Provengo: A Tool Suite for Scenario Driven Model-Based Testing

Michael Bar-Sinai, Achiya Elyasaf, Gera Weiss, Yeshayahu Weiss

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

Abstract

We present Provengo, a comprehensive suite of tools designed to facilitate the implementation of Scenario-Driven Model-Based Testing (SDMBT), an innovative approach that utilizes scenarios to construct a model encompassing the user's perspective and the system's business value while also defining the desired outcomes. With the assistance of Provengo, testers gain the ability to effortlessly create natural user stories and seamlessly integrate them into a model capable of generating effective tests. The demonstration illustrates how SDMBT effectively addresses the bootstrapping challenge commonly encountered in model-based testing (MBT) by enabling incremental development, starting from simple models and gradually augmenting them with additional stories.

Original languageEnglish
Title of host publicationProceedings - 2023 38th IEEE/ACM International Conference on Automated Software Engineering, ASE 2023
PublisherInstitute of Electrical and Electronics Engineers
Pages2062-2065
Number of pages4
ISBN (Electronic)9798350329964
DOIs
StatePublished - 1 Jan 2023
Event38th IEEE/ACM International Conference on Automated Software Engineering, ASE 2023 - Echternach, Luxembourg
Duration: 11 Sep 202315 Sep 2023

Publication series

NameProceedings - 2023 38th IEEE/ACM International Conference on Automated Software Engineering, ASE 2023

Conference

Conference38th IEEE/ACM International Conference on Automated Software Engineering, ASE 2023
Country/TerritoryLuxembourg
CityEchternach
Period11/09/2315/09/23

ASJC Scopus subject areas

  • Software
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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