IET Software最新文献

{"title":"Evaluation of Compliance Rule Languages for Modelling Regulatory Compliance Requirements","authors":"Andrea Zasada, M. Hashmi, M. Fellmann, David Knuplesch","doi":"10.3390/software2010004","DOIUrl":"https://doi.org/10.3390/software2010004","url":null,"abstract":"Compliance in business processes has become a fundamental requirement given the constant rise in regulatory requirements and competitive pressures that have emerged in recent decades. While in other areas of business process modelling and execution, considerable progress towards automation has been made (e.g., process discovery, executable process models), the interpretation and implementation of compliance requirements is still a highly complex task requiring human effort and time. To increase the level of “mechanization” when implementing regulations in business processes, compliance research seeks to formalize compliance requirements. Formal representations of compliance requirements should, then, be leveraged to design correct process models and, ideally, would also serve for the automated detection of violations. To formally specify compliance requirements, however, multiple process perspectives, such as control flow, data, time and resources, have to be considered. This leads to the challenge of representing such complex constraints which affect different process perspectives. To this end, current approaches in business process compliance make use of a varied set of languages. However, every approach has been devised based on different assumptions and motivating scenarios. In addition, these languages and their presentation usually abstract from real-world requirements which often would imply introducing a substantial amount of domain knowledge and interpretation, thus hampering the evaluation of their expressiveness. This is a serious problem, since comparisons of different formal languages based on real-world compliance requirements are lacking, meaning that users of such languages are not able to make informed decisions about which language to choose. To close this gap and to establish a uniform evaluation basis, we introduce a running example for evaluating the expressiveness and complexity of compliance rule languages. For language selection, we conducted a literature review. Next, we briefly introduce and demonstrate the languages’ grammars and vocabularies based on the representation of a number of legal requirements. In doing so, we pay attention to semantic subtleties which we evaluate by adopting a normative classification framework which differentiates between different deontic assignments. Finally, on top of that, we apply Halstead’s well-known metrics for calculating the relevant characteristics of the different languages in our comparison, such as the volume, difficulty and effort for each language. With this, we are finally able to better understand the lexical complexity of the languages in relation to their expressiveness. In sum, we provide a systematic comparison of different compliance rule languages based on real-world compliance requirements which may inform future users and developers of these languages. Finally, we advocate for a more user-aware development of compliance languages which should consider a trade off be","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"38 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82781217","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}

{"title":"Retracted: Visualisation-based binary classification of android malware using vgg16","authors":"Aryan Marwaha,&nbsp;Rami Qays Malik,&nbsp;Shehab Mohamed Beram,&nbsp;Ali Rizwan,&nbsp;Kakarla Hari Kishore,&nbsp;Deepak Thakur,&nbsp;Tanya Gera,&nbsp;Mohammad Shabaz","doi":"10.1049/sfw2.12094","DOIUrl":"https://doi.org/10.1049/sfw2.12094","url":null,"abstract":"<p>Retraction: [Aryan Marwaha, Rami Qays Malik, Shehab Mohamed Beram, Ali Rizwan, Hari Kishore Kakarla, Deepak Thakur, Tanya Gera, Mohammad Shabaz, Visualisation-based binary classification of android malware using vgg16, <i>IET Software</i> 2023 (https://doi.org/10.1049/sfw2.12094)].</p><p>The above article from <i>IET Software</i>, published online on 23 January 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor-in-Chief, Hana Chockler, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 4","pages":"717-728"},"PeriodicalIF":1.6,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12094","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50141809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Constructing meaningful code changes via graph transformer","authors":"Shikai Guo,&nbsp;Mengxuan Li,&nbsp;Xin Ge,&nbsp;Hui Li,&nbsp;Rong Chen,&nbsp;Tingting Li","doi":"10.1049/sfw2.12097","DOIUrl":"https://doi.org/10.1049/sfw2.12097","url":null,"abstract":"<p>The rapid development of Open-Source Software (OSS) has resulted in a significant demand for code changes to maintain OSS. Symptoms of poor design and implementation choices in code changes often occur, thus heavily hindering code reviewers to verify correctness and soundness of code changes. Researchers have investigated how to learn meaningful code changes to assist developers in anticipating changes that code reviewers may suggest for the submitted code. However, there are two main limitations to be addressed, including the limitation of long-range dependencies of the source code and the missing syntactic structural information of the source code. To solve these limitations, a novel method is proposed, named Graph Transformer for learning meaningful Code Transformations (GTCT), to provide developers with preliminary and quick feedback when developers submit code changes, which can improve the quality of code changes and improve the efficiency of code review. GTCT comprises two components: code graph embedding and code transformation learning. To address the missing syntactic structural information of the source code limitation, the code graph embedding component captures the types and patterns of code changes by encoding the source code into a code graph structure from the lexical and syntactic representations of the source code. Subsequently, the code transformation learning component uses the multi-head attention mechanism and positional encoding mechanism to address the long-range dependencies limitation. Extensive experiments are conducted to evaluate the performance of GTCT by both quantitative and qualitative analyses. For the quantitative analysis, GTCT relatively outperforms the baseline on six datasets by 210%, 342.86%, 135%, 29.41%, 109.09%, and 91.67% in terms of perfect prediction. Meanwhile, the qualitative analysis shows that each type of code change by GTCT outperforms that of the baseline method in terms of bug fixed, refactoring code and others' taxonomy of code changes.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 2","pages":"154-167"},"PeriodicalIF":1.6,"publicationDate":"2023-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12097","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50140087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retracted: Data exploration of college students' humanistic literacy in the internet age under the big data environment","authors":"Taixiang Tang,&nbsp;Huihua Zhang","doi":"10.1049/sfw2.12087","DOIUrl":"https://doi.org/10.1049/sfw2.12087","url":null,"abstract":"<p>Retraction: [Taixiang Tang, Huihua Zhang, Data exploration of college students' humanistic literacy in the internet age under the big data environment, <i>IET Software</i> 2023 (https://doi.org/10.1049/sfw2.12087)].</p><p>The above article from <i>IET Software</i>, published online on 20 January 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor-in-Chief, Hana Chockler, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 4","pages":"649-660"},"PeriodicalIF":1.6,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12087","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50138493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retracted: Anomaly detection with ensemble empirical mode decomposition and approximate entropy for quick user datagram protocol internet connection-based distributed Blockchain systems","authors":"Yuanlong Cao,&nbsp;Keyang Gu,&nbsp;Junyi Wu,&nbsp;Xiang Zou,&nbsp;Lei Tao,&nbsp;Xin Huang,&nbsp;Changgen Jiang","doi":"10.1049/sfw2.12096","DOIUrl":"https://doi.org/10.1049/sfw2.12096","url":null,"abstract":"<p>Retraction: [Yuanlong Cao, Keyang Gu, Junyi Wu, Xiang Zou, Lei Tao, Xin Huang, Changgen Jiang, Anomaly detection with ensemble empirical mode decomposition and approximate entropy for quick user datagram protocol internet connection-based distributed Blockchain systems, <i>IET Software</i> 2023 (https://doi.org/10.1049/sfw2.12096)].</p><p>The above article from <i>IET Software</i>, published online on 20 January 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor-in-Chief, Hana Chockler, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 4","pages":"742-754"},"PeriodicalIF":1.6,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12096","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50152667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Model-Driven Approach for Software Process Line Engineering","authors":"Halimeh Agh, Raman Ramsin","doi":"10.3390/software2010003","DOIUrl":"https://doi.org/10.3390/software2010003","url":null,"abstract":"It has become increasingly preferable to construct bespoke software development processes according to the specifications of the project at hand; however, defining a separate process for each project is time consuming and costly. One solution is to use a Software Process Line (SPrL), a specialized Software Product Line (SPL) in the context of process definition. However, instantiating an SPrL is a slow and error-prone task if performed manually; an adequate degree of automation is therefore essential, which can be achieved by using a Model-Driven Development (MDD) approach. Furthermore, we have identified specific shortcomings in existing approaches for SPrL Engineering (SPrLE). To address the identified shortcomings, we propose a novel MDD approach specifically intended for SPrLE; this approach can be used by method engineers and project managers to first define an SPrL, and then construct custom processes by instantiating it. The proposed approach uses a modeling framework for modeling an SPrL, and applies transformations to provide a high degree of automation when instantiating the SPrL. The proposed approach addresses the shortcomings by providing an adequate coverage of four activities, including Feasibility analysis, Enhancing the core process, Managing configuration complexity, and Post-derivation enhancement. The proposed approach has been validated through an industrial case study and an experiment; the results have shown that the proposed approach can improve the processes being used in organizations, and is rated highly as to usefulness and ease of use.","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"144 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80992241","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}

{"title":"Acknowledgment to the Reviewers of Software in 2022","authors":"","doi":"10.3390/software2010002","DOIUrl":"https://doi.org/10.3390/software2010002","url":null,"abstract":"High-quality academic publishing is built on rigorous peer review [...]","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"136 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73493259","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}

{"title":"Retracted: Research on intelligent elevation control method of shearer drum based on deep learning","authors":"Pu Zhang","doi":"10.1049/sfw2.12089","DOIUrl":"https://doi.org/10.1049/sfw2.12089","url":null,"abstract":"<p>Retraction: [Pu Zhang, Research on intelligent elevation control method of shearer drum based on deep learning, <i>IET Software 2023</i> (https://doi.org/10.1049/sfw2.12089)].</p><p>The above article from <i>IET Software</i>, published online on 17 January 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor-in-Chief, Hana Chockler, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 4","pages":"672-680"},"PeriodicalIF":1.6,"publicationDate":"2023-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12089","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50135774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retracted: Prediction of stock market movement via technical analysis of stock data stored on blockchain using novel History Bits based machine learning algorithm","authors":"Nitin Nandkumar Sakhare,&nbsp;Imambi S. Shaik,&nbsp;Suman Saha","doi":"10.1049/sfw2.12092","DOIUrl":"https://doi.org/10.1049/sfw2.12092","url":null,"abstract":"<p>Retraction: [Nitin Nandkumar Sakhare, Imambi S. Shaik, Suman Saha, Prediction of stock market movement via technical analysis of stock data stored on blockchain using novel History Bits based machine learning algorithm, <i>IET Software</i> 2023 (https://doi.org/10.1049/sfw2.12092)].</p><p>The above article from <i>IET Software</i>, published online on 12 January 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor-in-Chief, Hana Chockler, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 4","pages":"705-716"},"PeriodicalIF":1.6,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12092","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50129851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retracted: Neural network economic forecast method based on genetic algorithm","authors":"Zhong Li","doi":"10.1049/sfw2.12090","DOIUrl":"https://doi.org/10.1049/sfw2.12090","url":null,"abstract":"<p>Retraction: [Zhong Li, Neural network economic forecast method based on genetic algorithm, <i>IET Software</i> 2023 (https://doi.org/10.1049/sfw2.12090)].</p><p>The above article from <i>IET Software</i>, published online on 12 January 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor-in-Chief, Hana Chockler, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 4","pages":"681-693"},"PeriodicalIF":1.6,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12090","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50129467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}