Experiences in testing and analysing data intensive systems

Teemu Kanstrén

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    6 Citations (Scopus)

    Abstract

    Testing software-intensive systems, for us, has traditionally focused on verifying and validating compliance and conformance to specification, as well as some general non-functional requirements such as performance of different components. In recent years, we have seen a strong move towards more data intensive systems. We have found that these types of systems require a different approach for testing and analysis, moving more towards exploring the system, its elements, behaviour and properties from a big data and analytics perspective. This paper summarizes our experiences in building and developing test and analytics environments for evaluating the performance, reliability, and security of such data-intensive systems.
    Original languageEnglish
    Title of host publication2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages589-590
    Number of pages2
    ISBN (Electronic)978-1-5386-2072-4
    ISBN (Print)978-1-5386-2073-1
    DOIs
    Publication statusPublished - 7 Aug 2017
    MoE publication typeA4 Article in a conference publication
    EventIEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C) - Prague, Czech Republic
    Duration: 25 Jul 201729 Jul 2017

    Conference

    ConferenceIEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)
    Abbreviated titleQRS-C
    CountryCzech Republic
    CityPrague
    Period25/07/1729/07/17

    Keywords

    • testing
    • security
    • software reliability
    • data models
    • big Data
    • software
    • analytics
    • reliability

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    Cite this

    Kanstrén, T. (2017). Experiences in testing and analysing data intensive systems. In 2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C) (pp. 589-590). [8004386] IEEE Institute of Electrical and Electronic Engineers. https://doi.org/10.1109/QRS-C.2017.107