dasher 4.11+git20130508.adc653-2 source package in Ubuntu
Changelog
dasher (4.11+git20130508.adc653-2) unstable; urgency=medium * Cherry-pick upstream patch to fix FTBFS (Closes: #755343) * Add myself to uploaders -- Balint Reczey <email address hidden> Thu, 30 Oct 2014 22:04:05 +0100
Upload details
- Uploaded by:
- Debian GNOME Maintainers
- Uploaded to:
- Sid
- Original maintainer:
- Debian GNOME Maintainers
- Architectures:
- any all
- Section:
- x11
- Urgency:
- Medium Urgency
See full publishing history Publishing
Series | Published | Component | Section | |
---|---|---|---|---|
Xenial | release | universe | x11 |
Downloads
File | Size | SHA-256 Checksum |
---|---|---|
dasher_4.11+git20130508.adc653-2.dsc | 2.4 KiB | 5b7089dee555cc3db274fea154448bc9e1d8d3582dcadb8df49f6869e639fddb |
dasher_4.11+git20130508.adc653.orig.tar.xz | 6.9 MiB | 5d096450c6b63a87e6ec2b6e0ac52150e37ef8ec243cd3414b876f05ebc507cb |
dasher_4.11+git20130508.adc653-2.debian.tar.xz | 6.9 KiB | dc6e140a586af5d5507ab90a648c6e577106537a8dc8b46b1cc22503bdcc7cf7 |
Available diffs
No changes file available.
Binary packages built by this source
- dasher: No summary available for dasher in ubuntu vivid.
No description available for dasher in ubuntu vivid.
- dasher-data: No summary available for dasher-data in ubuntu vivid.
No description available for dasher-data in ubuntu vivid.
- dasher-dbgsym: debug symbols for package dasher
Dasher is an information-
efficient text-entry interface, driven by natural
continuous pointing gestures. Dasher is a competitive text-entry system
wherever a full-size keyboard cannot be used - for example,
.
* on a palmtop computer
* on a wearable computer
* when operating a computer one-handed, by joystick, touchscreen, trackball,
or mouse
* when operating a computer with zero hands (i.e., by head-mouse or by
eyetracker).
.
The eyetracking version of Dasher allows an experienced user to write text
as fast as normal handwriting - 25 words per minute; using a mouse,
experienced users can write at 39 words per minute.
.
Dasher uses a more advanced prediction algorithm than the T9(tm) system
often used in mobile phones, making it sensitive to surrounding context.