Pub Date : 2024-11-28DOI: 10.1016/j.simpa.2024.100721
Gabriela Pedraza-Jiménez, Gerardo Tinoco-Guerrero, Francisco Javier Domínguez-Mota, José Alberto Guzmán-Torres, José Gerardo Tinoco-Ruiz
This work introduces mGFD: Cloud Generator, a web-based software for generating non-structured clouds of points that is useful in numerical analysis, particularly in applying the Meshless Generalized Finite Difference Method (mGFD). mGFD: CloudGenerator allows to manually define external and internal boundary nodes, using an image as a guide, providing precise control over boundary conditions. It supports image uploads (.png, .jpg, .jpeg) to guide node placement and automatically generates the internal cloud of points. The web-based software is open-source and accessible for research and has been used to produce results in some papers, such as the ones mentioned in this paper.
{"title":"mGFD: CloudGenerator","authors":"Gabriela Pedraza-Jiménez, Gerardo Tinoco-Guerrero, Francisco Javier Domínguez-Mota, José Alberto Guzmán-Torres, José Gerardo Tinoco-Ruiz","doi":"10.1016/j.simpa.2024.100721","DOIUrl":"10.1016/j.simpa.2024.100721","url":null,"abstract":"<div><div>This work introduces mGFD: Cloud Generator, a web-based software for generating non-structured clouds of points that is useful in numerical analysis, particularly in applying the Meshless Generalized Finite Difference Method (mGFD). mGFD: CloudGenerator allows to manually define external and internal boundary nodes, using an image as a guide, providing precise control over boundary conditions. It supports image uploads (.png, .jpg, .jpeg) to guide node placement and automatically generates the internal cloud of points. The web-based software is open-source and accessible for research and has been used to produce results in some papers, such as the ones mentioned in this paper.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"23 ","pages":"Article 100721"},"PeriodicalIF":1.3,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142756998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.simpa.2024.100704
S. Bonduà , S. Focaccia , M. Elkarmoty
Rock masses are naturally affected by discontinuities, joints and fractures that affect their exploitation. After block extraction, different cutting pattern can produce different recovery ratio of the block. The optimization of the cutting pattern can be computed if the discontinuities are mapped by the use of non-destructive methods. We propose a software code able to compute the number of intersected slabs by different cuttings scenarios. The algorithm adopts a brute force computation of several scenarios as specified by the user. The software uses the Open MP library in order to reduce computation time.
岩块天然存在不连续面、节理和裂缝，这些都会影响岩块的开采。岩块开采后，不同的切割方式会产生不同的岩块采收率。如果使用非破坏性方法绘制不连续面图，就可以计算出切割模式的最优化。我们提出了一种软件代码，能够计算不同切割方案下相交板块的数量。该算法对用户指定的几种情况采用蛮力计算。该软件使用 Open MP 库，以减少计算时间。
{"title":"SlabCutOpt: A code for ornamental stone slab cut optimization","authors":"S. Bonduà , S. Focaccia , M. Elkarmoty","doi":"10.1016/j.simpa.2024.100704","DOIUrl":"10.1016/j.simpa.2024.100704","url":null,"abstract":"<div><div>Rock masses are naturally affected by discontinuities, joints and fractures that affect their exploitation. After block extraction, different cutting pattern can produce different recovery ratio of the block. The optimization of the cutting pattern can be computed if the discontinuities are mapped by the use of non-destructive methods. We propose a software code able to compute the number of intersected slabs by different cuttings scenarios. The algorithm adopts a brute force computation of several scenarios as specified by the user. The software uses the Open MP library in order to reduce computation time.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100704"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.simpa.2024.100712
Davi Alves Oliveira , Valter de Senna , Hernane Borges de Barros Pereira
Cohesion is one of the main defining characteristics of a text. CohesionNet, an R app with a Shiny interface, processes raw text to calculate network-based cohesion indices. The indices are based on stem repetition and on the analysis of synonymy and hypernymy. The app also constructs a network representation of the text that can be saved in the Pajek NET format. CohesionNet facilitates the assessment of potential applications of the indices, like text classification, automatic summarization, and readability improvement. Currently supporting English texts only, upcoming versions will include additional language support.
内聚力是文本的主要定义特征之一。CohesionNet 是一款带有 Shiny 界面的 R 应用程序，可处理原始文本，计算基于网络的内聚力指数。这些指数基于词干重复以及同义词和超同义词分析。该应用程序还能构建文本的网络表示，并以 Pajek NET 格式保存。CohesionNet 可帮助评估指数的潜在应用，如文本分类、自动摘要和可读性改进。目前仅支持英文文本，即将推出的版本将包括更多语言支持。
{"title":"CohesionNet: Software for network-based textual cohesion analysis","authors":"Davi Alves Oliveira , Valter de Senna , Hernane Borges de Barros Pereira","doi":"10.1016/j.simpa.2024.100712","DOIUrl":"10.1016/j.simpa.2024.100712","url":null,"abstract":"<div><div>Cohesion is one of the main defining characteristics of a text. CohesionNet, an R app with a Shiny interface, processes raw text to calculate network-based cohesion indices. The indices are based on stem repetition and on the analysis of synonymy and hypernymy. The app also constructs a network representation of the text that can be saved in the Pajek NET format. CohesionNet facilitates the assessment of potential applications of the indices, like text classification, automatic summarization, and readability improvement. Currently supporting English texts only, upcoming versions will include additional language support.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100712"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142724077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.simpa.2024.100723
Davide Italo Serramazza, Thach Le Nguyen, Georgiana Ifrim
tsCaptum is a Python library that enables explainability for time series classification and regression using saliency maps (i.e., attribution-based explanation). It bridges the gap between popular time series frameworks (e.g., aeon, sktime, sklearn) and explanation libraries like Captum. tsCaptum tackles the computational complexity of explaining long time series by employing chunking techniques, significantly reducing the number of model evaluations required. This allows users to easily apply Captum explainers to any univariate or multivariate time series model or pipeline built using the aforementioned frameworks. tsCaptum is readily available on pypi.org and can be installed with a simple ”pip install tsCaptum” command.
{"title":"A short tutorial for multivariate time series explanation using tsCaptum","authors":"Davide Italo Serramazza, Thach Le Nguyen, Georgiana Ifrim","doi":"10.1016/j.simpa.2024.100723","DOIUrl":"10.1016/j.simpa.2024.100723","url":null,"abstract":"<div><div>tsCaptum is a Python library that enables explainability for time series classification and regression using saliency maps (i.e., attribution-based explanation). It bridges the gap between popular time series frameworks (e.g., aeon, sktime, sklearn) and explanation libraries like Captum. tsCaptum tackles the computational complexity of explaining long time series by employing chunking techniques, significantly reducing the number of model evaluations required. This allows users to easily apply Captum explainers to any univariate or multivariate time series model or pipeline built using the aforementioned frameworks. tsCaptum is readily available on pypi.org and can be installed with a simple ”pip install tsCaptum” command.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100723"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.simpa.2024.100714
Young Lee , Jeong Yang , Mohammad Al-Ramahi , Daniel Delgado
SmartSAT is a mobile web application designed to enhance the efficiency and equitable access of San Antonio’s public transit services, providing real-time bus arrival predictions, notifying riders of seat availability, and gathering rider’s feedback. It aims to leverage technology to deliver an inclusive service with potential impacts for social equality, and enhancement of overall ridership experience. Two studies were conducted to access the impact of SmartSAT on the actual bus arrival times and rider’s communte experience. The findings of the arrival times analysis indicated that certain routes exhibited very slow average differences between their actual and schedule arrival times while a couple displayed a big average difference showing significant delayes and deviations from the schedules timetable. The rider experience study found that there is a differential in the feelings of access to the city’s public transit system held by poor, working-class, and Latinx communities in San Antonio. These findings suggest the need for regular minitoring and optimazation of the bus schedules to improve the effieiency and inclusive access to the current transportaiton system. The outcomes of the study primarily benefit San Antonio residents, especially for underserved communities, leading to an enhancement of its transit network infrastructure.
{"title":"SmartSAT: A customizable mobile web application toward improving the efficiency and equitable access of San Antonio’s public transit services","authors":"Young Lee , Jeong Yang , Mohammad Al-Ramahi , Daniel Delgado","doi":"10.1016/j.simpa.2024.100714","DOIUrl":"10.1016/j.simpa.2024.100714","url":null,"abstract":"<div><div>SmartSAT is a mobile web application designed to enhance the efficiency and equitable access of San Antonio’s public transit services, providing real-time bus arrival predictions, notifying riders of seat availability, and gathering rider’s feedback. It aims to leverage technology to deliver an inclusive service with potential impacts for social equality, and enhancement of overall ridership experience. Two studies were conducted to access the impact of SmartSAT on the actual bus arrival times and rider’s communte experience. The findings of the arrival times analysis indicated that certain routes exhibited very slow average differences between their actual and schedule arrival times while a couple displayed a big average difference showing significant delayes and deviations from the schedules timetable. The rider experience study found that there is a differential in the feelings of access to the city’s public transit system held by poor, working-class, and Latinx communities in San Antonio. These findings suggest the need for regular minitoring and optimazation of the bus schedules to improve the effieiency and inclusive access to the current transportaiton system. The outcomes of the study primarily benefit San Antonio residents, especially for underserved communities, leading to an enhancement of its transit network infrastructure.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100714"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142704618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.simpa.2024.100715
Sanaa Kaddoura, Reem Nassar
EnhancedBERT is a software framework designed to disambiguate Arabic polysemous terms using advanced natural language processing techniques. It integrates transformer architectures with ensemble methods to achieve high performance in understanding and processing Arabic text. The framework provides a flexible pipeline that can be directly utilized or fine-tuned according to specific needs. EnhancedBERT stands out for its ease of use, leveraging transformer-based models combined with ensemble strategies to provide superior contextual understanding. This contextual awareness makes it an invaluable tool for researchers and practitioners tackling complexities in Arabic language processing.
{"title":"EnhancedBERT: A python software tailored for arabic word sense disambiguation","authors":"Sanaa Kaddoura, Reem Nassar","doi":"10.1016/j.simpa.2024.100715","DOIUrl":"10.1016/j.simpa.2024.100715","url":null,"abstract":"<div><div>EnhancedBERT is a software framework designed to disambiguate Arabic polysemous terms using advanced natural language processing techniques. It integrates transformer architectures with ensemble methods to achieve high performance in understanding and processing Arabic text. The framework provides a flexible pipeline that can be directly utilized or fine-tuned according to specific needs. EnhancedBERT stands out for its ease of use, leveraging transformer-based models combined with ensemble strategies to provide superior contextual understanding. This contextual awareness makes it an invaluable tool for researchers and practitioners tackling complexities in Arabic language processing.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100715"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142703377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.simpa.2024.100718
Alauddin Sabari , Imran Hasan , Salem A. Alyami , Pietro Liò , Md. Sadek Ali , Mohammad Ali Moni , AKM Azad
LandSin, a web application with a back-end database, is developed for global land value estimation by combining polynomial regression and differential privacy models. Leveraging local amenities and property details, LandSin offers key features, e.g., accurate land value and price predictions, affordability and habitability analysis, and terrain insights using Google Maps. In addition, it facilitates useful infographics, helping stakeholders identify economically deprived but habitable areas for balanced regional development. It also supports real estate agencies and community planners in finding habitable land by making data-driven decisions regarding land investments and regional planning, ensuring informed and strategic choices.
{"title":"LandSin: A differential ML and google API-enabled web server for real-time land insights and beyond","authors":"Alauddin Sabari , Imran Hasan , Salem A. Alyami , Pietro Liò , Md. Sadek Ali , Mohammad Ali Moni , AKM Azad","doi":"10.1016/j.simpa.2024.100718","DOIUrl":"10.1016/j.simpa.2024.100718","url":null,"abstract":"<div><div><em>LandSin</em>, a web application with a back-end database, is developed for global land value estimation by combining polynomial regression and differential privacy models. Leveraging local amenities and property details, <em>LandSin</em> offers key features, e.g., accurate land value and price predictions, affordability and habitability analysis, and terrain insights using Google Maps. In addition, it facilitates useful infographics, helping stakeholders identify economically deprived but habitable areas for balanced regional development. It also supports real estate agencies and community planners in finding habitable land by making data-driven decisions regarding land investments and regional planning, ensuring informed and strategic choices.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100718"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142654390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.simpa.2024.100719
H.L. Varona , C. Noriega , S. Herold-Garcia , S.M.A. Lira , M. Araujo , F. Hernandez
The study and analysis of drifter trajectories, such as buoys and floating devices, have become fundamental to understanding oceanographic phenomena. The detailed analysis of oceanographic parameters using specialized software allows researchers to study environmental changes on different temporal and spatial scales. This article explores the importance and functionalities of this type of software, highlighting its role in improving research methodologies and generating scientific knowledge applicable to oceanography and meteorology. drifViewer is a MATLAB package designed to optimize the search for drift trajectories and analyze oceanographic parameters. It allows researchers to search for drift trajectories in the AOML dataset quickly, create summary tables, and export data to MATLAB and NetCDF formats. driftViewer contributes to scientific research in oceanography and marine geology by improving the ability to model and predict drifting currents, which is essential for studies on climate change, ocean current dynamics, and marine habitat conservation. It is also a useful tool for studying the trajectories of oil slicks, microplastics, and chemical and living species.
{"title":"driftViewer: Optimization of drifter trajectory search and export of oceanographic parameters","authors":"H.L. Varona , C. Noriega , S. Herold-Garcia , S.M.A. Lira , M. Araujo , F. Hernandez","doi":"10.1016/j.simpa.2024.100719","DOIUrl":"10.1016/j.simpa.2024.100719","url":null,"abstract":"<div><div>The study and analysis of drifter trajectories, such as buoys and floating devices, have become fundamental to understanding oceanographic phenomena. The detailed analysis of oceanographic parameters using specialized software allows researchers to study environmental changes on different temporal and spatial scales. This article explores the importance and functionalities of this type of software, highlighting its role in improving research methodologies and generating scientific knowledge applicable to oceanography and meteorology. drifViewer is a MATLAB package designed to optimize the search for drift trajectories and analyze oceanographic parameters. It allows researchers to search for drift trajectories in the AOML dataset quickly, create summary tables, and export data to MATLAB and NetCDF formats. driftViewer contributes to scientific research in oceanography and marine geology by improving the ability to model and predict drifting currents, which is essential for studies on climate change, ocean current dynamics, and marine habitat conservation. It is also a useful tool for studying the trajectories of oil slicks, microplastics, and chemical and living species.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100719"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.simpa.2024.100720
Michael Simonis , Stefan Nickel
Multi-level capacitated lot-sizing problems with linked lot sizes and backorders (MLCLSP-L-B) are used in pharmaceutical tablets manufacturing processes to right-size material production lots so that costs are kept at a minimum, production resource capacities are not exceeded, and customer demand is fulfilled. Uncertain demand behavior characterizes today’s global tablets market. Pharmaceutical companies request solution approaches that solve the MLCLSP-L-B with probabilistic demand. Implementing this model in industrial applications for tablets manufacturing systems requires efficient data processing due to the amount of data and the capability to store simulated demand scenarios. This paper covers the first integration of the MLCLSP-L-B with probabilistic demand and Relational Database Structures (RDS). Modeling techniques for the RDS to process massive data are outlined. A virtual environment provides the implementation software PostgreSQL and infrastructure environment. Additionally, numerical experiments with research data are used to evaluate the agility and efficiency of the developed RDS.
{"title":"PostgreSQL: Relational database structures application on capacitated lot-sizing for pharmaceutical tablets manufacturing processes","authors":"Michael Simonis , Stefan Nickel","doi":"10.1016/j.simpa.2024.100720","DOIUrl":"10.1016/j.simpa.2024.100720","url":null,"abstract":"<div><div>Multi-level capacitated lot-sizing problems with linked lot sizes and backorders (MLCLSP-L-B) are used in pharmaceutical tablets manufacturing processes to right-size material production lots so that costs are kept at a minimum, production resource capacities are not exceeded, and customer demand is fulfilled. Uncertain demand behavior characterizes today’s global tablets market. Pharmaceutical companies request solution approaches that solve the MLCLSP-L-B with probabilistic demand. Implementing this model in industrial applications for tablets manufacturing systems requires efficient data processing due to the amount of data and the capability to store simulated demand scenarios. This paper covers the first integration of the MLCLSP-L-B with probabilistic demand and Relational Database Structures (RDS). Modeling techniques for the RDS to process massive data are outlined. A virtual environment provides the implementation software PostgreSQL and infrastructure environment. Additionally, numerical experiments with research data are used to evaluate the agility and efficiency of the developed RDS.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100720"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142703378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.simpa.2024.100713
Guru Bhandari, Nikola Gavric, Andrii Shalaginov
The study introduces VulnMiner, a comprehensive framework encompassing a data extraction tool tailored for identifying vulnerabilities in C/C++ source code. Moreover, it unveils an initial release of a vulnerability dataset, curated from prevalent projects and annotated with vulnerable and benign instances. This dataset incorporates projects with vulnerabilities labeled as Common Weakness Enumeration (CWE) categories. The developed open-source extraction tool collects vulnerability data utilizing static security analyzers. The study also fosters the machine learning (ML) and natural language processing (NLP) model’s effectiveness in accurately classifying vulnerabilities, evidenced by its identification of numerous weaknesses in open-source projects.
{"title":"VulnMiner: A comprehensive framework for vulnerability collection from C/C++ source code projects","authors":"Guru Bhandari, Nikola Gavric, Andrii Shalaginov","doi":"10.1016/j.simpa.2024.100713","DOIUrl":"10.1016/j.simpa.2024.100713","url":null,"abstract":"<div><div>The study introduces <em>VulnMiner</em>, a comprehensive framework encompassing a data extraction tool tailored for identifying vulnerabilities in C/C++ source code. Moreover, it unveils an initial release of a vulnerability dataset, curated from prevalent projects and annotated with vulnerable and benign instances. This dataset incorporates projects with vulnerabilities labeled as Common Weakness Enumeration (CWE) categories. The developed open-source extraction tool collects vulnerability data utilizing static security analyzers. The study also fosters the machine learning (ML) and natural language processing (NLP) model’s effectiveness in accurately classifying vulnerabilities, evidenced by its identification of numerous weaknesses in open-source projects.</div></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"22 ","pages":"Article 100713"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142742851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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