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Evaluation of Compliance Rule Languages for Modelling Regulatory Compliance Requirements 为法规遵从性需求建模的遵从性规则语言的评估
IF 1.6 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2023-01-28 DOI: 10.3390/software2010004
Andrea Zasada, M. Hashmi, M. Fellmann, David Knuplesch
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
鉴于最近几十年来出现的监管需求和竞争压力的不断增加,业务流程中的遵从性已经成为一项基本需求。虽然在业务流程建模和执行的其他领域,已经在自动化方面取得了相当大的进展(例如,流程发现、可执行流程模型),但遵从性需求的解释和实现仍然是一项高度复杂的任务,需要人力和时间。为了在业务流程中实现规则时提高“机械化”水平,遵从性研究试图将遵从性需求形式化。因此,应该利用遵从性需求的正式表示来设计正确的流程模型,并且在理想情况下,还可以用于自动检测违规行为。然而,要正式指定遵从性需求,必须考虑多个过程透视图,例如控制流、数据、时间和资源。这导致了表示影响不同过程透视图的复杂约束的挑战。为此,业务流程遵从性的当前方法使用了一组不同的语言。然而,每种方法都是基于不同的假设和激励情景而设计的。此外,这些语言及其表示通常是从现实世界的需求中抽象出来的,这通常意味着引入大量的领域知识和解释,从而阻碍了对其表达性的评估。这是一个严重的问题,因为缺乏基于实际遵从性需求的不同形式语言的比较,这意味着这些语言的用户无法对选择哪种语言做出明智的决定。为了缩小这一差距并建立统一的评估基础,我们引入了一个运行的示例来评估遵从规则语言的表达性和复杂性。在语言选择上,我们进行了文献综述。接下来,我们将根据一些法律要求的表示简要介绍和演示语言的语法和词汇。在此过程中,我们通过采用区分不同义务赋值的规范分类框架来评估语义的微妙之处。最后,在此基础上,我们应用Halstead的著名指标来计算我们比较中不同语言的相关特征,如每种语言的数量、难度和努力。有了这个,我们最终能够更好地理解语言的词汇复杂性与其表达能力的关系。总之,我们基于现实世界的遵从性需求对不同的遵从性规则语言进行了系统的比较,这可能会为未来的用户和开发人员提供这些语言的信息。最后,我们提倡对遵从性语言进行更加用户感知的开发,它应该考虑在表达性、复杂性和可用性之间进行权衡。
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引用次数: 2
Retracted: Visualisation-based binary classification of android malware using vgg16 撤回:使用vgg16对安卓恶意软件进行基于可视化的二进制分类
IF 1.6 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2023-01-23 DOI: 10.1049/sfw2.12094
Aryan Marwaha, Rami Qays Malik, Shehab Mohamed Beram, Ali Rizwan, Kakarla Hari Kishore, Deepak Thakur, Tanya Gera, Mohammad Shabaz

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, IET Software 2023 (https://doi.org/10.1049/sfw2.12094)].

The above article from IET Software, 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.

撤回:[Aryan Marwaha,Rami Qays Malik,Shehab Mohamed Beram,Ali Rizwan,Hari Kishore Kakarla,Deepak Thakur,Tanya Gera,Mohammad Shabaz,使用vgg16的基于可视化的android恶意软件二进制分类,IET软件2023(https://doi.org/10.1049/sfw2.12094)]。IET Software的上述文章于2023年1月23日在线发表在威利在线图书馆(wileyonlinelibrary.com),经主编Hana Chockler、工程与技术学会(IET)和John Wiley and Sons有限公司同意撤回。本文作为客座编辑特刊的一部分发表。经过调查,IET和该杂志确定,这篇文章没有按照该杂志的同行评审标准进行评审,有证据表明该特刊的同行评审过程受到了系统的操纵。因此,我们不能保证内容的完整性或可靠性。因此,我们决定收回这篇文章。提交人已被告知撤回的决定。
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引用次数: 3
Constructing meaningful code changes via graph transformer 通过图转换器构造有意义的代码更改
IF 1.6 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2023-01-21 DOI: 10.1049/sfw2.12097
Shikai Guo, Mengxuan Li, Xin Ge, Hui Li, Rong Chen, Tingting Li

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.

开放源码软件(OSS)的快速发展导致了对代码更改的巨大需求,以维护OSS。在代码更改中,经常会出现设计和实现选择不当的症状,从而严重阻碍代码审查人员验证代码更改的正确性和可靠性。研究人员调查了如何学习有意义的代码更改,以帮助开发人员预测代码审查人员可能对提交的代码建议的更改。然而,有两个主要的限制需要解决,包括源代码的长程依赖性的限制和源代码缺少语法结构信息。为了解决这些局限性,提出了一种新的方法,称为图变换器,用于学习有意义的代码变换(GTCT),在开发人员提交代码更改时为开发人员提供初步快速的反馈,从而提高代码更改的质量和代码审查的效率。GTCT包括两个部分:代码图嵌入和代码转换学习。为了解决源代码限制的语法结构信息缺失问题,代码图嵌入组件通过将源代码从源代码的词汇和语法表示编码为代码图结构来捕获代码变化的类型和模式。随后,代码转换学习组件使用多头注意力机制和位置编码机制来解决长程依赖性限制。进行了大量的实验,通过定量和定性分析来评估GTCT的性能。对于定量分析,GTCT在六个数据集上的完美预测相对优于基线210%、342.86%、135%、29.41%、109.09%和91.67%。同时,定性分析表明,GTCT的每种类型的代码更改在bug修复、重构代码和其他代码更改分类方面都优于基线方法。
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引用次数: 0
Retracted: Data exploration of college students' humanistic literacy in the internet age under the big data environment 收回:大数据环境下网络时代大学生人文素养的数据探索
IF 1.6 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2023-01-20 DOI: 10.1049/sfw2.12087
Taixiang Tang, Huihua Zhang

Retraction: [Taixiang Tang, Huihua Zhang, Data exploration of college students' humanistic literacy in the internet age under the big data environment, IET Software 2023 (https://doi.org/10.1049/sfw2.12087)].

The above article from IET Software, 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.

收回:[唐泰祥,张惠华,大数据环境下互联网时代大学生人文素养的数据探索,IET软件2023(https://doi.org/10.1049/sfw2.12087)]来自IET Software的上述文章于2023年1月20日在线发表在威利在线图书馆(wileyonlinelibrary.com),经主编Hana Chockler、工程与技术学会(IET)和John Wiley and Sons有限公司同意撤回。本文作为客座编辑特刊的一部分发表。经过调查,IET和该杂志确定,这篇文章没有按照该杂志的同行评审标准进行评审,有证据表明该特刊的同行评审过程受到了系统的操纵。因此,我们不能保证内容的完整性或可靠性。因此,我们决定收回这篇文章。提交人已被告知撤回的决定。
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引用次数: 0
Retracted: Anomaly detection with ensemble empirical mode decomposition and approximate entropy for quick user datagram protocol internet connection-based distributed Blockchain systems 收回:基于集成经验模式分解和近似熵的快速用户数据报协议互联网连接分布式区块链系统异常检测
IF 1.6 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2023-01-20 DOI: 10.1049/sfw2.12096
Yuanlong Cao, Keyang Gu, Junyi Wu, Xiang Zou, Lei Tao, Xin Huang, Changgen Jiang

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, IET Software 2023 (https://doi.org/10.1049/sfw2.12096)].

The above article from IET Software, 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.

撤回:[曹元龙,顾克阳,吴俊义,邹翔,雷涛,黄欣,江长根,基于集成经验模式分解和近似熵的快速用户数据报协议互联网连接分布式区块链系统异常检测,IET软件2023(https://doi.org/10.1049/sfw2.12096)]。IET Software的上述文章于2023年1月20日在线发表在威利在线图书馆(wileyonlinelibrary.com),经主编Hana Chockler、工程与技术学会(IET)和John Wiley and Sons有限公司同意撤回。本文作为客座编辑特刊的一部分发表。经过调查,IET和该杂志确定,这篇文章没有按照该杂志的同行评审标准进行评审,有证据表明该特刊的同行评审过程受到了系统的操纵。因此,我们不能保证内容的完整性或可靠性。因此,我们决定收回这篇文章。提交人已被告知撤回的决定。
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引用次数: 0
A Model-Driven Approach for Software Process Line Engineering 软件过程线工程的模型驱动方法
IF 1.6 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2023-01-20 DOI: 10.3390/software2010003
Halimeh Agh, Raman Ramsin
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.
根据手头项目的规格来构建定制的软件开发过程已经变得越来越可取;然而,为每个项目定义一个单独的过程既耗时又昂贵。一种解决方案是在过程定义的上下文中使用软件过程线(SPrL),即专门的软件产品线(SPL)。然而,如果手动执行,实例化SPrL是一个缓慢且容易出错的任务;因此,适当程度的自动化是必要的,这可以通过使用模型驱动开发(MDD)方法来实现。此外,我们已经确定了SPrL工程(SPrLE)的现有方法中的具体缺点。为了解决已确定的缺点,我们提出了一种专门用于SPrLE的新型MDD方法;方法工程师和项目经理可以使用这种方法首先定义一个SPrL,然后通过实例化它来构造定制的过程。建议的方法使用建模框架对SPrL进行建模,并在实例化SPrL时应用转换来提供高度的自动化。建议的方法通过提供四个活动的充分覆盖来解决缺点,包括可行性分析、增强核心过程、管理配置复杂性和派生后增强。通过工业案例研究和实验验证了该方法的有效性;结果表明,所提出的方法可以改进组织中正在使用的过程,并且在有用性和易用性方面被高度评价。
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引用次数: 0
Acknowledgment to the Reviewers of Software in 2022 对2022年软件审稿人的感谢
IF 1.6 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2023-01-18 DOI: 10.3390/software2010002
High-quality academic publishing is built on rigorous peer review [...]
高质量的学术出版建立在严格的同行评审的基础上[…]
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引用次数: 0
Retracted: Research on intelligent elevation control method of shearer drum based on deep learning 收回:基于深度学习的采煤机滚筒智能高程控制方法研究
IF 1.6 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2023-01-17 DOI: 10.1049/sfw2.12089
Pu Zhang

Retraction: [Pu Zhang, Research on intelligent elevation control method of shearer drum based on deep learning, IET Software 2023 (https://doi.org/10.1049/sfw2.12089)].

The above article from IET Software, 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.

收回:[Pu Zhang,基于深度学习的采煤机滚筒智能高程控制方法研究,IET软件2023(https://doi.org/10.1049/sfw2.12089)]来自IET Software的上述文章于2023年1月17日在线发表在威利在线图书馆(wileyonlinelibrary.com),经主编Hana Chockler、工程与技术学会(IET)和John Wiley and Sons有限公司同意撤回。本文作为客座编辑特刊的一部分发表。经过调查,IET和该杂志确定,这篇文章没有按照该杂志的同行评审标准进行评审,有证据表明该特刊的同行评审过程受到了系统的操纵。因此,我们不能保证内容的完整性或可靠性。因此,我们决定收回这篇文章。提交人已被告知撤回的决定。
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引用次数: 0
Retracted: Prediction of stock market movement via technical analysis of stock data stored on blockchain using novel History Bits based machine learning algorithm 撤回:通过使用新的基于历史位的机器学习算法对存储在区块链上的股票数据进行技术分析来预测股市走势
IF 1.6 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2023-01-12 DOI: 10.1049/sfw2.12092
Nitin Nandkumar Sakhare, Imambi S. Shaik, Suman Saha

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, IET Software 2023 (https://doi.org/10.1049/sfw2.12092)].

The above article from IET Software, 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.

撤回:[Nitin Nandkumar Sakhare,Imambi S.Shaik,Suman Saha,通过使用新的基于历史位的机器学习算法对存储在区块链上的股票数据进行技术分析来预测股市走势,IET软件2023(https://doi.org/10.1049/sfw2.12092)]来自IET Software的上述文章于2023年1月12日在线发表在威利在线图书馆(wileyonlinelibrary.com),经主编Hana Chockler、工程与技术学会(IET)和John Wiley and Sons有限公司同意撤回。本文作为客座编辑特刊的一部分发表。经过调查,IET和该杂志确定,这篇文章没有按照该杂志的同行评审标准进行评审,有证据表明该特刊的同行评审过程受到了系统的操纵。因此,我们不能保证内容的完整性或可靠性。因此,我们决定收回这篇文章。提交人已被告知撤回的决定。
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引用次数: 2
Retracted: Neural network economic forecast method based on genetic algorithm 收回:基于遗传算法的神经网络经济预测方法
IF 1.6 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2023-01-12 DOI: 10.1049/sfw2.12090
Zhong Li

Retraction: [Zhong Li, Neural network economic forecast method based on genetic algorithm, IET Software 2023 (https://doi.org/10.1049/sfw2.12090)].

The above article from IET Software, 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.

收回:[钟莉,基于遗传算法的神经网络经济预测方法,IET软件2023(https://doi.org/10.1049/sfw2.12090)]来自IET Software的上述文章于2023年1月12日在线发表在威利在线图书馆(wileyonlinelibrary.com),经主编Hana Chockler、工程与技术学会(IET)和John Wiley and Sons有限公司同意撤回。本文作为客座编辑特刊的一部分发表。经过调查,IET和该杂志确定,这篇文章没有按照该杂志的同行评审标准进行评审,有证据表明该特刊的同行评审过程受到了系统的操纵。因此,我们不能保证内容的完整性或可靠性。因此,我们决定收回这篇文章。提交人已被告知撤回的决定。
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引用次数: 0
期刊
IET Software
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