Intelligent Perception and Diagnosis Model for Health Status of Complex Software System

WANG Sen; WANG Yu; NING De-jun

doi:10.12263/DZXB.20190396

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Intelligent Perception and Diagnosis Model for Health Status of Complex Software System

PAPERS | 更新时间：2025-12-08

- Intelligent Perception and Diagnosis Model for Health Status of Complex Software System
- ACTA ELECTRONICA SINICA Vol. 49, Issue 9, Pages: 1799-1808(2021)
- 作者机构：
  
  1.同济大学电子与信息工程学院，上海 201804
  2.中国科学院上海高等研究院，上海 201210
- 作者简介：
- 基金信息：
- DOI：10.12263/DZXB.20190396
  CLC： TP311
- Received：15 April 2019，
  
  Revised：2020-12-31，
  
  Published：25 September 2021
- 稿件说明：
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王森,王煜,宁德军.复杂软件系统健康状态智能感知与诊断模型[J].电子学报,2021,49(09):1799-1808.

WANG Sen,WANG Yu,NING De-jun.Intelligent Perception and Diagnosis Model for Health Status of Complex Software System[J].ACTA ELECTRONICA SINICA,2021,49(09):1799-1808.
王森,王煜,宁德军.复杂软件系统健康状态智能感知与诊断模型[J].电子学报,2021,49(09):1799-1808. DOI： 10.12263/DZXB.20190396.

WANG Sen,WANG Yu,NING De-jun.Intelligent Perception and Diagnosis Model for Health Status of Complex Software System[J].ACTA ELECTRONICA SINICA,2021,49(09):1799-1808. DOI： 10.12263/DZXB.20190396.

摘要

随着工业物联网和人工智能技术的迅猛发展，各种复杂软件系统（Complex Software System

CSS）日趋盛行，成为最重要的软件系统开发范式之一，其固有的成长性构造和适应性演化性质要求CSS必须能够实时感知和诊断自身的健康状态，确保其适应性演化过程中的质量. 本文采用特征工程和存储库数据挖掘技术，对影响开源CSS健康状态的特征进行分析，建立了一个数据驱动的实时、客观地反映开源CSS健康状态的自感知模型，并进一步借鉴质量控制图的思想，定义了能够辅助开源CSS故障诊断的自诊断模型. 最后，通过对比实验，证明了本文提出的模型因为全面综合了软件开发过程的绝大多数特征，能够更加全面和有效地评价软件的健康状态.

Abstract

With the rapid development of Industry Internet of Things and AI technology

various complex software systems (CSS) are becoming more and more popular

and becoming one of the most important software development paradigms. Its inherent growth construction and adaptive evolution require CSS to be able to perceive and diagnose its own health status in real time

so as to ensure the quality of its adaptive evolution. The paper uses feature engineering and mining software repositories (MSR) technology to analyze the features that affect the health of open source CSS

and establishes a data driven perception model that can reflect the health status of open source CSS in real time and objectively. Furthermore

a self-diagnosis model that can assist open source CSS fault diagnosis is defined with reference to the quality control chart. Finally

through the model comparison experiment

it is proved that our model can evaluate the health of software more comprehensively and effectively because it integrates most feature of software development process.

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Keywords

references

王怀民 , 吴文峻 , 毛新军 , 等 . 复杂软件系统的成长性构造与适应性演化 [J]. 中国科学:信息科学 , 2014 , 44 ( 6 ): 743 - 761 .

Wang H M , Wu W J , Mao X J , et al . Growth structure and adaptive evolution of complex software systems [J]. Chinese Science: Information Science , 2014 , 44 ( 6 ): 743 - 761 . (in Chinese)

中国信息物理系统发展论坛 . 信息物理系统白皮书 . [DB/OL]. http://www.cesi.cn/201703/2251.html , 2018‑03‑01 .

阿里研究院 ." 互联网+"——中国经济新引擎 [DB/OL]. http://www.aliresearch.com/blog/article/detail/id/20324.html , 2017⁃03⁃24 .

Lemos R D , Giese H , Müller H A , et al . Software engineering for self‑adaptive systems: a second research roadmap [A]. Software Engineering for Self‑Adaptive Systems II [C]. Berlin Heidelberg : Springer , 2013 . 1 - 32 .

Ralph P . Toward methodological guidelines for process theories and taxonomies in software engineering [J]. IEEE Transactions on Software Engineering , 2019 , 45 ( 7 ): 712 - 735 .

Shevtsov S , Berekmeri M , Weyns D , et al . Control-theoretical software adaptation: a systematic literature review [J]. IEEE Transactions on Software Engineering , 2018 , 44 ( 8 ): 784 - 810 .

IBM Corporation . An Architectural Blueprint for Autonomic Computing . [EB/OL] http://www-03.ibm.com/autonomic/pdfs/AC_Blueprint_White_Paper_4th.pdf http://www-03.ibm.com/autonomic/pdfs/AC_Blueprint_White_Paper_4th.pdf , 2017⁃06⁃24 .

Dobson S , Denazis S G , Fernández Antonio , et al . A survey of autonomic communications [J]. ACM Transactions on Autonomous and Adaptive Systems , 2006 , 1 ( 2 ): 223 - 259 .

Graziotin D , Lenberg P , Feldt R , et al . Psychometrics in Behavioral Software Engineering: a Methodological Introduction with Guidelines [EB/OL]. https://arxiv.org/pdf/2005.09959.pdf https://arxiv.org/pdf/2005.09959.pdf , 2020⁃10⁃19

Crowston K , Howison J , Annabi H . Information systems success in free and open source software development: theory and measures [J]. Software Process Improvement & Practice , 2010 , 11 ( 2 ): 123 - 148 .

Margan D , Čandrlić S . The success of open source software : A review[A]. 2015 38th International Convention on Information and Communication Technology , Electronics and Microelectronics (MIPRO) [C] . Piscataway, NJ : IEEE , 2015 . 1463 - 1468 .

Raja U , Tretter M J . Defining and evaluating a measure of open source project survivability [J]. IEEE Transactions on Software Engineering , 2012 , 38 ( 1 ): 163 - 174 .

Borges H , Tulio Valente M . What's in a GitHub star? understanding repository starring practices in a social coding platform [J]. Journal of Systems and Software , 2018 , 146 : 112 - 129 .

Jacques V . Introduction of Pygithub [DB/OL]. http://pygithub.readthedocs.io/en/latest/introduction.html , 2017⁃06⁃09 .

Hu Y , Wang S S , Ren Y Z , et al . User influence analysis for Github developer social networks [J]. Expert Systems with Applications , 2018 , 108 : 108 - 118 .

Borges H , Hora A , Valente M T . Understanding the factors that impact the popularity of GitHub repositories [A]. 2016 IEEE International Conference on Software Maintenance and Evolution (ICSME) [C]. Raleigh, NC, USA : IEEE , 2016 . 334 - 344 .

张得光 , 李兵 , 何鹏 , 等 . 基于软件生态系统的开源社区特性研究 [J]. 计算机工程 , 2015 , 41 ( 11 ): 106 - 113 .

Zhang D G , Li B , He P , et al . Characteristic study of open source community based on software ecosystem [J]. Computer Engineering , 2015 , 41 ( 11 ): 106 - 113 . (in Chinese)

宁德军 , 叶培根 , 刘琴 , 等 . 基于存储库数据挖掘的开源软件成功度量方法 [J]. 电子学报 , 2018 , 46 ( 012 ): 2930 - 2935 .

Ning D J , Ye P G , Liu Q , et al . Open source software success measurement method based on mining software repository [J]. Acta Electronica Sinica , 2018 , 46 ( 12 ): 2930 - 2935 . (in Chinese)

Wasserman A I , Guo X , Mcmillian B , et al . OSSpal: finding and evaluating open source software [A]. IFIP International Conference on Open Source Systems [C]. Buenos Aires, Argentina : Springer, Cham , 2017 . 193 - 203 .

Ghapanchi A H . Investigating the interrelationships among success measures of open source software projects [J]. Journal of Organizational Computing and Electronic Commerce , 2015 , 25 ( 1 ): 28 - 46 .

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