alex Rubinsteyn, Sergey Feldman, Timothy O’Donnell + 18 more
Scientific computing has become a central component of modern scientific discovery. Yet many computational tools are developed by small, specialized teams under incentives that encourage the release of rapidly prototyped tooling without commensurate attention to engineering concerns, including performance and…