Sidereal: Statistical adaptive generation of robust locators for web testing
Informazioni aggiuntive
Autori
Leotta M.,
Ricca F.,
Tonella P.
Tipo
Articolo pubblicato in rivista scientifica
Anno
2021
Lingua
Inglese
Sommario
SummaryBy ensuring adequate functional coverage, End‐to‐End (E2E) testing is a key enabling factor of continuous integration. This is even more true for web applications, where automated E2E testing is the only way to exercise the full stack used to create a modern application. The test code used for web testing usually relies on DOM locators, often expressed as XPath expressions, to identify the web elements and to extract the data checked in assertions. When applications evolve, the most dominant cost for the evolution of test code is due to broken locators, which fail to locate the target element in the novel versions and must be repaired. In this paper, we formulate the robust XPath locator generation problem as a graph exploration problem, instead of relying on ad‐hoc heuristics as the one implemented by the state of the art tool robula+. Our approach is based on a statistical adaptive algorithm implemented by the tool sidereal, which outperforms robula+'s heuristics in terms of robustness by learning the potential fragility of HTML properties from previous versions of the application under test. sidereal was applied to six applications and to a total of 611 locators and was compared against two baseline algorithms, robula+ and Montoto. The adoption of sidereal results in a significant reduction of the number of broken locators (respectively ‐55% and ‐70%). The time for generating such robust locators was deemed acceptable being in the order of hundredths of second.
Periodico
Software Testing, Verification and Reliability
Volume
31
Numero ( Mese )
3
Pagine (o numero dell’articolo)
e1767
ISSN
0960-0833, 1099-1689
Diffusione
Licenza
Licenza non definita
Visibilità
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