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Measuring a HTML5 Hybrid Application's Native Bridge on iOS

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dc.date.accessioned 2016-08-17T09:59:46Z und
dc.date.accessioned 2017-10-24T12:24:17Z
dc.date.available 2016-08-17T09:59:46Z und
dc.date.available 2017-10-24T12:24:17Z
dc.date.issued 2016-08-17T09:59:46Z
dc.identifier.uri http://radr.hulib.helsinki.fi/handle/10138.1/5695 und
dc.identifier.uri http://hdl.handle.net/10138.1/5695
dc.title Measuring a HTML5 Hybrid Application's Native Bridge on iOS en
ethesis.discipline Computer science en
ethesis.discipline Tietojenkäsittelytiede fi
ethesis.discipline Datavetenskap sv
ethesis.discipline.URI http://data.hulib.helsinki.fi/id/1dcabbeb-f422-4eec-aaff-bb11d7501348
ethesis.department.URI http://data.hulib.helsinki.fi/id/225405e8-3362-4197-a7fd-6e7b79e52d14
ethesis.department Institutionen för datavetenskap sv
ethesis.department Department of Computer Science en
ethesis.department Tietojenkäsittelytieteen laitos fi
ethesis.faculty Matematisk-naturvetenskapliga fakulteten sv
ethesis.faculty Matemaattis-luonnontieteellinen tiedekunta fi
ethesis.faculty Faculty of Science en
ethesis.faculty.URI http://data.hulib.helsinki.fi/id/8d59209f-6614-4edd-9744-1ebdaf1d13ca
ethesis.university.URI http://data.hulib.helsinki.fi/id/50ae46d8-7ba9-4821-877c-c994c78b0d97
ethesis.university Helsingfors universitet sv
ethesis.university University of Helsinki en
ethesis.university Helsingin yliopisto fi
dct.creator Paksula, Matti
dct.issued 2016
dct.language.ISO639-2 eng
dct.abstract Mobile apps are intended to be created with mobile platforms development tools and programming languages. This native development requires specialized skills and can therefore be prohibitively expensive. HTML5 hybrid app development is a popular alternative for native mobile app development. This development model allows developers to use standard web technologies and the end result can be indistinguishable from a native app by its visual representation. This model enables faster iteration speed, allows any web developer to build apps and supports simultaneous cross-platform development. However, since the web technology is not as performant as native, these hybrid apps have often been criticized for being noticeably 'laggy' by the app developer community and end users. One of the key components that affects HTML5 hybrid apps performance is the native bridge used in the app. This component bridges the embedded HTML5 application to the device features that wouldn't otherwise be available (such as writing to a file on the device's file system). The native bridge is one of the few components that a developer can freely change. Selecting the best native bridge for the app's needs is important as an inefficient native bridge can cause human noticeable delay in the app. The performance of native bridges has been acknowledged in academia and industry, but very little researched systematically. This thesis introduces a systematic method to evaluate native bridges performance. Along with this method, this thesis also describes a new open source tool implementing this method for benchmarking different native bridges. This tool hosts reference implementation for 32 native bridges. Example results from a test suite that tested all implemented native bridges with two embeddable web view engines (UIWebView and WKWebView) on four distinct iOS devices (two iPads, iPhone and iPod Touch) are evaluated. The results show that the majority of the known native bridge methods can cause human noticeable visual and auditory latency. It is also indicated that the performance is largely affected by app usage patterns. The slowest measured native bridge was over two times slower (from no delay to significant user interface delay) than the fastest one. en
dct.language en
ethesis.language.URI http://data.hulib.helsinki.fi/id/languages/eng
ethesis.language English en
ethesis.language englanti fi
ethesis.language engelska sv
ethesis.thesistype pro gradu-avhandlingar sv
ethesis.thesistype pro gradu -tutkielmat fi
ethesis.thesistype master's thesis en
ethesis.thesistype.URI http://data.hulib.helsinki.fi/id/thesistypes/mastersthesis
dct.identifier.urn URN:NBN:fi-fe2017112251304
dc.type.dcmitype Text

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