IVVES (Industrial-Grade Verification and Validation of Evolving Systems)

Pekka Aho; Tanja E. J. Vos; Otto Sybrandi; Sorin Patrasoiu; Joona Oikarinen; Olivia Rodriguez Valdes; Lianne V. Hufkens

IVVES (Industrial-Grade Verification and Validation of Evolving Systems)

Pekka Aho
, Tanja E. J. Vos
, Otto Sybrandi
, Sorin Patrasoiu
, Joona Oikarinen
, Olivia Rodriguez Valdes
, Lianne V. Hufkens

Research output: Contribution to conference › Conference Paper until 1 July 2025 › Academic

Abstract

Anincreasing numberofinformationsystemsarebasedonmachinelearning(ML)orartificialintelligence (AI). In some cases, the systems are adapting their behaviour during operation based on the data being gathered. This introduces new challenges for verification, validation and software testing. The traditional way of testing the systems during the development and before the deployment does not suffice anymore. IVVES (Industrial-Grade Verification and Validation of Evolving Systems) project aims to address these challenges by researching and developing methods to test ML and AI solutions and evolving systems, and using AI and ML to improve and automate development and testing. We summarise the results of the project at a high level, and provide more details on the research and collaboration related to scriptless end-to-end testing through graphical user interface.

Original language	English
Number of pages	8
Publication status	Published - 19 May 2022
Event	16th International Conference on Research Challenges in Information Science - Barcelona, Spain Duration: 17 May 2022 → 20 May 2022 https://www.rcis-conf.com/rcis2022/

Conference

Conference	16th International Conference on Research Challenges in Information Science
Abbreviated title	RCIS 2022
Country/Territory	Spain
City	Barcelona
Period	17/05/22 → 20/05/22
Internet address	https://www.rcis-conf.com/rcis2022/

Access to Document

https://dblp.org/rec/conf/rcis/AhoVSPOVH22Licence: CC BY

Cite this

@conference{39fac7e658ba49278e1b8cc37a9093f8,

title = "IVVES (Industrial-Grade Verification and Validation of Evolving Systems)",

abstract = "Anincreasing numberofinformationsystemsarebasedonmachinelearning(ML)orartificialintelligence (AI). In some cases, the systems are adapting their behaviour during operation based on the data being gathered. This introduces new challenges for verification, validation and software testing. The traditional way of testing the systems during the development and before the deployment does not suffice anymore. IVVES (Industrial-Grade Verification and Validation of Evolving Systems) project aims to address these challenges by researching and developing methods to test ML and AI solutions and evolving systems, and using AI and ML to improve and automate development and testing. We summarise the results of the project at a high level, and provide more details on the research and collaboration related to scriptless end-to-end testing through graphical user interface.",

author = "Pekka Aho and Vos, \{Tanja E. J.\} and Otto Sybrandi and Sorin Patrasoiu and Joona Oikarinen and Valdes, \{Olivia Rodriguez\} and Hufkens, \{Lianne V.\}",

note = "DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.; 16th International Conference on Research Challenges in Information Science, RCIS 2022 ; Conference date: 17-05-2022 Through 20-05-2022",

year = "2022",

month = may,

day = "19",

language = "English",

url = "https://www.rcis-conf.com/rcis2022/",

}

TY - CONF

T1 - IVVES (Industrial-Grade Verification and Validation of Evolving Systems)

AU - Aho, Pekka

AU - Vos, Tanja E. J.

AU - Sybrandi, Otto

AU - Patrasoiu, Sorin

AU - Oikarinen, Joona

AU - Valdes, Olivia Rodriguez

AU - Hufkens, Lianne V.

N1 - DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

PY - 2022/5/19

Y1 - 2022/5/19

N2 - Anincreasing numberofinformationsystemsarebasedonmachinelearning(ML)orartificialintelligence (AI). In some cases, the systems are adapting their behaviour during operation based on the data being gathered. This introduces new challenges for verification, validation and software testing. The traditional way of testing the systems during the development and before the deployment does not suffice anymore. IVVES (Industrial-Grade Verification and Validation of Evolving Systems) project aims to address these challenges by researching and developing methods to test ML and AI solutions and evolving systems, and using AI and ML to improve and automate development and testing. We summarise the results of the project at a high level, and provide more details on the research and collaboration related to scriptless end-to-end testing through graphical user interface.

AB - Anincreasing numberofinformationsystemsarebasedonmachinelearning(ML)orartificialintelligence (AI). In some cases, the systems are adapting their behaviour during operation based on the data being gathered. This introduces new challenges for verification, validation and software testing. The traditional way of testing the systems during the development and before the deployment does not suffice anymore. IVVES (Industrial-Grade Verification and Validation of Evolving Systems) project aims to address these challenges by researching and developing methods to test ML and AI solutions and evolving systems, and using AI and ML to improve and automate development and testing. We summarise the results of the project at a high level, and provide more details on the research and collaboration related to scriptless end-to-end testing through graphical user interface.

UR - https://www.rcis-conf.com/rcis2022/program.php

M3 - Conference Paper until 1 July 2025

T2 - 16th International Conference on Research Challenges in Information Science

Y2 - 17 May 2022 through 20 May 2022

ER -

IVVES (Industrial-Grade Verification and Validation of Evolving Systems)

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Cite this