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检索条件"任意字段=18th International Conference on Software Engineering and Knowledge Engineering"

共 35587 条记录，以下是611-620 订阅

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Towards the Construction of a software Benchmarking Dataset via Systematic Literature Review 50

Towards the Construction of a Software Benchmarking Dataset ...

引用

50th Euromicro conference on software engineering and Advanced Applications

作者： Yurum, Ozan Rasit Unlu, Huseyin Demirors, Onur Izmir Inst Technol Izmir Turkiye

ISBN: (纸本)9798350380279;9798350380262

Effort estimation is a fundamental task during the planning of software projects. Prediction models usually rely on two essential factors: software size and effort data. Measuring the size of the software can be done at various stages of the project with desired accuracy. Nevertheless, the industry faces challenges when it comes to collecting reliable actual effort data. Consequently, organizations encounter difficulties in establishing effort prediction models. Benchmarking datasets are available, but, in most cases, they have huge variances that make them less useful for effort prediction. In this study, we aimed to answer whether creating a software benchmarking dataset is possible by gathering the data from the literature. To the best of our knowledge, a comprehensive dataset that gathers the functional size and effort data of the studies from the literature is unavailable. For this purpose, we performed a systematic literature review to find studies that include projects measured with the COSMIC Functional Size Measurement (FSM) method and the related effort. As a result, we formed a dataset including 337 records from 18 studies that shared the corresponding size and effort data. Although we performed a limited search, we created a larger dataset than many datasets in the literature. In light of our review, we obtained that most studies did not share their dataset, and many lacked case details such as implementation environment and the scope of software development life cycle activities included in the effort data. We also compared the dataset with the ISBSG repository and found that our dataset has less variation in productivity. Our review showed the applicability of creating a software benchmarking dataset is possible by gathering the data from the literature. In conclusion, this study addresses gaps in the literature through a cost-free and easily extendable dataset.

关键词： software size measurement effort estimation dataset benchmarking COSMIC systematic literature review

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Encoding Domain knowledge in Log Analysis 40

Encoding Domain Knowledge in Log Analysis

引用

40th international conference on software Maintenance and Evolution

作者： Zamfirov, Filip Dams, Dennis Seraj, Mazyar Serebrenik, Alexander Eindhoven Univ Technol Eindhoven Netherlands TNO ESI Eindhoven Netherlands

ISBN: (纸本)9798350395693;9798350395686

software developers often use logs to, e.g., investigate bugs, familiarize themselves with the underlying system, or improve performance. To do so, they commonly rely on text editors or their own scripts. this lack of appropriate tooling remains a primary challenge in the industrial application of log analysis (state-of-the-practice), despite many tools and techniques proposed by previous scientific studies (state-of-the-art). To aid in bridging this gap between industry and academia, between state-of-the-practice and state-of-the-art, we zoom in on the ways developers perform log analysis. In particular, we conduct an exploratory case study to understand what structures developers identify in logs and how they utilize their knowledge in this process. Based on the results of the case study, we identify two classes of features, one related to encoding domain knowledge and another one related to sharing domain knowledge. We implement two features from the first class in an open-source log analysis platform designed in collaboration with our industrial partner. To evaluate the impact of the implemented features on log analysis, we conduct a user evaluation with software developers from our industrial partner. During this evaluation developers complete several tasks using the features and complete a usability questionnaire. Results show that users are able to encode their domain knowledge about the logs during their analysis. Furthermore, we observe that participants value highly ease of use and indicate an interest in using the features in their current practice. this sentiment is reflected in the resulting scores of the usability questionnaire, indicating above-average usability. Our findings pave the way to bridge the gap between academia and industry and facilitate the application of advanced log analysis approaches in industry.

关键词： Log Analysis Event Logging Industry Domain software Logs

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Indoor Environmental Quality in Airtight Energy-Efficient Dwellings: the Efficiency of Natural Ventilation 18

Indoor Environmental Quality in Airtight Energy-Efficient Dw...

引用

18th international conference on Indoor Air Quality and Climate, INDOOR AIR 2024

作者： Alhindawi, Ibrahim Sood, Divyanshu O’Donnell, James McGrath, James A. Byrne, Miriam A. Physics Unit School of Natural Science The Ryan Institute’s Centre for Climate and Air Pollution Studies National University of Ireland Galway Galway Ireland School of Mechanical & Materials Engineering UCD Energy Institute University College Dublin Dublin Ireland Department of Experimental Physics Maynooth University County Kildare Maynooth Ireland

ISBN: (纸本)9798331306816

this study examines the efficiency of natural ventilation in maintaining compliant IEQ levels in airtight dwellings. the methodology encompasses a longitudinal study that utilises a combination of low-cost and high-grade sensors in a range of energy-efficient houses in Ireland, to collect measurements of key indoor pollutants and thermal parameters. Results suggest the deficiency of natural ventilation to sustain conforming indoor pollutants levels. the results, presented at the conference, will include the data from ten dwellings, evaluating data trends of the measured parameters, as well as evaluating thermal comfort levels. © 2024 18th conference of the international Society of Indoor Air Quality and Climate, INDOOR AIR 2024 - conference Program and Proceedings. All rights reserved.

关键词： Indoor air pollution

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Structures’ Global Stiffness, a Criterion for the Materials’ Selection 1

引用

18th international Scientific conference Civil engineering and Buildings Services, CIBv 2023

作者： Mocanu, Ştefan Dumitriu, Cristian Ştefan Sasu, Anca Ruxandra Faculty of Mechanical Engineering and Robotics for Construction Technical University of Civil Engineering Bucharest 59 Calea Plevnei Bucharest Romania

ISBN: (数字)9783031607653

ISBN: (纸本)9783031607646

Structural and material optimization remains crucial in today’s constructive design and machine building area. the importance of this topic relies on its applications for testing the behavior of different materials under the action of various loading and the evaluation of the computation error. When choosing the materials for a specific application, an important criterion is the global structure stiffness, which must be precisely determined. this paper presents a case study of a statically indeterminate, circular plane structure used in specific engineering devices. this structure’s particular construction requires determining a dimensional parameter from the viewpoint of optimal rigidity (structure stiffness) to ensure minimal device size. A dual approach, the traditional calculus versus the Finite Element Method simulation, is used to solve the problem. the results of the two finite element software (Axis and SolidWorks) used in this study are also compared. Correlating the structural stiffness to the material properties is the best approach to the optimal design solution. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Finite element method

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An Industry Case Study on Adoption of AI-based Programming Assistants 44

An Industry Case Study on Adoption of AI-based Programming A...

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ACM/IEEE 46th international conference on software engineering - software engineering in Practice (ICSE-SEIP)

作者： Davila, Nicole Wiese, Igor Steinmacher, Igor da Silva, Lucas Lucio Kawamoto, Andre Peres Favaro, Gilson Jose Nunes, Ingrid Univ Fed Rio Grande do Sul Inst Informat Porto Alegre RS Brazil UTFPR Campo Mourao PR Brazil No Arizona Univ Flagstaff AZ USA Coamo Agroind Cooperat Campo Mourao PR Brazil Univ Fed Rio Grande do Sul Inst Informat Porto Alegre RS Brazil

ISBN: (纸本)9798400702174

Programming assistants based on artificial intelligence (AI), such as ChatGPT and Github Copilot, have gained worldwide popularity recently. Studies in software development have explored the adoption of these tools, investigating their characteristics and impacts and how practitioners interact and perceive them. To contribute to this growing body of knowledge, in this study, we aim to explore the adoption of AI-based programming assistants in the Brazilian industry. More specifically, we aim to understand how practitioners of a particular Brazilian agroindustry-related company perceive and use AI-based tools to develop software. Using an online survey, we collected and analyzed 72 responses from employees of the studied company. Our findings suggest that practitioners mainly adopt ChatGPT and Github Copilot, interacting with these tools to accelerate online searching, typing, and syntax recall. A recurrent difficulty is the lack of context in the suggestions provided by these tools, but participants work on detailed descriptions to contextualize and cope with this challenge. Among the reasons for not using AI-based tools, the most influential is that participants use a commercial programming language, i.e., Uniface, which these tools lack examples. Our results provide insights into the state of the practice related to AI-based programming assistants and discuss implications for practitioners and researchers.

关键词： Artificial Intelligence Generative AI ChatGPT Industry Case Study software Development

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Cluster Analysis in the Identification of Patterns in software Development with Agile Methodologies: A Systematic Literature Review 12

Cluster Analysis in the Identification of Patterns in Softwa...

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12th international conference in software engineering Research and Innovation, CONISOFT 2024

作者： Mercader-Olivares, Iskander E. Martinez-Moreno, Patricia Vergara-Camacho, Jose A. Sanchez-Garcia, Angel J. Ocharan-Hernandez, Jorge Octavio Universidad Veracruzana Facultad de Contaduría y Administración Veracruz Coatzacoalcos Mexico Universidad Veracruzana Facultad de Estadística e Informótica Veracruz Xalapa Mexico

ISBN: (纸本)9798331532116

software engineering is a discipline that aims to deliver quality software products. To this end, several development methodologies have been proposed, with agile methodologies being the most recently used, which promote the continuous delivery of functional software in short cycles called iterations or sprints. In these deliveries, there are activities where the identification of patterns in different software arti-facts is necessary. An example of this is the detection of similar artifacts to avoid redundancy or reuse artifacts. this study presents a systematic review of the literature that seeks to analyze the activities, development stages, benefits, and challenges that have been reported when applying various cluster analysis algorithms to identify patterns in agile methodologies. Fifteen primary studies selected through the Kitchenham methodology were analyzed. It was observed that k-means, k-medoids, and hierarchical clustering are the most used approaches in various stages of development such as requirements, design, and testing. Furthermore, the most analyzed artifacts were user stories. Finally, the studies reveal various advantages, such as pattern identification without a priori knowledge, variance reduction, and development time reduction, among others. However, the parameterization of these algorithms is still a fundamental challenge to be addressed in future work. © 2024 IEEE.

关键词： software quality

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IRS-Assisted Data and Energy Transfer MAC Protocol 18

IRS-Assisted Data and Energy Transfer MAC Protocol

引用

18th international conference on Ubiquitous Information Management and Communication, IMCOM 2024

作者： Xing, Weiyue Piao, Yijun Lee, Tae-Jin College of Information and Communication Engineering Sungkyunkwan University Department of Electrical and Computer Engineering Suwon16419 Korea Republic of

ISBN: (纸本)9798350331011

In the next-generation wireless networks, an enormous number of devices are expected to communicate with one another. However, due to the battery limitation of devices and insufficient energy supplement, data transmission efficiency of the network can be reduced. Intelligent Reflecting Surface (IRS) can work as helper for energy harvesting. In this paper, we propose an energy-efficient Medium Access Control (MAC) protocol that utilizes Non-Orthogonal Multiple Access (NOMA) with IRS. In the proposed protocol, devices can transmit data to the Hybrid Access Point (H-AP) simultaneously through NOMA and achieve sufficient energy from the H-AP with the help of IRS. the simulation results show that the proposed protocol has notable improvement in the system throughput and energy efficiency. © 2024 IEEE.

关键词： Medium access control

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knowledge Sharing in software Development: A Conceptual Framework 15

Knowledge Sharing in Software Development: A Conceptual Fram...

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15th international conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Chugh, Mitali UPES Dehradun India

ISBN: (纸本)9798331300579

software development is immensely dependent on knowledge. thus, software development organizations line up knowledge management (KM) to realistically apply the knowledge and renovate solutions for addressing challenges through the different stages of software development. KM facilitates these organizations to obtain and maintain a competitive advantage, specifically from the perspective of agile software development, wherever it nurtures collaboration and management among collocated or cross-functional development teams. the focus of this study is to investigate knowledge sharing in agile software projects and to identify the KS strategies and practices employed by agile teams and practitioners in the software development environment. A conceptual framework has been proposed to facilitate knowledge sharing within both collocated and distributed agile teams. this framework draws upon established theories and practices from knowledge management, organizational behavior, and agile methodologies. It presents a structured approach to understanding and addressing the various factors that influence knowledge sharing within agile teams. the conceptual framework covers elements such as communication, knowledge repositories, iterative development, customer collaboration, and engineering practices. In essence, this paper acts as a valued source for researchers, practitioners, and software development teams pursuing to enhance knowledge sharing in the agile context. By implementing the potential elements of the conceptual framework, organizations can unlock new possibilities for efficient knowledge transfer, collaboration, and innovation, ultimately driving the success of agile software development projects in an increasingly dynamic and technologically advanced world. © Grenze Scientific Society, 2024.

关键词： knowledge representation

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Car Detection Using Histogram of Oriented Gradients (HOG) Features on Autonomous Vehicle 18

Car Detection Using Histogram of Oriented Gradients (HOG) Fe...

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18th international conference on Telecommunication Systems, Services, and Applications, TSSA 2024

作者： Gunawan Setiawan, Wawan Sugiarto, Bambang Laluma, Riffa Haviani Suharsono, Teguh Nurhadi Sukmana, Rini Nuraini Universitas Sangga Buana Department of Informatics Engineering Faculty of Engineering Bandung Indonesia National Research and Inovation Agency Research Center for Artificial Intelligence and Cyber Security Bandung Indonesia

ISBN: (纸本)9798331527686

Autonomous vehicles are becoming a significant innovation trend in the global automotive industry along with the development of automotive technology. this autonomous vehicle concept promises revolutionary possibilities in transportation in the future. In autonomous vehicles, car detection is very necessary to support the car navigation system using the computer vision method. this research aims to propose car detection using a Histogram of Oriented Gradients (HOG) and a Vector Support Machine (SVM). the HOG feature extraction will extract the car image objects, thereby enabling autonomous vehicle systems to identify cars with high accuracy. On the other hand, the SVM classifier is used for the car detection process and separates car objects from other objects besides cars from the HOG features. the detection result showed that car detection accuracy was 83%. this indicates that the car detection in this research is successful and can be implemented on autonomous vehicle navigation systems. © 2024 IEEE.

关键词： Automotive industry

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Anomalous Human Action Recognition with Deep Learning Technique 18

Anomalous Human Action Recognition with Deep Learning Techni...

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18th INDIAcom;11th international conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Pallewar, Megha G. Pawar, Vijaya R. Gaikwad, Arun N. Zeal College of Engineering & Research Dept. of E&tc Engineering Pune India Savitribai Phule Pune University Dept. of E&tc Engineering Pune India

ISBN: (纸本)9789380544519

Detecting and comprehending human actions poses a significant challenge, especially in the context of enhancing human security. this area of study has garnered attention recently, and machine learning-based methods have emerged as the forefront approach for identifying unusual activities. In this research, the main focus is on spotting abnormal activities in videos, utilizing the UCF crime database as the primary source of data. the proposed system uses a range of pre-processing methods on the video data from this collection. the system employs deep learning techniques with Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) algorithms. the frames extracted from the videos are fed into CNN, which processes and extracts important features. the LSTM module is responsible for categorizing the activities portrayed in the input video. By combining the strengths of CNN and LSTM, system successfully identifies six distinct anomalous activities: Abuse, Arson, Assault, Burglary, Fight and Robbery. For training and evaluating the system, divide the dataset into an 80% training set, a 10% testing set, and a 10% validation set, including cross-validation steps. the resulting model demonstrates an impressive accuracy rate of approximately 97.8%. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Abnormal activity detection Anomaly Convolutional neural networks Human action detection Long short time memory

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