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	<title>SE250:lab-5:twon069 - Revision history</title>
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		<id>https://wiki.kram.nz/index.php?title=SE250:lab-5:twon069&amp;diff=6886&amp;oldid=prev</id>
		<title>Mark: 10 revision(s)</title>
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		<updated>2008-11-03T05:19:57Z</updated>

		<summary type="html">&lt;p&gt;10 revision(s)&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;==Task 1==&lt;br /&gt;
*Ok, so this is a tough lab indeed, had quite a lot of problem because realizing the code doesn&amp;#039;t work on Visual Studio so had to have cygwin set up on my computer at home to finish this lab. (took quite a while because I&amp;#039;m a total newbie at these shell stuff, however bvic helped a lot on the forum, so thanks!)&lt;br /&gt;
&lt;br /&gt;
*During the lab, it took quite a while to figure out what the output meant and understanding the codes, luckily HTTB from last year was great and had explanation to each of the output, so that got my started.&lt;br /&gt;
&lt;br /&gt;
===Determining the Sample Size===&lt;br /&gt;
*Ran a range of sample size to determine when the randomness start to not varie a lot&lt;br /&gt;
Results are:&lt;br /&gt;
&amp;lt;pre&amp;gt;&lt;br /&gt;
SS = 10		3.584963	55%	50%	126.0833   36.34%	-0.341362&lt;br /&gt;
SS = 100	6.328758	20%	50%	131.7      4.51%	-0.135626&lt;br /&gt;
SS = 1000	7.843786         1%     95%     128.0860   0.29%        -0.017268&lt;br /&gt;
SS = 10000	7.985498         0%     99%     125.8253   1.26%        -0.000047&lt;br /&gt;
SS = 100000	7.998297         0%     75%     127.5775   0.71%         0.000327&lt;br /&gt;
SS = 1000000	7.999876         0%  99.99%     127.5198   0.19%        -0.000567&lt;br /&gt;
&amp;lt;/pre&amp;gt;&lt;br /&gt;
*The randomness starts to not vary as much starting from 10000, so SS I choose will be 100000&lt;br /&gt;
&lt;br /&gt;
===Results===&lt;br /&gt;
&lt;br /&gt;
&amp;lt;pre&amp;gt;&lt;br /&gt;
buzhash low		7.99829	75.00%	127.577	0.71%	 0.000327&lt;br /&gt;
buzhashn low		7.99823	50.00%	127.493	0.13%	-0.003092&lt;br /&gt;
hash_CRC low		5.59830	0.01%	81.7834	24.53%	 0.028545&lt;br /&gt;
base256 low		0.00000	0.01%	97.000	27.32%	undefined&lt;br /&gt;
Java_Integer low	4.82824	0.01%	43.8834	27.32%	-0.092002&lt;br /&gt;
Java_Object low		2.00000	0.01%	77.000	27.32%	-0.521556&lt;br /&gt;
Java_String low		7.99958	99.99%	127.438	0.22%	-0.000646&lt;br /&gt;
rand low		7.95308	0.01%	111.441	11.17%	-0.051837&lt;br /&gt;
high rand low		7.99820	50.00%	127.402	0.59%	-0.001222&lt;br /&gt;
&lt;br /&gt;
buzhash high		7.99823	2.50%	127.374	0.77%	-0.000076&lt;br /&gt;
buzhashn high		7.82387	50.00%	127.493	0.13%	-0.003092&lt;br /&gt;
hash_CRC high		7.84045	0.01%	122.862	1.98%	 0.018518&lt;br /&gt;
base256 high		4.02297	0.01%	107.853	27.32%	 0.034082&lt;br /&gt;
Java_Integer high	4.82824	0.01%	43.8834	27.32%	-0.092002&lt;br /&gt;
Java_Object high	5.70432	0.01%	89.7964	21.50%	-0.148185&lt;br /&gt;
Java_String high	7.94554	0.01%	126.139	0.27%	 0.021181&lt;br /&gt;
rand high		7.95315	0.01%	111.468	11.13%	-0.048905&lt;br /&gt;
high rand high		7.99807	50.00%	127.405	0.07%	-0.002226&lt;br /&gt;
&amp;lt;/pre&amp;gt;&lt;br /&gt;
&lt;br /&gt;
===Conclusion===&lt;br /&gt;
*It was rather difficult putting up the results in a table, took a long time fiddling through each output.&lt;br /&gt;
*Just upon looking at the result of high entropy and low entropy, not a whole lot difference to the randomness of placement, pretty much the same, so it doesn&amp;#039;t really matter if the collection of items has a high entropy or not.&lt;br /&gt;
*Its very hard to determine a ranking system between each hash function, however it can be clearly shown that buzhash, buzhashn and high random all generate a good randomness in their tables.&lt;br /&gt;
*Random does not fall into the above category even though it&amp;#039;s Entropy is very close to 8 is due to it&amp;#039;s Monte Carlo score, having a high percentage of error.&lt;br /&gt;
*Java_String too, did not make it in the above category, due to the low Chi Square mark, even though the overall mark was good.&lt;br /&gt;
*base256 is probably the worst out of all, having really low randomness mark in all areas.&lt;br /&gt;
&lt;br /&gt;
==Task 2==&lt;br /&gt;
&amp;#039;&amp;#039;&amp;#039;10/100:&amp;#039;&amp;#039;&amp;#039;&lt;br /&gt;
&amp;lt;pre&amp;gt;&lt;br /&gt;
Buzhash low 10/100: llps = 2, expecting 1.39006&lt;br /&gt;
Hash CRC low 10/100: llps = 1, expecting 1.39006&lt;br /&gt;
Base256 low 10/100: llps = 10, expecting 1.39006&lt;br /&gt;
Java Object low 10/100: llps = 10, expecting 1.39006&lt;br /&gt;
Java String low 10/100: llps = 1, expecting 1.39006&lt;br /&gt;
&lt;br /&gt;
Buzhash high 10/100: llps = 2, expecting 1.39006&lt;br /&gt;
Hash CRC high CRC 10/100: llps = 1, expecting 1.39006&lt;br /&gt;
Base256 high 10/100: llps = 2, expecting 1.39006&lt;br /&gt;
Java Object high 10/100: llps = 1, expecting 1.39006&lt;br /&gt;
Java String high 10/100: llps = 1, expecting 1.39006&lt;br /&gt;
&lt;br /&gt;
Buzhashn 10/100: llps = 1, expecting 1.39006&lt;br /&gt;
Java Integer 10/100: llps = 1, expecting 1.39006&lt;br /&gt;
&amp;lt;/pre&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;#039;&amp;#039;&amp;#039;100/100:&amp;#039;&amp;#039;&amp;#039;&lt;br /&gt;
&amp;lt;pre&amp;gt;&lt;br /&gt;
Buzhash low 100/100: llps = 3, expecting 4.22683&lt;br /&gt;
Hash CRC low 100/100: llps = 6, expecting 4.22683&lt;br /&gt;
Base256 low 100/100: llps = 100, expecting 4.22683&lt;br /&gt;
Java Object low 100/100: llps = 100, expecting 4.22683&lt;br /&gt;
Java String low 100/100: llps = 3, expecting 4.22683&lt;br /&gt;
&lt;br /&gt;
Buzhash high 100/100: llps = 3, expecting 4.22683&lt;br /&gt;
Hash CRC high CRC 100/100: llps = 4, expecting 4.22683&lt;br /&gt;
Base256 high 100/100: llps = 4, expecting 4.22683&lt;br /&gt;
Java Object high 100/100: llps = 5, expecting 4.22683&lt;br /&gt;
Java String high 100/100: llps = 3, expecting 4.22683&lt;br /&gt;
&lt;br /&gt;
Buzhashn 100/100: llps = 4, expecting 4.22683&lt;br /&gt;
Java Integer 100/100: llps = 1, expecting 4.22683&lt;br /&gt;
&amp;lt;/pre&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;#039;&amp;#039;&amp;#039;1000/100:&amp;#039;&amp;#039;&amp;#039;&lt;br /&gt;
&amp;lt;pre&amp;gt;&lt;br /&gt;
Buzhash low 1000/100: llps = 22, expecting 18.7606&lt;br /&gt;
Hash CRC low 1000/100: llps = 43, expecting 18.7606&lt;br /&gt;
Base256 low 1000/100: llps = 1000, expecting 18.7606&lt;br /&gt;
Java Object low 1000/100: llps = 1000, expecting 18.7606&lt;br /&gt;
Java String low 1000/100: llps = 15, expecting 18.7606&lt;br /&gt;
&lt;br /&gt;
Buzhash high 1000/100: llps = 22, expecting 18.7606&lt;br /&gt;
Hash CRC high CRC 1000/100: llps = 25, expecting 18.7606&lt;br /&gt;
Base256 high 1000/100: llps = 103, expecting 18.7606&lt;br /&gt;
Java Object high 1000/100: llps = 47, expecting 18.7606&lt;br /&gt;
Java String high 1000/100: llps = 19, expecting 18.7606&lt;br /&gt;
&lt;br /&gt;
Buzhashn 1000/100: llps = 16, expecting 18.7606&lt;br /&gt;
Java Integer 1000/100: llps = 10, expecting 18.7606&lt;br /&gt;
&amp;lt;/pre&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&amp;#039;&amp;#039;&amp;#039;10000/100:&amp;#039;&amp;#039;&amp;#039;&lt;br /&gt;
&amp;lt;pre&amp;gt;&lt;br /&gt;
Buzhash low 10000/100: llps = 125, expecting 125.959&lt;br /&gt;
Hash CRC low 10000/100: llps = 409, expecting 125.959&lt;br /&gt;
Base256 low 10000/100: llps = 10000, expecting 125.959&lt;br /&gt;
Java Object low 10000/100: llps = 10000, expecting 125.959&lt;br /&gt;
Java String low 10000/100: llps = 110, expecting 125.959&lt;br /&gt;
&lt;br /&gt;
Buzhash high 10000/100: llps = 127, expecting 125.959&lt;br /&gt;
Hash CRC high CRC 10000/100: llps = 146, expecting 125.959&lt;br /&gt;
Base256 high 10000/100: llps = 671, expecting 125.959&lt;br /&gt;
Java Object high 10000/100: llps = 425, expecting 125.959&lt;br /&gt;
Java String high 10000/100: llps = 123, expecting 125.959&lt;br /&gt;
&lt;br /&gt;
Buzhashn 10000/100: llps = 128, expecting 125.959&lt;br /&gt;
Java Integer 10000/100: llps = 100, expecting 125.959&lt;br /&gt;
&amp;lt;/pre&amp;gt;&lt;br /&gt;
&lt;br /&gt;
*Java_Object, Base256, Hash CRC performed poorly.&lt;br /&gt;
*Buzhash and Buzhashn stays with the expected values.&lt;/div&gt;</summary>
		<author><name>Mark</name></author>
	</entry>
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