User agent detail

SoftBank/2.0/004SH/SHJ001/SN000000000000000 Browser/NetFront/3.5 Profile/MIDP-2.0 Configuration/CLDC-1.1
GeneralDeviceBot
ProviderBrowserEngineOSBrandModelTypeIs mobileIs touchIs botNameTypeParse timeActions
Source result (test suite)
woothee/woothee-testset
/testsets/mobilephone_softbank.yaml
SoftBank Mobile 004SHSoftBank mobilephone Detail
Providers
BrowscapPhp
6012
NetFront 3.5NetFront Mobile Deviceyes0.023 Detail
DonatjUAParser
v0.5.0
SoftBank 2.0closeclosecloseclosecloseclosecloseclosecloseclose0 Detail
NeutrinoApiCom
NetFront 3.5closeJVM Softbank004SHmobile-browseryescloseclose0.17705 Detail
PiwikDeviceDetector
3.5.2
NetFront 3.5NetFront Softbank004SHsmartphoneyes0.013 Detail
SinergiBrowserDetector
6.0.0
No result found
UAParser
v3.4.5
NetFront 3.5close closeclosecloseclose0.007 Detail
UserAgentStringCom
NetFront 3.5close closecloseclosecloseclose0.11703 Detail
WhatIsMyBrowserCom
NetFront closeclosecloseclosecloseclose0.50715 Detail
WhichBrowser
2.0.10
NetFront 3.5 Sharp004SHmobile:featureyescloseclose0.003 Detail
Woothee
v1.2.0
SoftBank Mobile 004SHcloseclosecloseclosemobilephoneclosecloseclose0 Detail
Wurfl
1.6.4
NetFront 3.5close Softbank004SHFeature Phoneyescloseclose0.024 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 13:37:31 | by ThaDafinser