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Software Validation and Preventive Software Quality Assurance for Metrology

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Data Modeling for Metrology and Testing in Measurement Science

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Summary

As everywhere in technological development, IT has become an indispensable part of metrology. Modern measuring instrumentsrely on embedded software. Data obtained through measurement are transferred via communication networks and processed further bysoftware systems. This development has led to increasingly complex and distributed metrological functions. This complexity has different facets: it can not only enhance the functionality of a measuring system itself including self-checking facilities, but also the distribution and transmission of measurement data and the methods used for data analysis. One can say that IT opens up a new world of concepts that essentially contribute to the development of metrology. In this, different fields of information technology have to be taken into account, extending from software engineering, computational methods, databases, communication technology, and security techniques to knowledge-based systems. This chapter of the book gives a survey of the software validation and software engineering methods in metrology. For a better illustration, the accompanying DVD presents two case studies of validation procedures performed at PTB. Finally, an outlook on future issues is given.

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Authors and Affiliations

  1. Physikalisch-Technische Bundesanstalt, Abbestrasse 2-12, 10587 Berlin, Germany

    Norbert Greif & Dieter Richter

Authors
  1. Norbert Greif
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  2. Dieter Richter
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Corresponding author

Correspondence to Norbert Greif .

Editor information

Editors and Affiliations

  1. Metrologica (INRIM), Divisione Termodinamica, Istituto Nazionale di Ricerca, Strada delle Cacce 73, Torino, 10135, Italy

    Franco Pavese

  2. MSC , Module 13 , National Physics Laboratory , Hampton Road, Teddington, Middlesex, TW11 0LW, United Kingdom

    Alistair B. Forbes

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© 2009 Birkhäuser Boston

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Greif, N., Richter, D. (2009). Software Validation and Preventive Software Quality Assurance for Metrology. In: Pavese, F., Forbes, A. (eds) Data Modeling for Metrology and Testing in Measurement Science. Modeling and Simulation in Science, Engineering and Technology. Birkhäuser Boston. https://doi.org/10.1007/978-0-8176-4804-6_12

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