dc.creator | Martín López, Alberto | es |
dc.date.accessioned | 2022-05-24T11:34:04Z | |
dc.date.available | 2022-05-24T11:34:04Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Martín López, A. (2020). AI-driven web API testing. En ICSE 2020: ACM/IEEE 42nd International Conference on Software Engineering: Companion (202-205), Seoul, South Korea: Association for Computing Machinery (ACM). | |
dc.identifier.isbn | 978-1-4503-7122-3 | es |
dc.identifier.uri | https://hdl.handle.net/11441/133617 | |
dc.description.abstract | Testing of web APIs is nowadays more critical than ever before,
as they are the current standard for software integration. A bug
in an organization’s web API could have a huge impact both in ternally (services relying on that API) and externally (third-party
applications and end users). Most existing tools and testing ap proaches require writing tests or instrumenting the system under
test (SUT). The main aim of this dissertation is to take web API
testing to an unprecedented level of automation and thoroughness.
To this end, we plan to apply artificial intelligence (AI) techniques
for the autonomous detection of software failures. Specifically, the
idea is to develop intelligent programs (we call them “bots”) ca pable of generating hundreds, thousands or even millions of test
inputs and to evaluate whether the test outputs are correct based
on: 1) patterns learned from previous executions of the SUT; and 2)
knowledge gained from analyzing thousands of similar programs.
Evaluation results of our initial prototype are promising, with bugs
being automatically detected in some real-world APIs. | es |
dc.description.sponsorship | Ministerio de Economía y Competitividad BELI (TIN2015-70560-R) | es |
dc.description.sponsorship | Ministerio de Ciencia, Innovación y Universidades RTI2018-101204-B-C21 (HORATIO) | es |
dc.description.sponsorship | Ministerio de Educación, Cultura y Deporte FPU17/04077 | es |
dc.format | application/pdf | es |
dc.format.extent | 4 | es |
dc.language.iso | eng | es |
dc.publisher | Association for Computing Machinery (ACM) | es |
dc.relation.ispartof | ICSE 2020: ACM/IEEE 42nd International Conference on Software Engineering: Companion (2020), pp. 202-205. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Web APIs | es |
dc.subject | RESTful API | es |
dc.subject | Testing framework | es |
dc.subject | Automated software testing | es |
dc.subject | Artificial Intelligence | es |
dc.title | AI-driven web API testing | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dc.type.version | info:eu-repo/semantics/submittedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.relation.projectID | BELI (TIN2015-70560-R) | es |
dc.relation.projectID | RTI2018-101204-B-C21 (HORATIO) | es |
dc.relation.projectID | FPU17/04077 | es |
dc.relation.publisherversion | https://dl.acm.org/doi/10.1145/3377812.3381388 | es |
dc.identifier.doi | 10.1145/3377812.3381388 | es |
dc.contributor.group | Universidad de Sevilla. TIC205: Ingeniería del Software Aplicada | es |
dc.publication.initialPage | 202 | es |
dc.publication.endPage | 205 | es |
dc.eventtitle | ICSE 2020: ACM/IEEE 42nd International Conference on Software Engineering: Companion | es |
dc.eventinstitution | Seoul, South Korea | es |
dc.relation.publicationplace | New York, USA | es |
dc.contributor.funder | Ministerio de Economía y Competitividad (MINECO). España | es |
dc.contributor.funder | Ministerio de Ciencia, Innovación y Universidades (MICINN). España | es |
dc.contributor.funder | Ministerio de Educación, Cultura y Deporte (MECD). España | es |