Semenenko nataliia (8 risultati)
Lingua: Inglese
Editore: VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2014
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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EUR 65,10
EUR 3,49 spedizioneSpedito in U.S.A.Quantità: 4 disponibili
Condizione: New. pp. 68.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 39,90
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Due to the rapid evolution of Web technologies and the failure of Web standards to uniformize every single technology evolution, Web developers are faced with the challenge of ensuring that their applications are correctly rendered… across a broad range of browsers and platforms. To detect cross-browser incompatibilities, developers often resort to visually checking that each document produced by their application is consistently rendered across all relevant browsers. This manual testing approach is time consuming and error-prone. Existing cross-browser compatibility testing tools speed up this process. However, existing tools in this space suffer from over-sensitivity. Reducing the number of false positives produced by these testing tools is challenging, since defining criteria for classifying a difference as an incompatibility is to some extent subjective. This work presents a machine learning approach to improve the accuracy of two techniques for cross-browser compatibility testing - one based on image analysis and one based on DOM analysis. Two classification algorithms were used, namely classification trees and neural networks. 68 pp. Englisch.
Lingua: Inglese
Editore: VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2014
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 65,08
EUR 7,61 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Condizione: New. Print on Demand pp. 68 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.
Lingua: Inglese
Editore: VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2014
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 65,69
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND pp. 68.
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Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 34,25
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Semenenko NataliiaNataliia started her studies in NTUU KPI , Kyiv, Ukraine. After completing her bachelor degree in Computer Science she moved to Estonia for Software Engineering Master programme in Ta…rtu University which she succes.
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 39,90
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Due to the rapid evolution of Web technologies and the failure of Web standards to uniformize every single technology evolution, Web developers are faced with the challenge of ensuring that their applications are correctly rendered acr…oss a broad range of browsers and platforms. To detect cross-browser incompatibilities, developers often resort to visually checking that each document produced by their application is consistently rendered across all relevant browsers. This manual testing approach is time consuming and error-prone. Existing cross-browser compatibility testing tools speed up this process. However, existing tools in this space suffer from over-sensitivity. Reducing the number of false positives produced by these testing tools is challenging, since defining criteria for classifying a difference as an incompatibility is to some extent subjective. This work presents a machine learning approach to improve the accuracy of two techniques for cross-browser compatibility testing ¿ one based on image analysis and one based on DOM analysis. Two classification algorithms were used, namely classification trees and neural networks.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 40,89
EUR 60,60 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Due to the rapid evolution of Web technologies and the failure of Web standards to uniformize every single technology evolution, Web developers are faced with the challenge of ensuring that their applications are correctly rendered acro…ss a broad range of browsers and platforms. To detect cross-browser incompatibilities, developers often resort to visually checking that each document produced by their application is consistently rendered across all relevant browsers. This manual testing approach is time consuming and error-prone. Existing cross-browser compatibility testing tools speed up this process. However, existing tools in this space suffer from over-sensitivity. Reducing the number of false positives produced by these testing tools is challenging, since defining criteria for classifying a difference as an incompatibility is to some extent subjective. This work presents a machine learning approach to improve the accuracy of two techniques for cross-browser compatibility testing - one based on image analysis and one based on DOM analysis. Two classification algorithms were used, namely classification trees and neural networks.
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- Print on Demand
Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 35,60
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. Diagnosis of Cross-Browser Compatibility Issues via Machine Learning | Nataliia Semenenko | Taschenbuch | 68 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659185564 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[…dot]de | Anbieter: preigu Print on Demand.
