Pub Date : 2024-03-19DOI: 10.1142/s0218194024500025
Carlos Calatayud Asensi, José Vicente Berná Martínez, Lucía Arnau Muñoz, Francisco Maciá Pérez
Traditionally, drinking water supply infrastructures have been designed to store as much water as possible and to do so during the energy cheap hours. This approach is unsustainable today. The use of digital systems capable of modeling the behavior of infrastructures and the creation of intelligent control systems can help to make drinking water supply systems more efficient and effective, while still meeting minimum service requirements. This work proposes the development of a control system, based on multi-agent systems (MAS), capable of generating an intelligent control over a drinking water infrastructure, based on the use of local interests of the agents and with an emergent behavior coherent with the needs. To validate the proposal, a simulator based on the infrastructures of a medium-sized Spanish city of 5000 inhabitants has been built and the control has been simulated using the MAS. The results show how the system can maintain the objectives set, handling unknown situations, and facilitating the development of future physical systems based on a just-in-time paradigm that guarantees sustainability, as it allows the generation of virtualizations of the infrastructures and their behavior, thus being able to study the best option for an infrastructure to resolve a supply situation.
传统上，饮用水供应基础设施的设计目的是尽可能多地储水，并在能耗低的时段储水。如今，这种方法已难以为继。使用能够模拟基础设施行为的数字系统和创建智能控制系统，有助于提高饮用水供应系统的效率和效益，同时还能满足最低服务要求。这项工作建议开发一个基于多代理系统（MAS）的控制系统，该系统能够对饮用水基础设施进行智能控制，其基础是利用代理的本地兴趣和符合需求的新兴行为。为了验证该建议，我们以西班牙一个拥有 5000 名居民的中型城市的基础设施为基础，建立了一个模拟器，并使用 MAS 对控制进行了模拟。结果表明，该系统能够保持既定目标，处理未知情况，并促进未来基于及时范例的物理系统的发展，从而保证可持续性，因为它允许生成基础设施及其行为的虚拟化，从而能够研究基础设施解决供应问题的最佳方案。
{"title":"Modeling and Control of Drinking Water Supply Infrastructures Through Multi-Agent Systems for Sustainability","authors":"Carlos Calatayud Asensi, José Vicente Berná Martínez, Lucía Arnau Muñoz, Francisco Maciá Pérez","doi":"10.1142/s0218194024500025","DOIUrl":"https://doi.org/10.1142/s0218194024500025","url":null,"abstract":"<p>Traditionally, drinking water supply infrastructures have been designed to store as much water as possible and to do so during the energy cheap hours. This approach is unsustainable today. The use of digital systems capable of modeling the behavior of infrastructures and the creation of intelligent control systems can help to make drinking water supply systems more efficient and effective, while still meeting minimum service requirements. This work proposes the development of a control system, based on multi-agent systems (MAS), capable of generating an intelligent control over a drinking water infrastructure, based on the use of local interests of the agents and with an emergent behavior coherent with the needs. To validate the proposal, a simulator based on the infrastructures of a medium-sized Spanish city of 5000 inhabitants has been built and the control has been simulated using the MAS. The results show how the system can maintain the objectives set, handling unknown situations, and facilitating the development of future physical systems based on a just-in-time paradigm that guarantees sustainability, as it allows the generation of virtualizations of the infrastructures and their behavior, thus being able to study the best option for an infrastructure to resolve a supply situation.</p>","PeriodicalId":50288,"journal":{"name":"International Journal of Software Engineering and Knowledge Engineering","volume":"92 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140170468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-28DOI: 10.1142/s0218194023420019
Weidong Liu, Fei Li, Senjun Pei, Chunming Cheng
With the increasing number of patent applications over the years, instances of patent infringement cases have become more frequent. However, traditional manual patent infringement detection models are no longer suitable for large-scale infringement detection. Existing automated models mainly focus on detecting one-to-one patent infringements, but neglect the many-to-one scenarios. The many-to-one patent infringement detection model faces some major challenges. First, the diversity of patent domains, complexity of content and ambiguity of features make it difficult to extract and represent patent features. Second, patent infringement detection relies on the correlation between patents and the comparison of contextual information as the key factors, but modeling the process and drawing conclusions present challenges. To address these challenges, we propose a many-to-one patent graph (MPG) embedding base infringement detection model. Our model extracts the relationship between keywords and patents, as well as association relation between keywords from many-to-one patent texts (MPTs), to construct a MPG. We obtain patent infringement features through graph embedding of MPG. By using these embedding features as input, the many-to-one infringement detection (MOID) model outputs the conclusion on whether a patent is infringed or not. The comparative experimental results indicate that our model improves accuracy, precision and F-measure by 3.81%, 11.82% and 5.37%, respectively, when compared to the state-of-the-art method.
{"title":"MOID: Many-to-One Patent Graph Embedding Base Infringement Detection Model","authors":"Weidong Liu, Fei Li, Senjun Pei, Chunming Cheng","doi":"10.1142/s0218194023420019","DOIUrl":"https://doi.org/10.1142/s0218194023420019","url":null,"abstract":"<p>With the increasing number of patent applications over the years, instances of patent infringement cases have become more frequent. However, traditional manual patent infringement detection models are no longer suitable for large-scale infringement detection. Existing automated models mainly focus on detecting one-to-one patent infringements, but neglect the many-to-one scenarios. The many-to-one patent infringement detection model faces some major challenges. First, the diversity of patent domains, complexity of content and ambiguity of features make it difficult to extract and represent patent features. Second, patent infringement detection relies on the correlation between patents and the comparison of contextual information as the key factors, but modeling the process and drawing conclusions present challenges. To address these challenges, we propose a many-to-one patent graph (MPG) embedding base infringement detection model. Our model extracts the relationship between keywords and patents, as well as association relation between keywords from many-to-one patent texts (MPTs), to construct a MPG. We obtain patent infringement features through graph embedding of MPG. By using these embedding features as input, the many-to-one infringement detection (MOID) model outputs the conclusion on whether a patent is infringed or not. The comparative experimental results indicate that our model improves accuracy, precision and F-measure by 3.81%, 11.82% and 5.37%, respectively, when compared to the state-of-the-art method.</p>","PeriodicalId":50288,"journal":{"name":"International Journal of Software Engineering and Knowledge Engineering","volume":"163 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140170226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-14DOI: 10.1142/s0218194023500699
Naglaa A. Eldanasory, Engy Yehia, A. Idrees
{"title":"EFSP: an enhanced full scrum process model","authors":"Naglaa A. Eldanasory, Engy Yehia, A. Idrees","doi":"10.1142/s0218194023500699","DOIUrl":"https://doi.org/10.1142/s0218194023500699","url":null,"abstract":"","PeriodicalId":50288,"journal":{"name":"International Journal of Software Engineering and Knowledge Engineering","volume":"15 6","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138971555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-14DOI: 10.1142/s0218194023500687
Yasir Hussain, Zhiqiu Huang, Yu Zhou, I. A. Khan
{"title":"Exploring the Impact of Vocabulary Techniques on Code Completion: A Comparative Approach","authors":"Yasir Hussain, Zhiqiu Huang, Yu Zhou, I. A. Khan","doi":"10.1142/s0218194023500687","DOIUrl":"https://doi.org/10.1142/s0218194023500687","url":null,"abstract":"","PeriodicalId":50288,"journal":{"name":"International Journal of Software Engineering and Knowledge Engineering","volume":"156 20 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138973276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.1142/s0218194023430015
Fernando Ibarra-Torres, Matias Urbieta, N. Medina-Medina
{"title":"Appling Scrum to knowledge transfer among software developers","authors":"Fernando Ibarra-Torres, Matias Urbieta, N. Medina-Medina","doi":"10.1142/s0218194023430015","DOIUrl":"https://doi.org/10.1142/s0218194023430015","url":null,"abstract":"","PeriodicalId":50288,"journal":{"name":"International Journal of Software Engineering and Knowledge Engineering","volume":"78 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138626014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-10DOI: 10.1142/s0218194023500675
Yang Qu, Jinchen Xu, Bei Zhou, Jiangwei Hao, Fei Li, Zuoyan Zhang
{"title":"SCR-LIBM: A Correctly Rounded Elementary Function Library in Double-Precision","authors":"Yang Qu, Jinchen Xu, Bei Zhou, Jiangwei Hao, Fei Li, Zuoyan Zhang","doi":"10.1142/s0218194023500675","DOIUrl":"https://doi.org/10.1142/s0218194023500675","url":null,"abstract":"","PeriodicalId":50288,"journal":{"name":"International Journal of Software Engineering and Knowledge Engineering","volume":" 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135191284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-08DOI: 10.1142/s0218194023500596
Yanfang Ma, Wei Zhou
During the process of software development, a significant challenge revolves around accurately estimating the associated costs. The primary goal of project managers is to ensure the delivery of a highly trustworthiness product that aligns with the designated budgetary constraints. Nonetheless, the trustworthiness of software hinges upon a range of distinct attributes. When implementing a budget allocation scheme to enhance these attributes, conflicts among them may arise. Thus, it becomes imperative to select an appropriate allocation scheme that effectively mitigates conflict-associated costs. In this paper, we will define the conflict costs and establish costs estimation models. The difficulty coefficient constraint for improving attributes is established. Subsequently, we will analyze the relative importance weights of these attributes. Drawing upon the conflict costs, importance weights, and difficulty coefficient constraint, we present an algorithm to determine an appropriate budget allocation scheme, which can minimize conflict-associated costs. Finally, we provide an illustrative example that demonstrates the practicability of our proposed algorithm. This research offers valuable insights to software managers, aiding them in the reasonable allocation of budgetary resources, thereby maximizing overall benefits.
{"title":"The Allocation Scheme of Software Development Budget with Minimal Conflict Attributes","authors":"Yanfang Ma, Wei Zhou","doi":"10.1142/s0218194023500596","DOIUrl":"https://doi.org/10.1142/s0218194023500596","url":null,"abstract":"During the process of software development, a significant challenge revolves around accurately estimating the associated costs. The primary goal of project managers is to ensure the delivery of a highly trustworthiness product that aligns with the designated budgetary constraints. Nonetheless, the trustworthiness of software hinges upon a range of distinct attributes. When implementing a budget allocation scheme to enhance these attributes, conflicts among them may arise. Thus, it becomes imperative to select an appropriate allocation scheme that effectively mitigates conflict-associated costs. In this paper, we will define the conflict costs and establish costs estimation models. The difficulty coefficient constraint for improving attributes is established. Subsequently, we will analyze the relative importance weights of these attributes. Drawing upon the conflict costs, importance weights, and difficulty coefficient constraint, we present an algorithm to determine an appropriate budget allocation scheme, which can minimize conflict-associated costs. Finally, we provide an illustrative example that demonstrates the practicability of our proposed algorithm. This research offers valuable insights to software managers, aiding them in the reasonable allocation of budgetary resources, thereby maximizing overall benefits.","PeriodicalId":50288,"journal":{"name":"International Journal of Software Engineering and Knowledge Engineering","volume":" 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135293547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-04DOI: 10.1142/s0218194023500572
Yi Zhu, Yuxiang Gao, Yu Qiao
Interpretation is important for adopting software defect prediction in practice. Model-agnostic techniques such as Local Interpretable Model-agnostic Explanation (LIME) can help practitioners understand the factors which contribute to the prediction. They are effective and useful for models constructed on tabular data with traditional features. However, when they are applied on source code-based models, they cannot differentiate the contribution of code tokens in different locations for deep learning-based models with Bag-of-Word features. Besides, only using limited features as explanation may result in information loss about actual riskiness. Such limitations may lead to inaccurate explanation for source code-based models, and make model-agnostic techniques not useful and helpful as expected. Thus, we apply a perturbation-based approach Randomized Input Sampling Explanation (RISE) for source code-based defect prediction. Besides, to fill the gap that there lacks a systematical evaluation on model-agnostic techniques on source code-based defect models, we also conduct an extensive case study on the model-agnostic techniques on both token frequency-based and deep learning-based models. We find that (1) model-agnostic techniques are effective to identify the most important code tokens for an individual prediction and predict defective lines based on the importance scores, (2) using limited features (code tokens) for explanation may result in information loss about actual riskiness, and (3) RISE is more effective than others as it can generate more accurate explanation, achieve better cost-effectiveness for line-level prediction, and result in less information loss about actual riskiness. Based on such findings, we suggest that model-agnostic techniques can be a supplement to file-level source code-based defect models, while such explanations should be used with caution as actual risky tokens may be ignored. Also, compared with LIME, we would recommend RISE for a more effective explanation.
{"title":"An Empirical Study on Model-Agnostic Techniques for Source Code-Based Defect Prediction","authors":"Yi Zhu, Yuxiang Gao, Yu Qiao","doi":"10.1142/s0218194023500572","DOIUrl":"https://doi.org/10.1142/s0218194023500572","url":null,"abstract":"Interpretation is important for adopting software defect prediction in practice. Model-agnostic techniques such as Local Interpretable Model-agnostic Explanation (LIME) can help practitioners understand the factors which contribute to the prediction. They are effective and useful for models constructed on tabular data with traditional features. However, when they are applied on source code-based models, they cannot differentiate the contribution of code tokens in different locations for deep learning-based models with Bag-of-Word features. Besides, only using limited features as explanation may result in information loss about actual riskiness. Such limitations may lead to inaccurate explanation for source code-based models, and make model-agnostic techniques not useful and helpful as expected. Thus, we apply a perturbation-based approach Randomized Input Sampling Explanation (RISE) for source code-based defect prediction. Besides, to fill the gap that there lacks a systematical evaluation on model-agnostic techniques on source code-based defect models, we also conduct an extensive case study on the model-agnostic techniques on both token frequency-based and deep learning-based models. We find that (1) model-agnostic techniques are effective to identify the most important code tokens for an individual prediction and predict defective lines based on the importance scores, (2) using limited features (code tokens) for explanation may result in information loss about actual riskiness, and (3) RISE is more effective than others as it can generate more accurate explanation, achieve better cost-effectiveness for line-level prediction, and result in less information loss about actual riskiness. Based on such findings, we suggest that model-agnostic techniques can be a supplement to file-level source code-based defect models, while such explanations should be used with caution as actual risky tokens may be ignored. Also, compared with LIME, we would recommend RISE for a more effective explanation.","PeriodicalId":50288,"journal":{"name":"International Journal of Software Engineering and Knowledge Engineering","volume":"15 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135728296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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