User agent detail

SoftBank/1.0/932SH/SHJ003/SN353700022260911 Browser/NetFront/3.5 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 3.5 Sharp932SHmobile:featureyes Detail
Providers
BrowscapPhp
6012
NetFront 3.5NetFront Mobile Deviceyes0.02 Detail
DonatjUAParser
v0.5.0
SoftBank 1.0closeclosecloseclosecloseclosecloseclosecloseclose0 Detail
NeutrinoApiCom
NetFront 3.5closeJVM Softbank932SHmobile-browseryescloseclose0.20102 Detail
PiwikDeviceDetector
3.5.2
NetFront 3.5NetFront Softbank932SHsmartphoneyes0.005 Detail
SinergiBrowserDetector
6.0.0
No result found
UAParser
v3.4.5
NetFront 3.5close closeclosecloseclose0.006 Detail
UserAgentStringCom
NetFront 3.5close closecloseclosecloseclose0.09101 Detail
WhatIsMyBrowserCom
NetFront closeclosecloseclosecloseclose3.64837 Detail
WhichBrowser
2.0.10
NetFront 3.5 Sharp932SHmobile:featureyescloseclose0.003 Detail
Woothee
v1.2.0
SoftBank Mobile 932SHcloseclosecloseclosemobilephoneclosecloseclose0 Detail
Wurfl
1.6.4
NetFront 3.5close Softbank932SHFeature Phoneyescloseclose0.014 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 13:40:45 | by ThaDafinser