Experiences in testing and analysing data intensive systems

Teemu Kanstrén

doi:10.1109/QRS-C.2017.107

Experiences in testing and analysing data intensive systems

Teemu Kanstrén

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

11 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 language	English
Title of host publication	2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	589-590
ISBN (Electronic)	978-1-5386-2072-4
ISBN (Print)	978-1-5386-2073-1
DOIs	https://doi.org/10.1109/QRS-C.2017.107
Publication status	Published - 7 Aug 2017
MoE publication type	A4 Article in a conference publication
Event	IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C) - Prague, Czech Republic Duration: 25 Jul 2017 → 29 Jul 2017

Conference

Conference	IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)
Abbreviated title	QRS-C
Country/Territory	Czech Republic
City	Prague
Period	25/07/17 → 29/07/17

Keywords

testing
security
software reliability
data models
big Data
software
analytics
reliability

Access to Document

10.1109/QRS-C.2017.107

Cite this

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title = "Experiences in testing and analysing data intensive systems",

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.",

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author = "Teemu Kanstr{\'e}n",

year = "2017",

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day = "7",

doi = "10.1109/QRS-C.2017.107",

language = "English",

isbn = "978-1-5386-2073-1",

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booktitle = "2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)",

publisher = "IEEE Institute of Electrical and Electronic Engineers",

address = "United States",

note = "IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C), QRS-C ; Conference date: 25-07-2017 Through 29-07-2017",

}

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)., 8004386, IEEE Institute of Electrical and Electronic Engineers, pp. 589-590, IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C), Prague, Czech Republic, 25/07/17. https://doi.org/10.1109/QRS-C.2017.107

Experiences in testing and analysing data intensive systems. / Kanstrén, Teemu.
2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C). IEEE Institute of Electrical and Electronic Engineers, 2017. p. 589-590 8004386.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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PY - 2017/8/7

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N2 - 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.

AB - 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.

KW - testing

KW - security

KW - software reliability

KW - data models

KW - big Data

KW - software

KW - analytics

KW - reliability

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DO - 10.1109/QRS-C.2017.107

M3 - Conference article in proceedings

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BT - 2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)

PB - IEEE Institute of Electrical and Electronic Engineers

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Y2 - 25 July 2017 through 29 July 2017

ER -

Experiences in testing and analysing data intensive systems

Abstract

Conference

Keywords

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SENDATE-PLANETS: Secure Networking for a Data Center Cloud in Europe

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Experiences in testing and analysing data intensive systems

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Projects

SENDATE-PLANETS: Secure Networking for a Data Center Cloud in Europe

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