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A blockchain-based and microservices-architected software composition analysis system 基于区块链和微服务架构的软件组成分析系统
IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-06-11 DOI: 10.1002/smr.2675
Xin Zhou, Jinwei Xu, Xiaokang Li, Lingli Cao, Lingjie Li, Yanze Wang, Shanshan Li, Hui Liu

“Shift To Left” is the cornerstone of the successful implementation of DevSecOps. By testing projects for vulnerabilities in the early stages of development, teams can save overall costs before security issues reach the build phase. As one of the popular practices in “Shift To Left,” the Software Composition Analysis (SCA) system aims to leverage the Software Bill of Materials (SBOM) to enhance software supply chain security. However, the SBOM lacks mature generation and distribution mechanisms, requiring incentive measures to drive industry consensus. Additionally, the data and tools associated with the SBOM lack effective record-keeping and monitoring, making it challenging to ensure data integrity and tool security. Traditional SCA systems treat SBOM as a regular data format for external service provision, yet fail to solve problems such as lack of shared platforms, inability to guarantee data integrity and tool security, as well as issues with poor interoperation compatibility. This paper introduces blockchain technology into the SCA system, utilizing smart contracts to provide core SBOM tool services and microservices to improve the operational efficiency of smart contract deployment and maintenance. The proposed SCA system effectively provides a shared platform for SBOM with reliable data integrity, guaranteed tool security, and good interoperability.

"向左移动 "是成功实施 DevSecOps 的基石。通过在开发早期阶段对项目进行漏洞测试,团队可以在安全问题进入构建阶段之前节省总体成本。作为 "向左转 "的流行实践之一,软件构成分析(SCA)系统旨在利用软件物料清单(SBOM)来增强软件供应链的安全性。然而,SBOM 缺乏成熟的生成和分配机制,需要采取激励措施来推动行业达成共识。此外,与 SBOM 相关的数据和工具缺乏有效的记录保存和监控,因此确保数据完整性和工具安全性具有挑战性。传统的 SCA 系统将 SBOM 作为常规数据格式对外提供服务,但无法解决缺乏共享平台、无法保证数据完整性和工具安全性以及互操作兼容性差等问题。本文将区块链技术引入SCA系统,利用智能合约提供SBOM核心工具服务,并利用微服务提高智能合约部署和维护的运行效率。所提出的 SCA 系统能有效地为 SBOM 提供一个共享平台,具有可靠的数据完整性、有保障的工具安全性和良好的互操作性。
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引用次数: 0
Looking back and forward: A retrospective and future directions on software engineering for systems-of-systems 回顾过去,展望未来:系统软件工程的回顾与未来方向
IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-06-09 DOI: 10.1002/smr.2697
Everton Cavalcante, Thais Batista, Flavio Oquendo

Modern systems are increasingly connected and more integrated with other existing systems, giving rise to systems-of-systems (SoS). An SoS consists of a set of independent, heterogeneous systems that interact to provide new functionalities and accomplish global missions through emergent behavior manifested at runtime. The distinctive characteristics of SoS, when contrasted to traditional systems, pose significant research challenges within software engineering. These challenges motivate the need for a paradigm shift and the exploration of novel approaches for designing, developing, deploying, and evolving these systems. The International Workshop on Software Engineering for Systems-of-Systems (SESoS) series started in 2013 to fill a gap in scientific forums addressing SoS from the software engineering perspective, becoming the first venue for this purpose. This article presents a study aimed at outlining the evolution and future trajectory of software engineering for SoS based on the examination of 57 papers spanning the 11 editions of the SESoS workshop (2013–2023). The study combined scoping review and scientometric analysis methods to categorize and analyze the research contributions concerning temporal and geographic distribution, topics of interest, research methodologies employed, application domains, and research impact. Based on such a comprehensive overview, this article discusses current and future directions in software engineering for SoS.

现代系统与其他现有系统的连接和集成度越来越高,从而产生了系统的系统(SoS)。SoS 由一系列独立的异构系统组成,这些系统通过在运行时表现出的突发行为进行交互,以提供新的功能和完成全局任务。与传统系统相比,SoS 具有与众不同的特点,这给软件工程领域的研究带来了重大挑战。这些挑战促使人们需要转变模式,探索设计、开发、部署和演进这些系统的新方法。系统的软件工程(SESoS)系列国际研讨会始于2013年,旨在填补从软件工程角度解决SoS问题的科学论坛的空白,并成为实现这一目的的第一个场所。本文介绍了一项研究,旨在通过对 SESoS 研讨会(2013-2023 年)11 届会议期间的 57 篇论文进行审查,勾勒出 SoS 软件工程的发展和未来轨迹。研究结合了范围审查和科学计量分析方法,对研究贡献进行了分类和分析,涉及时间和地理分布、关注主题、采用的研究方法、应用领域和研究影响。基于这样一个全面的概述,本文讨论了 SoS 软件工程的当前和未来发展方向。
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引用次数: 0
A survey of the state-of-the-art approaches for evaluating trust in software ecosystems 评估软件生态系统信任度的最新方法概览
IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-06-03 DOI: 10.1002/smr.2695
Fang Hou, Slinger Jansen

Third-party software has streamlined the software engineering process, allowed software engineers to focus on developing more advanced components, and reduced time and cost. This shift has led to software development strategies moving from competition to collaboration, resulting in the concept of software ecosystems, in which internal and external actors work together on shared platforms and place their trust in the ecosystem. However, the increase in shared components has also created challenges, especially in security, as the large dependency trees significantly enlarge a system's attack surface. The situation is made worse by the lack of effective ways to measure and ensure the trustworthiness of these components. In this article, we explore current approaches used to evaluate trust in software ecosystems, focusing on analyzing the specific techniques utilized, the primary factors in trust evaluation, the diverse formats for result presentation, as well as the software ecosystem entities considered in the approaches. Our goal is to provide the status of current trust evaluation approaches, including their limitations. We identify key challenges, including the limited coverage of software ecosystem entities; the objectivity, universality, and environmental impacts of the evaluation approaches; the risk assessment for the evaluation approaches; and the security attacks posed by trust evaluation in these approaches.

第三方软件简化了软件工程流程,使软件工程师能够专注于开发更先进的组件,并减少了时间和成本。这种转变导致软件开发战略从竞争转向合作,产生了软件生态系统的概念,即内部和外部参与者在共享平台上合作,并对生态系统给予信任。然而,共享组件的增加也带来了挑战,尤其是在安全方面,因为庞大的依赖树大大增加了系统的攻击面。由于缺乏有效的方法来衡量和确保这些组件的可信度,情况变得更加糟糕。在本文中,我们将探讨当前用于评估软件生态系统信任度的方法,重点分析所使用的具体技术、信任度评估的主要因素、结果呈现的不同格式以及这些方法所考虑的软件生态系统实体。我们的目标是提供当前信任度评估方法的现状,包括其局限性。我们确定了主要挑战,包括软件生态系统实体的有限覆盖范围;评估方法的客观性、普遍性和环境影响;评估方法的风险评估;以及这些方法中的信任评估带来的安全攻击。
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引用次数: 0
Deep learning or classical machine learning? An empirical study on line-level software defect prediction 深度学习还是经典机器学习?线路级软件缺陷预测实证研究
IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-06-02 DOI: 10.1002/smr.2696
Yufei Zhou, Xutong Liu, Zhaoqiang Guo, Yuming Zhou, Corey Zhang, Junyan Qian

Background

Line-level software defect prediction (LL-SDP) serves as a valuable tool for developers to detect defective lines with minimal human effort. Recently, GLANCE was proposed as a readily implementable baseline for assessing the efficacy of newly proposed LL-SDP models.

Problem

While DeepLineDP, a cutting-edge LL-SDP model rooted in deep learning, has demonstrated state-of-the-art performance, it has not yet been compared against GLANCE.

Objective

We aim to empirically compare DeepLineDP with GLANCE to obtain a comprehensive understanding of how deep learning contributes to solving the LL-SDP challenge.

Method

We compare GLANCE against DeepLineDP to assess the extent to which DeepLineDP surpasses GLANCE in predicting defective files and identifying problematic lines. In order to obtain a reliable conclusion, we use the same dataset and performance metrics utilized by DeepLineDP.

Result

Our experimental findings indicate that DeepLineDP does not outperform GLANCE in LL-SDP. This suggests that the application of deep learning, in this context, does not yield the anticipated significant improvements.

Conclusion

This finding underscores the need for further research in deep learning-based LL-SDP to attain the state-of-the-art performance that remains elusive for less advanced techniques.

线路级软件缺陷预测(LL-SDP)是开发人员以最小的人力检测缺陷线路的重要工具。最近,GLANCE 被提出作为评估新提出的 LL-SDP 模型功效的一个易于实现的基线。虽然 DeepLineDP(一种植根于深度学习的前沿 LL-SDP 模型)已经展示了最先进的性能,但它尚未与 GLANCE 进行过比较。我们将 GLANCE 与 DeepLineDP 进行比较,以评估 DeepLineDP 在预测缺陷文件和识别问题行方面超越 GLANCE 的程度。为了得出可靠的结论,我们使用了与 DeepLineDP 相同的数据集和性能指标。我们的实验结果表明,DeepLineDP 在 LL-SDP 中的表现并没有超过 GLANCE。这表明,在这种情况下,深度学习的应用并没有产生预期的显著改进。这一发现突出表明,需要进一步研究基于深度学习的 LL-SDP,以获得最先进的性能,而对于不太先进的技术来说,这种性能仍然难以达到。
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引用次数: 0
An approach for serious game design and development based on iterative evaluation 基于迭代评估的严肃游戏设计和开发方法
IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-05-27 DOI: 10.1002/smr.2680
Besma Ben Amara, Hedia Mhiri Sellami, Lamjed Ben Said

Serious games (SGs) are valuable tools for learning, training, and improving skills in various domains because they engage and motivate players to achieve planned processes to reach objectives. Several works provided methods, models, and frameworks to support SG development. However, designers, developers, teachers, and researchers face challenges in creating SG with entertainment and learning balance, and many designed games still do not fulfill the main intended objectives. This paper introduces an approach, called SGDA-IE with phases and steps to follow during the entire SG design process. It was built on literature review and SG design challenges designers need to consider from the early stages when creating SG. The proposed approach is founded on three perspectives: software engineering best practices, video game industry practices, and SG success factors and provides means to overcome the investigated design challenges. These are characteristics taxonomy model, requirements specification approach, and artifacts iterative evaluation by designer, domain expert, and players. To assess our approach efficacy, we conceived a health, safety, and environment (HSE) training SG for workers on fuel storage sites and petroleum installations. The feedback received is positive and indicates a favorable specification method of the SG, effective participatory design, and control over requirements evolution. The SG playtesting reveals a significant involvement of participants and efficient tracking of the knowledge acquisition.

严肃游戏(SGs)是学习、培训和提高各领域技能的重要工具,因为它们能吸引和激励玩家完成计划过程,从而达到目标。一些著作提供了支持 SG 开发的方法、模型和框架。然而,设计者、开发者、教师和研究人员在创造兼顾娱乐和学习的 SG 时面临着挑战,许多设计的游戏仍然没有达到预期的主要目标。本文介绍了一种名为 "SGDA-IE "的方法,它包含了整个 SG 设计过程中的各个阶段和步骤。它建立在文献综述和设计者在创建 SG 的早期阶段需要考虑的 SG 设计挑战的基础上。所提出的方法基于三个视角:软件工程最佳实践、视频游戏行业实践和 SG 成功因素,并提供了克服所调查的设计挑战的方法。这些方法包括特征分类模型、需求规范方法以及由设计者、领域专家和玩家进行的工件迭代评估。为了评估我们的方法是否有效,我们为燃料储存地和石油设施的工人设计了一个健康、安全和环境(HSE)培训 SG。所收到的反馈是积极的,并表明该 SG 具有良好的规范方法、有效的参与式设计和对需求演变的控制。SG 游戏测试表明,参与者的参与度很高,对知识获取的跟踪也很有效。
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引用次数: 0
Multi-objective optimization-based and fault localization-oriented test case generation for novice programs 为新手程序生成基于多目标优化和面向故障定位的测试用例
IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-05-27 DOI: 10.1002/smr.2679
Yong Liu, Zezhong Yang, Luxi Fan, Yonghao Wu, Xiang Chen, Xiaotang Zhou

Online judgment (OJ) systems are capable of evaluating program results by automatically executing test cases, significantly improving the efficiency of traditional guidance approaches. Moreover, existing studies attempt to assist novices through automated fault localization techniques to provide feedback to novices, which can help them quickly find the location of faulty statements. Among them, spectrum-based fault localization (SBFL) techniques have been widely used for their lightweight and efficiency, which only requires coverage information and test results of test cases to conduct fault localization. However, manually constructing high-quality test cases for a large number of OJ questions is tough work to complete. To solve this problem, we propose the novice program-oriented Multi-Objective Optimization-Based Fault Localization-Oriented Test Case Generation (MFTCG) for automatically generating test inputs. Specifically, we use multi-objective optimization algorithms to evolve the test case in terms of both fault localization and faulty code detection capability. We conduct experiments with 8911 programs from the well-known public OJ platform AtCoder. The results show that our proposed approach MFTCG can achieve the best fault localization performance compared with existing automated test case generation approaches in most cases and can achieve the similar faulty code detection capability compared to manually designed test cases.

摘要在线判断(OJ)系统能够通过自动执行测试用例来评估程序结果,大大提高了传统指导方法的效率。此外,现有研究还尝试通过自动故障定位技术为新手提供反馈,帮助他们快速找到错误语句的位置。其中,基于频谱的故障定位(SBFL)技术因其轻便高效而被广泛应用,该技术只需测试用例的覆盖信息和测试结果即可进行故障定位。然而,针对大量 OJ 问题手动构建高质量的测试用例是一项难以完成的工作。为了解决这个问题,我们提出了面向新手程序的基于多目标优化的故障定位测试用例生成(MFTCG),用于自动生成测试输入。具体地说,我们使用多目标优化算法,从故障定位和故障代码检测能力两方面对测试用例进行演化。我们使用著名的公共 OJ 平台 AtCoder 中的 8911 个程序进行了实验。结果表明,与现有的自动生成测试用例方法相比,我们提出的方法 MFTCG 在大多数情况下都能实现最佳的故障定位性能,并且与人工设计的测试用例相比,也能实现类似的故障代码检测能力。
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引用次数: 0
Special issues on emerging technologies and their importance for software and systems processes 关于新兴技术及其对软件和系统流程重要性的特刊
IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-05-21 DOI: 10.1002/smr.2678
Xiwei Xu, Jens Heidrich
<p>The integration of these emerging technologies into software and systems processes is not merely a matter of technological advancement but a fundamental shift in how software is conceived, developed, and deployed. As organizations strive to innovate and stay competitive in today's digital economy, harnessing the power of AI, big data, blockchain, AR, and other emerging technologies is imperative for driving efficiency, agility, and innovation in software and systems development. By embracing these technologies and adapting to the evolving technological landscape, software developers and organizations can unlock new opportunities, address complex challenges, and deliver transformative solutions that meet the evolving needs of users and stakeholders.</p><p>The 17th International Conference on Software and System Processes (ICSSP) held in 2023 focused on the theme “Software and System Processes for and with Emerging Technologies.” This theme reflects the accelerating pace of technological advancement and its profound impact on software and system development practices. The conference provided a platform for researchers and practitioners to explore innovative approaches in incorporating new technologies into software and system processes, aiming to advance the state of both research and practice in the field.</p><p>This special issue of the Journal of Software: Evolution and Process features a selection of high-quality articles from ICSSP 2023 that exemplify the conference theme. The articles selected for inclusion cover a range of topics related to software and system processes, highlighting the diverse applications of emerging technologies in improving development practices and how to improve our engineering processes when developing systems using emerging technologies.</p><p>The selection process for the seven articles featured in this special issue involved a rigorous evaluation of the scientific contributions presented at the ICSSP 2023. Out of the 10 scientific articles presented at the conference, the editorial team carefully selected the four most outstanding articles based on their originality, relevance to the conference theme, and contribution to advancing software and systems processes. These selected articles underwent an extended review process and were expanded into comprehensive articles for inclusion in this special issue. Additionally, the three keynote speakers at the conference were invited to contribute articles summarizing their research presentations and providing valuable insights into the field. It is important to note that all submitted articles, including those selected for this special issue, underwent thorough peer reviews by experts in the field before being accepted for publication in the journal. The inclusion of these keynote articles further enriches this special issue by offering diverse perspectives and cutting-edge research in software and systems processes.</p><p>The articles featured in this special issue can
将这些新兴技术整合到软件和系统流程中不仅仅是技术进步的问题,而是软件构思、开发和部署方式的根本转变。在当今的数字经济时代,企业要努力创新并保持竞争力,就必须利用人工智能、大数据、区块链、AR 和其他新兴技术的力量来提高软件和系统开发的效率、敏捷性和创新性。通过拥抱这些技术并适应不断变化的技术环境,软件开发人员和组织可以释放新的机遇,应对复杂的挑战,并提供变革性的解决方案,以满足用户和利益相关者不断变化的需求。2023 年举行的第 17 届国际软件和系统过程大会(ICSSP)的主题是 "面向新兴技术的软件和系统过程"。这一主题反映了技术进步的加速及其对软件和系统开发实践的深刻影响。会议为研究人员和从业人员提供了一个平台,探讨将新技术融入软件和系统过程的创新方法,旨在推动该领域的研究和实践:软件:演变与过程》特刊精选了 2023 年国际软件和服务供应商大会上体现大会主题的高质量文章。入选的文章涵盖了与软件和系统过程相关的一系列主题,重点介绍了新兴技术在改进开发实践中的各种应用,以及在使用新兴技术开发系统时如何改进我们的工程过程。在会议上发表的 10 篇科学论文中,编辑团队根据文章的原创性、与会议主题的相关性以及对推进软件和系统过程的贡献,精心挑选出四篇最优秀的文章。这些被选中的文章都经过了详细审查,并被扩充为综合文章,收录在本特刊中。此外,会议的三位主讲人也应邀撰文总结了他们的研究成果,并提供了对该领域的宝贵见解。值得注意的是,所有提交的文章,包括被选入本特刊的文章,都经过了该领域专家的全面同行评审,然后才被接受在期刊上发表。本特刊所收录的文章可分为两类,每一类都涉及新兴技术背景下软件和系统工程的重要方面。第一组文章探讨了如何利用新兴技术加强软件和系统工程实践或开发具有专用品质的系统。这些文章展示了将新兴技术融入软件开发流程的创新方法,从而提高了效率、安全性和可靠性。另一方面,第二组文章侧重于流程的总体改进,认识到尽管新技术层出不穷,但软件工程从根本上说仍然是以人为本的。这些文章强调了拥有合格的、积极进取的软件工程师以及合适的、高质量的流程的重要性,它们是将新兴技术有效融入软件工程实践的重要组成部分。本特刊收录的文章体现了新兴技术在软件和系统流程中的多样化应用,以及在使用新兴技术开发系统时不断改进工程流程的重要性。通过应对关键挑战和提出创新解决方案,这些文章为推动该领域的研究和实践做出了贡献。我们希望本特刊能成为有志于探索软件和系统流程与新兴技术交叉点的研究人员和从业人员的宝贵资源。
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引用次数: 0
Enhancing agile project success: a comprehensive study of risk management approaches among Malaysian practitioners 提高敏捷项目的成功率:马来西亚从业人员风险管理方法综合研究
IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-05-19 DOI: 10.1002/smr.2681
Mazni Omar, Abdul Rehman Gilal, Mazida Ahmad, Huda Ibrahim, Azman Yasin, Hapini Awang, Abdullah Almogahed

Risk management (RM) plays a role in project management in the software development field. As information technology (IT) systems become more essential across industries and IT projects continue to face failure rates effective project management becomes crucial. However, the utilization of methodologies in risk management is not widely considered, specifically in Malaysia. This study aims to investigate how software practitioners in Malaysia have implemented risk management and discover strategies that can enhance risk management for agile contexts. The main focus of this study is the limited integration of methodologies into risk management practices, which has created a gap within the software risk domain. Successful risk management is essential for the achievement of software projects, and the findings from this study can offer insights for software development organizations to make informed decisions and improve project outcomes. By utilizing a quantitative approach and adapted questionnaires, this comprehensive study collected data from 60 practitioners and conducted descriptive analysis to identify key risk elements that have significant potential to affect project performance. The findings highlight these risk elements that can significantly impact project success. Agile methodologies, with their emphasis on collaboration, communication within teams, and engagement with stakeholders, including top management, are instrumental in aligning project objectives, identifying potential risks, and resolving issues promptly. This study provides empirical insights into the risk management practices of agile practitioners in Malaysia, which can equip software development organizations with valuable knowledge for informed decision-making. By enhancing project outcomes and guiding future strategic actions, the findings of this study can contribute to the improvement of agile risk management in the software development industry, particularly in the Malaysian context.

风险管理(RM)在软件开发领域的项目管理中发挥着重要作用。随着信息技术(IT)系统在各行各业变得越来越重要,IT 项目不断面临失败率,有效的项目管理变得至关重要。然而,风险管理方法的使用并未得到广泛考虑,特别是在马来西亚。本研究旨在调查马来西亚的软件从业人员是如何实施风险管理的,并发现可以在敏捷环境下加强风险管理的策略。本研究的重点是将方法论有限地融入风险管理实践,这在软件风险领域造成了差距。成功的风险管理对于软件项目的成功至关重要,本研究的结果可为软件开发组织提供见解,帮助其做出明智决策并改善项目成果。通过采用定量方法和改编问卷,这项综合研究收集了 60 名从业人员的数据,并进行了描述性分析,以确定对项目绩效有重大潜在影响的关键风险因素。研究结果强调了这些会对项目成功产生重大影响的风险因素。敏捷方法强调团队内部的协作和沟通,以及与包括高层管理人员在内的利益相关者的接触,这有助于协调项目目标、识别潜在风险并及时解决问题。本研究对马来西亚敏捷实践者的风险管理实践进行了实证分析,为软件开发组织做出明智决策提供了宝贵的知识。通过提高项目成果和指导未来的战略行动,本研究的结论可为改进软件开发行业的敏捷风险管理做出贡献,尤其是在马来西亚。
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引用次数: 0
Sustainable software engineering—A contribution puzzle of different teams in large IT organizations 可持续软件工程--大型 IT 企业不同团队的贡献之谜
IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-05-13 DOI: 10.1002/smr.2677
Alexander Poth, Pegah Momen

IT sustainability is becoming more and more important within the digitalization journey. It is more than green coding or the usage of power-efficient hardware – it needs a holistic approach to leverage the potentials end-to-end in the software life-cycle. The overall value stream within the IT organization is subject to sustainability alignment. This holistic alignment demands the engagement of different teams in large IT organizations. This article identifies the contributions of typical team stakeholders and evaluates their sustainability software engineering (SSE) contributions. This includes demand, architecture, design, implementation, operation, and usage. As an IT organization focuses on more than just software, the term sustainable IT engineering (SIE) fits better with the scope of organizational sustainability. The proposed approaches are presented based on instantiations within the Volkswagen Group IT.

摘要 IT 的可持续发展在数字化进程中变得越来越重要。它不仅仅是绿色编码或使用高能效硬件,而是需要一种整体方法,在软件生命周期中端到端发挥潜能。IT 组织内的整体价值流必须与可持续性保持一致。这种整体调整需要大型 IT 组织中不同团队的参与。本文确定了典型团队利益相关者的贡献,并评估了他们在可持续性软件工程(SSE)方面的贡献。这包括需求、架构、设计、实施、运营和使用。由于 IT 组织关注的不仅仅是软件,因此可持续 IT 工程(SIE)一词更符合组织可持续发展的范围。我们将根据大众汽车集团 IT 部门的实际情况介绍所提出的方法。
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引用次数: 0
A novel defect prediction method based on semantic feature enhancement 基于语义特征增强的新型缺陷预测方法
IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-04-28 DOI: 10.1002/smr.2674
Chi Zhang, Xiaoli Wang, Jinfu Chen, Saihua Cai, Rexford Nii Ayitey Sosu

Although cross-project defect prediction (CPDP) techniques that use traditional manual features to build defect prediction model have been well-developed, they usually ignore the semantic and structural information inside the program and fail to capture the hidden features that are critical for program category prediction, resulting in poor defect prediction results. Researchers have proposed using deep learning to automatically extract the semantic features of programs and fuse them with traditional features as training data. However, in practice, it is important to explore the effective representation of the semantic features in the programs and how the fusion of a reasonable ratio between the two types of features can maximize the effectiveness of the model. In this paper, we propose a semantic feature enhancement-based defect prediction framework (SFE-DP), which augments the semantic feature set extracted from the program code with data. We also introduce a layer of self-attentive mechanism and a matching layer to filter low-efficiency and non-critical semantic features in the model structure. Finally, we combine the idea of hybrid loss function to iteratively optimize the model parameters. Extensive experiments validate that SFE-DP can outperform the baseline approaches on 90 pairs of CPDP tasks formed by 10 open-source projects.

摘要虽然利用传统人工特征建立缺陷预测模型的跨项目缺陷预测(CPDP)技术已经得到了很好的发展,但它们通常忽略了程序内部的语义和结构信息,无法捕捉到对程序类别预测至关重要的隐藏特征,导致缺陷预测结果不佳。研究人员提出利用深度学习自动提取程序的语义特征,并将其与传统特征融合作为训练数据。然而,在实际应用中,如何有效地表征程序中的语义特征,以及如何融合两类特征的合理比例,才能最大限度地提高模型的有效性,是探索的重点。在本文中,我们提出了一种基于语义特征增强的缺陷预测框架(SFE-DP),它利用数据增强了从程序代码中提取的语义特征集。我们还引入了一层自我关注机制和一个匹配层,以过滤模型结构中的低效和非关键语义特征。最后,我们结合混合损失函数的思想,对模型参数进行迭代优化。大量实验验证了 SFE-DP 在由 10 个开源项目组成的 90 对 CPDP 任务中的表现优于基线方法。
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Journal of Software-Evolution and Process
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