Ai for software quality assurance blue sky ideas talk

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

Abstract

Modern software systems are highly complex and often have multiple dependencies on external parts such as other processes or services. This poses new challenges and exacerbate existing challenges in different aspects of software Quality Assurance (QA) including testing, debugging and repair. The goal of this talk is to present a novel AI paradigm for software QA (AI4QA). A quality assessment AI agent uses machinelearning techniques to predict where coding errors are likely to occur. Then a test generation AI agent considers the error predictions to direct automated test generation. Then a test execution AI agent executes tests, that are passed to the rootcause analysis AI agent, which applies automatic debugging algorithms. The candidate root causes are passed to a code repair AI agent that tries to create a patch for correcting the isolated error.

Original languageEnglish
Title of host publicationAAAI 2020 - 34th AAAI Conference on Artificial Intelligence
PublisherAAAI press
Pages13529-13533
Number of pages5
ISBN (Electronic)9781577358350
StatePublished - 1 Jan 2020
Event34th AAAI Conference on Artificial Intelligence, AAAI 2020 - New York, United States
Duration: 7 Feb 202012 Feb 2020

Publication series

NameAAAI 2020 - 34th AAAI Conference on Artificial Intelligence

Conference

Conference34th AAAI Conference on Artificial Intelligence, AAAI 2020
Country/TerritoryUnited States
CityNew York
Period7/02/2012/02/20

ASJC Scopus subject areas

  • Artificial Intelligence

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