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A testing data validity assessment method and testing data validation platform based on SOA

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Abstract

In modern manufacturing, ensuring the quality of component testing data is highly valued by both product manufacturers and component suppliers. However, in common component quality analysis processes, testing data are assumed to be valid, which might not be true. Therefore, assessing the validity of component testing data would be important. Many existing data analysis platforms are separated from enterprises’ own systems, which makes the inspection data analysis incoherent to their business process. In this paper, we propose a testing data quality assessment method and a testing data validation platform based on SOA. The platform provides reliable third-party testing data validation service via RESTful APIs, so that the services can be seamlessly integrated to enterprise systems. The testing data validity assessment method, which is the core of the platform, is implemented by detecting illegal behavior in data recording. The detection is a combination of behavior analysis and a positive and unlabeled learning process.

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Acknowledgements

This research is supported by the Shanghai Institute of Precision Measurement Project under Grand No. SAST2017-128 and the National Natural Science Foundation of China under Grant No. 61373030.

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Authors and Affiliations

  1. School of Software, Shanghai Jiao Tong University, Shanghai, China

    Beige Zhang, Lihong Jiang & Hongming Cai

  2. China Shanghai Institute of Precision Measurement and Testing, Shanghai, China

    Chun Li

  3. Faculty of Engineering and Computing, Coventry University, Coventry, UK

    Nazaraf Shah & Xiang Fei

Authors
  1. Beige Zhang
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  2. Chun Li
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  3. Nazaraf Shah
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  4. Xiang Fei
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  5. Lihong Jiang
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  6. Hongming Cai
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Corresponding author

Correspondence to Hongming Cai.

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Zhang, B., Li, C., Shah, N. et al. A testing data validity assessment method and testing data validation platform based on SOA. SOCA 12, 201–209 (2018). https://doi.org/10.1007/s11761-018-0242-4

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  • DOI: https://doi.org/10.1007/s11761-018-0242-4

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