User agent detail

Vodafone/1.0/V905SH/SHJ001 Browser/VF-NetFront/3.3 Profile/MIDP-2.0 Configuration/CLDC-1.1
GeneralDeviceBot
ProviderBrowserEngineOSBrandModelTypeIs mobileIs touchIs botNameTypeParse timeActions
Source result (test suite)
whichbrowser/parser
/tests/data/mobile/carrier-softbank.yaml
NetFront 3.3 SharpV905SHmobile:featureyes Detail
Providers
BrowscapPhp
6012
NetFront 3.3NetFront Mobile Deviceyes0.019 Detail
DonatjUAParser
v0.5.0
Vodafone 1.0closeclosecloseclosecloseclosecloseclosecloseclose0 Detail
NeutrinoApiCom
NetFront 3.3closeJVM Softbank905SHmobile-browseryescloseclose0.18502 Detail
PiwikDeviceDetector
3.5.2
No result found
SinergiBrowserDetector
6.0.0
No result found
UAParser
v3.4.5
NetFront 3.3close closeclosecloseclose0.013 Detail
UserAgentStringCom
NetFront 3.3close closecloseclosecloseclose0.04601 Detail
WhatIsMyBrowserCom
NetFront closeclosecloseclosecloseclose0.42004 Detail
WhichBrowser
2.0.10
NetFront 3.3 SharpV905SHmobile:featureyescloseclose0.003 Detail
Woothee
v1.2.0
SoftBank Mobile V905SHcloseclosecloseclosemobilephoneclosecloseclose0.001 Detail
Wurfl
1.6.4
NetFront 3.3close Softbank905SHFeature Phoneyescloseclose0.015 Detail

About this comparison

The primary goal of this project is simple
I wanted to know which user agent parser is the most accurate in each part - device detection, bot detection and so on...

The secondary goal is to provide a source for all user agent parsers to improve their detection based on this results.

You can also improve this further, by suggesting ideas at ThaDafinser/UserAgentParserComparison

The comparison is based on the abstraction by ThaDafinser/UserAgentParser
Comparison created 2016-02-13 13:38:16 | by ThaDafinser