Dear All,
We are happy to announce a new edition
of the Dogelog Player:
- Enhanced GC:
To lift the native stack limitations, we
opted for a marking algorithm based on
Peter Deutschs algorithm E as found in
Donald Knuths "The Art of Computing Programming"
book. Our variant uses an int field that was
anyway recently introduced for Prolog
compound coloring, so that no extra space
was introduced in this release.
- Enhanced Binary-Ops:
By adopting the pointer approach from Jaffar's
Unification we could get rid of the map based
realization from previous releases for union
find. It turns out this gives quite a speed
advantage. We also lifted the native stack
limitation by using an extra space in the
form of a stack and a log, which surprisingly
performs well especially for Java, less for
JavaScript and Python.
- Enhanced Unary-Ops:
For unary operations such as term_variables/2,
ground/1, etc.. we experimented with both
Peter Deutsch and a stack / log approaches.
Interestingly for performance reasons we had
to dismiss the two phase approach induced by
a marking algorithm such as Peter Deutsch,
and went also with the one phase approach as
offered by a stack / log realization.
Have Fun!
Jan Burse, 02.10.2025, https://www.herbrand.ai/
We present a Prolog transducer dubbed NetFish
that can be used to translate Java code into C#
code. NetFish can be built with a non-standard
version of DCG, extending the notion of semi-context
from terminals to non-terminals. NetFish can be
easily run over arbitrary long files
with little memory.
NetFish uses a sliding window along an input text.
It then applies the given compiled DSL rules in a
cascading style. We used various LLMs such as
ChatGPT and DeepSeek to advice us in the rules,
but such a process is currently not integrated.
The output can be run with .NET 9.0.
See also:
NetFish Transducer in Dogelog Player
https://medium.com/2989/9d392937c1e3
Mild Shock schrieb:
Dear All,
We are happy to announce a new edition
of the Dogelog Player:
- Enhanced GC:
To lift the native stack limitations, we
opted for a marking algorithm based on
Peter Deutschs algorithm E as found in
Donald Knuths "The Art of Computing Programming"
book. Our variant uses an int field that was
anyway recently introduced for Prolog
compound coloring, so that no extra space
was introduced in this release.
- Enhanced Binary-Ops:
By adopting the pointer approach from Jaffar's
Unification we could get rid of the map based
realization from previous releases for union
find. It turns out this gives quite a speed
advantage. We also lifted the native stack
limitation by using an extra space in the
form of a stack and a log, which surprisingly
performs well especially for Java, less for
JavaScript and Python.
- Enhanced Unary-Ops:
For unary operations such as term_variables/2,
ground/1, etc.. we experimented with both
Peter Deutsch and a stack / log approaches.
Interestingly for performance reasons we had
to dismiss the two phase approach induced by
a marking algorithm such as Peter Deutsch,
and went also with the one phase approach as
offered by a stack / log realization.
Have Fun!
Jan Burse, 02.10.2025, https://www.herbrand.ai/
Hi,
Dogelog Player is a 100% Prolog written Prolog
system for the JavaScript, Python and Java platform.
From its inception we let most of the higher order
logic programming rest in limbo. Only recently we
added call/n and maplist/n, foldl/n, etc..
The upcoming release will see the introduction of
arrow functions via (=>)/2 and filter/3, etc..
JavaScript programmers might be familiar with the
concept, only our arrow functions are boolean
arrow functions driven by the outcome of a goal.
Diverting from library(yall) of Logtalk provenance,
the syntax and semantic of our arrow functions matches
that of JavaScript. To speed up loop processing we have
already a runtime preprocessing in place. The future
might bring refinements, such as ahead of time
compilation into Albufeira anonymous predicates.
Bye
See also:
Arrow Functions in Dogelog Player https://qiita.com/j4n_bur53/items/eff987ced7b0d0c267e9
Mild Shock schrieb:
We present a Prolog transducer dubbed NetFish
that can be used to translate Java code into C#
code. NetFish can be built with a non-standard
version of DCG, extending the notion of semi-context
from terminals to non-terminals. NetFish can be
easily run over arbitrary long files
with little memory.
NetFish uses a sliding window along an input text.
It then applies the given compiled DSL rules in a
cascading style. We used various LLMs such as
ChatGPT and DeepSeek to advice us in the rules,
but such a process is currently not integrated.
The output can be run with .NET 9.0.
See also:
NetFish Transducer in Dogelog Player
https://medium.com/2989/9d392937c1e3
Mild Shock schrieb:
Dear All,
We are happy to announce a new edition
of the Dogelog Player:
- Enhanced GC:
To lift the native stack limitations, we
opted for a marking algorithm based on
Peter Deutschs algorithm E as found in
Donald Knuths "The Art of Computing Programming"
book. Our variant uses an int field that was
anyway recently introduced for Prolog
compound coloring, so that no extra space
was introduced in this release.
- Enhanced Binary-Ops:
By adopting the pointer approach from Jaffar's
Unification we could get rid of the map based
realization from previous releases for union
find. It turns out this gives quite a speed
advantage. We also lifted the native stack
limitation by using an extra space in the
form of a stack and a log, which surprisingly
performs well especially for Java, less for
JavaScript and Python.
- Enhanced Unary-Ops:
For unary operations such as term_variables/2,
ground/1, etc.. we experimented with both
Peter Deutsch and a stack / log approaches.
Interestingly for performance reasons we had
to dismiss the two phase approach induced by
a marking algorithm such as Peter Deutsch,
and went also with the one phase approach as
offered by a stack / log realization.
Have Fun!
Jan Burse, 02.10.2025, https://www.herbrand.ai/
| Sysop: | DaiTengu |
|---|---|
| Location: | Appleton, WI |
| Users: | 1,075 |
| Nodes: | 10 (0 / 10) |
| Uptime: | 94:28:48 |
| Calls: | 13,798 |
| Calls today: | 1 |
| Files: | 186,989 |
| D/L today: |
6,265 files (1,782M bytes) |
| Messages: | 2,438,400 |