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Ludwig
Advanced Cheater
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Joined: 10 Jan 2016
Posts: 68
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 Posted: Thu Sep 08, 2016 12:39 am Post subject: Simplyfying code to make it run quicker |
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Good day people
im working on a script to de-obfuscate swf files...i realize lua might not be the best tool for the job, but its all that im familiar with atm...and im not a oder...
here is one of the sections of code thats taking a lot of time...and if possible i would like to simplyfy to make it run quicker
any help is apreciated...
| Code: |
cmp_swap1=''
cmp_swap2=''
for q=1,cmp_amt-1 do--compare amount..roughly 22 000 words of variables etc
--im running through a rabcsm decompile of the file first, which i read into class, and line 2d array
if cmpare[q]~= '' then
cmp_swap1='"'..cmpare[q]..'"'
cmp_swap2='"'..cmpare[q]..'_"'
for r=1, f_b__rab_amnt do--number of classes
for rr=1, #file_array_b_rab[r] do--number of lines / class..total in all 1 700 000 lines
file_array_b_rab[r][rr] = string.gsub(file_array_b_rab[r][rr], cmp_swap1, cmp_swap2)
end
end
end
end
cmp_swap1=''
cmp_swap2=''
--showMessage("Array compare 1 done")
-- now i do the same with the AS3//jpex decompiled version of the file ...,roughly 900k lines of code to check
for q=1,cmp_amt-1 do
if cmpare[q]~= '' then
cmp_swap1=cmpare[q]
cmp_swap2=cmpare[q]..'_'
for r=1, f_b__jpex_amnt do
for rr=1, #file_array_b_jpex[r] do
x, y = string.find(file_array_b_jpex[r][rr],cmpare[q] )
if x~=nil and y ~= nil then
nxt_char=string.sub(file_array_b_jpex[r][rr],y+1, y+1)
--print(nxt_char)
if tonumber(nxt_char)==nil then--checking if the nxt character of the string ive found is indeed the correct one...some can be line var_1...where in the line its var_11, so making sure its nt a number
file_array_b_jpex[r][rr] = string.gsub(file_array_b_jpex[r][rr], cmp_swap1, cmp_swap2)
end
end
end
end
end
end |
this specific part of code takes about 7 hours to complete in the files im doing |
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panraven
Grandmaster Cheater
![]() Reputation: 55
Joined: 01 Oct 2008
Posts: 942
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| Posted: Thu Sep 08, 2016 8:25 am Post subject: |
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Break down the work load with multiple createNativeThread call may help,
but I've problem which cause access violation, so no working example, sorry.
The idea is to turn :
| Code: |
for q=1,cmp_amt-1 do
<<do on list of 1...cmp_amt-1>>
end
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to
| Code: |
local m = math.floor(cmp_amt/4) -- divid to four part
for i=1,cmp_amt-1,m do
createNativeThread(function(th, from, to)
for k = from,to do
<<do on list of from...to>>
end
end, i --[[from]], math.min(i+m-1, cmp_amt-1)--[[to]])
end
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if your pc have four core/thread, the 4 part should work on parallel.
bye~
ADDED:
make a function that use createNativeThread.
I'm confused on how to join multiple thread within a function using the Thread Class property, so I used an alternative method.
A for loop can be convert like :
| Code: |
for i=from,to do
<<block>
end
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to
| Code: |
for i=from,to do
func(i) -- convert from <<block>>
end
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then to
| Code: |
function Each(first,last,f) -- define 'Each' function
for i=first,last do
f(i)
end
end
Each(from,to,func) -- execute using Each function
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The attached function
| Code: |
function asyncPartitionEach(from,to,npart,f,...)
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is similar, but divide the loop into different Thread for execution, hopefully they will execute parallel on multi-thread environment to cut the total running time.
npart is a number from 1 to 7, which tell how many part to divide.
In a sample run of the test function on my i7 4 core/8 thread,
| Code: |
prepare
start, sampled 1000 sequencial total: 5.996 sec
1 part, 5.9930 - expected : 5.9960
2 part, 3.1040 - expected : 2.9980
3 part, 2.1410 - expected : 1.9987
4 part, 1.8760 - expected : 1.4990
5 part, 1.6170 - expected : 1.1992
6 part, 1.5370 - expected : 0.9993
7 part, 1.4920 - expected : 0.8566
done
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it can be seen that after 4 part, the speed up is diminishing. It should depend on the current os resource.
Note that, on general multi-threading computation, synchronization must be considered on updating same variable from different thread.
----
As to simplfying the code, I tried rearrange some test code, for example,
from
| Code: |
for q=1,cmp_amt-1...
for r=...
for rr=...
....gsub(some string, swap1, swap2)
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to
| Code: |
for r=...
for rr=...
....gsub(some string, Q_swap1[1], Q_swap2[1]):gsub( Q_swap1[2], Q_swap2[2]):...:gsub( Q_swap1[cmp_amt-1], Q_swap2[cmp_amt-1])
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where the last part is made to a single function outside the r/rr loop, hopefully save some looping overhead. But the result on running time really have no different.
I think as long as each q,r,rr has to be loop through, the total raw cpu execution time cannot be cut down significantly.
bye~
_________________
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Ludwig
Advanced Cheater
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Joined: 10 Jan 2016
Posts: 68
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| Posted: Fri Sep 09, 2016 12:37 am Post subject: |
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damn..thnx a lot bro...ill give it some thought and try to figure this out...its a lot to take in...
hope i dont get lost on this |
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