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Sei Lisa 281ff4d96a Strings representing denormals no longer give 0 when cast to float

This annoyance and discrepancy with LSO was finally fixed by Linden Lab. The change has prompted some modifications to the test suite to accommodate for the new results. A further improvement has been to make these tests more friendly to be run in SL, making it easier to verify the results.

Fixes #17.

Reported by SaladDais@users.noreply.github.com - thanks!

2022-05-17 13:48:05 +02:00

lslopt

Strings representing denormals no longer give 0 when cast to float

2022-05-17 13:48:05 +02:00

pcpp @ 18d5bc4cdb

Update to latest pcpp, remove expression evaluator

2020-11-04 13:09:34 +01:00

unit_tests

Strings representing denormals no longer give 0 when cast to float

2022-05-17 13:48:05 +02:00

.gitignore

Add the outfile.tmp file generated by a test to .gitignore

2019-01-15 23:22:02 +01:00

.gitmodules

Don't report pcpp as modified if it has untracked files

2019-01-12 20:33:52 +01:00

builtins-unittest.txt

Get rid of builtins.txt.dat by adding a parameter to the parser ctor.

2015-07-09 20:35:14 +02:00

builtins.txt

New constants and functions; some refactoring of lslfuncopt

2022-05-13 14:49:18 +02:00

COPYING

Add copyright notices to all files, to prepare the program for release.

2015-03-05 23:18:41 +01:00

cpreproc.py

Update copyright year

2021-01-05 23:27:21 +01:00

fndata.txt

New constants and functions; some refactoring of lslfuncopt

2022-05-13 14:49:18 +02:00

main.py

Update copyright year

2021-01-05 23:27:21 +01:00

README.md

Update link to point to lsl.blacktulip-virtual.com instead of lsl.project.zone

2018-01-18 15:41:28 +01:00

run-tests.py

Update copyright year

2021-01-05 23:27:21 +01:00

strutil.py

Update copyright year

2021-01-05 23:27:21 +01:00

README.md

LSL PyOptimizer

LSL PyOptimizer is a LSL2 script optimizer written in Python 2. Currently it only supports code memory optimization (no speed optimization), only for Mono (no LSO), and only for the Second Life flavour of LSL (no OpenSim etc.).

HTML introduction, list of features and documentation available at http://lsl.blacktulip-virtual.com/lsl-pyoptimizer/