RAIDAD：一个模型驱动的框架，用于物联网数据分析软件的自动化和敏捷开发

IF 3.8 2区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Information and Software Technology Pub Date : 2025-07-05 DOI:10.1016/j.infsof.2025.107818

Mohsen Gholami, Bahman Zamani, Behrouz Shahgholi Ghahfarokhi

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引用次数: 0

摘要

背景：目前，开发物联网领域的数据分析软件面临着复杂性、重复性和开发人员缺乏领域知识等挑战。为了解决这些问题，已经引入了像CRISP-DM这样的方法，为数据分析提供结构化指导。目标：尽管结构化方法的可用性，构建数据分析管道仍然涉及管理复杂性和冗余。已经提出了模型驱动的方法来解决这些挑战，但通常无法全面解决数据分析工作流的所有阶段以及阶段和数据集之间的相互依赖关系。本研究介绍了RAIDAD，这是一个模型驱动的框架，通过覆盖CRISP-DM方法的所有阶段来解决这些差距。方法：RAIDAD包括用于物联网数据分析的特定领域建模语言、图形建模编辑器、代码生成转换引擎和用于无缝模型-数据集成的数据模型助手。这些组件作为Eclipse插件交付。结果：RAIDAD具有双重评价。首先，与RapidMiner和ML-Quadrat的比较操作评估显示，RAIDAD在可用性和生产力方面比RapidMiner提高了9.6%，比ML-Quadrat提高了23%。其次，将RAIDAD与通用编程语言进行比较，证明其在减少物联网数据分析软件的工作量和生产时间方面的优势。结论：这个全面的框架确保了有效和有组织的数据分析方法，解决了物联网领域的关键挑战。未来的研究将集中于扩展RAIDAD对更广泛的数据分析和机器学习算法的支持，增强自动化能力，并结合持续的用户反馈，以确保框架的发展符合新兴需求。

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RAIDAD: A model-driven framework for automated and agile development of IoT data analysis software

Context:

Nowadays, developing data analysis software for the IoT domain faces challenges such as complexity, repetitive tasks, and developers’ lack of domain knowledge. To address these issues, methodologies like CRISP-DM have been introduced, providing structured guidance for data analysis.

Objectives:

Despite the availability of structured methodologies, building data analysis pipelines still involves managing complexity and redundancy. Model-driven approaches have been proposed to tackle these challenges but often fail to address all stages of the data analysis workflow and the interdependencies between stages and datasets comprehensively. This research introduces RAIDAD, a model-driven framework that addresses these gaps by covering all phases of the CRISP-DM methodology.

Methods:

RAIDAD includes a domain-specific modeling language for IoT data analysis, a graphical modeling editor, a code generation transformation engine, and a data model assistant for seamless model-data integration. These components are delivered as an Eclipse plugin.

Results:

The evaluation of RAIDAD is two-fold. First, a comparative operational evaluation with RapidMiner and ML-Quadrat shows RAIDAD achieves a 9.6% improvement in usability and productivity over RapidMiner and a 23% improvement over ML-Quadrat. Second, RAIDAD is compared to a general-purpose programming language, demonstrating its superiority in reducing effort and production time for IoT data analysis software.

Conclusion:

This comprehensive framework ensures an efficient and organized approach to data analysis, addressing key challenges in the IoT domain. Future research will focus on expanding RAIDAD’s support for a wider range of data analysis and machine learning algorithms, enhancing automation capabilities, and incorporating continuous user feedback to ensure the framework evolves in line with emerging needs.

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来源期刊

Information and Software Technology 工程技术-计算机：软件工程

CiteScore

9.10

自引率

7.70%

发文量

164

审稿时长

9.6 weeks

期刊介绍： Information and Software Technology is the international archival journal focusing on research and experience that contributes to the improvement of software development practices. The journal''s scope includes methods and techniques to better engineer software and manage its development. Articles submitted for review should have a clear component of software engineering or address ways to improve the engineering and management of software development. Areas covered by the journal include: • Software management, quality and metrics, • Software processes, • Software architecture, modelling, specification, design and programming • Functional and non-functional software requirements • Software testing and verification & validation • Empirical studies of all aspects of engineering and managing software development Short Communications is a new section dedicated to short papers addressing new ideas, controversial opinions, "Negative" results and much more. Read the Guide for authors for more information. The journal encourages and welcomes submissions of systematic literature studies (reviews and maps) within the scope of the journal. Information and Software Technology is the premiere outlet for systematic literature studies in software engineering.