User agent detail

SoftBank/2.0/944SH/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 944SHSoftBank mobilephone Detail
Providers
BrowscapPhp
6012
NetFront 3.5NetFront Mobile Deviceyes0.032 Detail
DonatjUAParser
v0.5.0
SoftBank 2.0closeclosecloseclosecloseclosecloseclosecloseclose0 Detail
NeutrinoApiCom
NetFront 3.5closeJVM Softbank944SHmobile-browseryescloseclose0.2 Detail
PiwikDeviceDetector
3.5.2
NetFront 3.5NetFront Softbank944SHsmartphoneyes0.006 Detail
SinergiBrowserDetector
6.0.0
No result found
UAParser
v3.4.5
NetFront 3.5close closeclosecloseclose0.012 Detail
UserAgentStringCom
NetFront 3.5close closecloseclosecloseclose0.065 Detail
WhatIsMyBrowserCom
NetFront closeclosecloseclosecloseclose0.409 Detail
WhichBrowser
2.0.10
NetFront 3.5 Sharp944SHmobile:featureyescloseclose0.003 Detail
Woothee
v1.2.0
SoftBank Mobile 944SHcloseclosecloseclosemobilephoneclosecloseclose0.002 Detail
Wurfl
1.6.4
NetFront 3.5close Softbank944SHFeature Phoneyescloseclose0.02 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 13:43:04 | by ThaDafinser