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A. V. GERBESSIOTIS
CS610-101
Fall 2019 Aug 20, 2019
PrP: Programming Project
Page 1 Handout
(c) Copyright A. Gerbessiotis. All rights reserved.
Posting this document on the Web, other than its original location at NJIT, is strictly prohibited unless there
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1 Programming Project (PrP) Logistics
Warning: Besides the algorithmic-related programming, for some or all of the options you need to provide
command-line processing or file-based input/output. If you are not familiar with those topics and
requirements we urge you to become so as soon as possible. Thus start familiarizing with them early in the
semester. The more you procrastinate the more problems you will potentially face when you integrate these
components with the algorithmic-related material.
STEP-1. Read carefully Handout 2 and follow all the requirements specified there; moreover, observe
naming conventions, comments and testing as specified in sections 2-4 of Handout 2.
STEP-2. When the archive per Handout 2 guidelines is ready, upload it to moodle and do not forget to press
the submit button; the submission timestamp depends on this (submission button).
BEFORE NOON-time of Wed 4 December, 2019
If you want to get 0 pts ignore Handout 2.
You may do one or two options (or none at all). You may utilize the same language or not. We provide
descriptions that are to the extent possible language independent: thus a reference in Java is a pointer
in C or C++ for example.
OPTION 1 (Hash Table related). Do the programming related to the building of a Hash Table that can
maintain arbitrarily long strings in C, C++, or Java; it is similar to that used by Google around 1997-1998.
OPTION 2. Do the programming part related to Kleinberg’s HITS, and Google’s PageRank algorithms in
Java, C, or C++.
Either implementation should be optimized enough for a test execution to take no more than few seconds,
maximum 15 seconds forgivingly. (We are a bit more explicit about this in the 8th line or so of OPTION 1.)
A. V. GERBESSIOTIS
CS610-101
Fall 2019 Aug 20, 2019
PrP: Programming Project
Page 2 Handout
2 OPTION 1: Hashing ( 134 points)
We are asking you to implement a Lexicon structure realized by Google in 1997-1998 to store words (aka
arbitrarily long strings of characters) in main memory. Lexicon L uses a Hash Table T structure along with
an Array A of NULL separated strings . In our case words are going to be English character words only
(upper-case or lower case). Table T will be organized as a hash-table using collision-resolution by openaddressing
as specified in class. You are going to use quadratic probing for h(k,i) and keep the choice of
the quadratic function simple: i2
so that h(k,i) = (h0(k) +i2) mod m. The keys that you will hash are going
to be English words. Thus function h
0
(k) is also going to be kept simple: the sum of the ASCII/Unicode
values of the characters mod m, where m is the slot-size of the hash table. Thus ’alex’ (the string is between
the quotation marks) is mapped to 97+108+101+120 mod m whatever m is. In the example below, for
m = 11, h(alex,0) = 8. Table T however won’t store key values k in it. This is because the keys are strings
of arbitrary length. Instead, T will store pointers/references in the form of an index to another array A. The
second table, array A will be a character array and will store the words maintained in T separated by NUL
values \0. This is not 2 characters a backslash followed by a zero. It is 1B (ASCII), 2B (UNICODE) whose
all bits are set to 0, the NUL value. If you don’t know what B is, it is a byte; never use b for a bit, write
instead bit or bits i.e. read Handout 3.
An insertion operation affects T and A. A word w is hashed, an available slot in T is computed and
let that slot be t. In T[t] we store an index to table A. This index is the first location that stores the first
character of w. The ending location is the \0 following w in A. New words that do not exist (never inserted,
or inserted but subsequently deleted) are appended in A. Thus originally you need to be wise enough in
choosing the appropriate size of A. If at some point you run-out of space, you need to increase the size of
A accordingly, even if T remains the same. Doubling it, is an option. Likewise the size of T might also
have to be increased. This causes more problems that you also need to attend to. A deletion will modify T
as needed but will not erase w from A. Let it be there. So A might get dirty (i.e. it contains garbage) after
several deletions. If several operations later you end up inserting w after deleting it previously, you do it the
insertion way and you reinsert w, even if a dirty copy of it might still be around. You DO NOT DO a linear
search to find out if it exists arleady in A; it is inefficient. There is not much to say for a search.
You need to support few more operations: Print , Create, Empty/Full/Batch with the last of those
checking for an empty or full table/array and a mechanism to perform multiple operations in batch form.
Print prints nicely T and its contents i.e. index values to A. In addition it prints nicely (linear-wise in one
line) the contents of A. (For a \0 you will do the SEMI obvious: print a backslash but not its zero). The
intent of Print is to assist the grader. Print however does not print the words of A for deleted words. It
prints stars for every character of a deleted word instead. (An alternative is that during deletion each such
character has already been turned into a star.) Function Create creates T with m slots, and A with 15m chars
and initializes A to spaces. The following is a suggested minimal interface (we try to be language agnostic).
We call the class that supports and realizes A and T a lexicon: L is one instance of a lexicon.
HashCreate (lexicon L, int m); // Create T, A. T will have m slots; A should be 15m
HashEmpty (lexicon L); // Check if L is empty
HashFull (lexicon L); // Check if L can maintain more words
HashPrint (lexicon L); // Print of L
HashInsert (lexicon L, word w); //Insert w into L (and T and A)
HashDelete (lexicon L, word w); //Delete w from L (but not necessarily from A)
HashSearch (lexicon L, word w); //Search for string in L (and this means T)
HashBatch (lexicon L, file filename)
The list of functions above is a suggestion of what needs to be implemented: it is too generic and general
to be programming language agnostic.
A. V. GERBESSIOTIS
CS610-101
Fall 2019 Aug 20, 2019
PrP: Programming Project
Page 3 Handout
Testing utilizes HashBatch. Its argument filename, an arbitrary filename contains several operations
that are executed in batch mode. Operation 10 is Insert, Operation 11 is Deletion, and Operation 12 is
Search. Operation 13 is Print, Operation 14 is Create. Operation 15 is Comment; the rest of the line is
ignored. (Create accepts as its second parameter and that of HashCreate, an integer value next to its code 14;
this becomes m.) The HashBatch accepts an arbitrary filename such as command.txt or file.txt that contains
a sequence of operations.
% java mplexicon filearbitrary.txt
% ./mplexicon file.txt
15 ready-to-print CAUTION: 15 is a comment string (chars,numbers,-)
13 operation 15 is skipped/ignored
The six-line batch file above will print the following. The T entries for 0, 5, 9 are the indexes (first position)
for alex, tom, jerry respectively. Note that the ASCII values for ’alex’ mod 11 give an 8, but for ’tom’
and ’jerry’ give 6, i.e. a collision occurs. A minimal output for Print is available below.
T A: alex\tom\jerry\
0: CAUTION: \ means \0
1: \t is not a tab character !!!
If the following lines were added to the file
they will generate in addition on screen
alex found at slot 8
tom found at slot 6
jerry found at slot 7
mary not found
tom deleted from slot 6
T A: alex\***\jerry\
Deliverables. An archive per Handout 2 guidelines.
A. V. GERBESSIOTIS
CS610-101
Fall 2019 Aug 20, 2019
PrP: Programming Project
Page 4 Handout
3 OPTION 2: HITS and PageRank implementations ( 134 points)
Implement Kleinberg’s HITS Algorithm, and Google’s PageRank algorithm in Java, C, or C++ as explained.
(A) Implement the HITS algorithm as explained in class/Subject notes adhering to the guidelines of
Handout 2. Pay attention to the sequence of update operations and the scaling. For an example of the
Subject notes, you have output for various initialization vectors. You need to implement class or function
hits (e.g. hitsWXYZ. For an explanation of the arguments see the discussion on PageRank to follow.
% java hits iterations initialvalue filename
% ./hits iterations initialvalue filename
(B) Implement Google’s PageRank algorithm as explained in class/Subject notes adhering also to the
guidelines of Handout 2 and this description. The input for this (and the previous) problem would be a file
containing a graph represented through an adjacency list representation. The command-line interface is as
follows. First we have the class/binary file (eg pgrk). Next we have an argument that denotes the number
of iterations if it is a positive integer or an errorrate for a negative or zero integer value. The next
argument initialvalue indicates the common initial values of the vector(s) used. The final argument is a
string indicating the filename that stores the input graph.
% ./pgrk iterations initialvalue filename // in fact pgrkWXYZ
% java pgrk iterations initialvalue filename // in fact pgrkWXYZ
The two algorithms are iterative. In particular, at iteration t all pagerank values are computed using results
from iteration t − 1. The initialvalue helps us to set-up the initial values of iteration 0 as needed.
Moreover, in PageRank, parameter d would be set to 0.85. The PageRank PR(A) of vertex A depends on
the PageRanks of vertices T1,...,Tm incident to A, i.e. pointing to A; check Subject 7 section 3.6 for more
details. The pageranks at iteration t use the pageranks of iteration t −1 (synchronous update). Thus PR(A)
on the left in the PageRank equation is for iteration t, but all PR (Ti) values are from the previous iteration
t − 1. Be careful and synchronize! In order to run the ’algorithm’ we either run it for a fixed number
of iterations and iterations determines that, or for a fixed errorrate (an alias for iterations); an
iterations equal to 0 corresponds to a default errorrate of 10−5
. A -1, -2, etc , -6 for iterations
becomes an errorrate of 10−1
,10−2
,...,10−6
respectively. At iteration t when all authority/hub/PageRank
values have been computed (and auth/hub values scaled) we compare for every vertex the current and the
previous iteration values. If the difference is less than errorrate for EVERY VERTEX, then and only then
can we stop at iteration t.
Argument initialvalue sets the initial vector values. If it is 0 they are initialized to 0, if it is 1 they
are initialized to 1. If it is -1 they are initialized to 1/N, where N is the number of web-pages (vertices of
the graph). If it is -2 they are initialized to 1/

N. filename first.)
Argument filename describes the input (directed) graph and it has the following form. The first
line contains two numbers: the number of vertices followed by the number of edges which is also the
number of remaining lines. PAY ATTENTION THAT NUMBER of VERTICES comes first. The sample
graph is treacherous: n and m are the same! All vertices are labeled 0,...,N − 1. Expect N to be less
than 1,000,000. In each line an edge (i, j) is represented by i j. Thus our graph has (directed) edges
(0,2),(0,3),(1,0),(2,1). Vector values are printed to 7 decimal digits. If the graph has N GREATER than
10, then the values for iterations, initialvalue are automatically set to 0 and -1 respectively. In
such a case the hub/authority/pageranks at the stopping iteration (i.e t) are ONLY shown, one per line. The
graph below will be referred to as samplegraph.txt
A. V. GERBESSIOTIS
CS610-101
Fall 2019 Aug 20, 2019
PrP: Programming Project
Page 5 Handout
The following invocations relate to samplegraph.txt, with a fixed number of iterations and the fixed
error rate that determines how many iterations will run. Your code should compute for this graph the same
rank values (intermediate and final). A sample of the output for the case of N > 10 is shown (output truncated
to first 4 lines of it).
% ./pgrk 15 -1 samplegraph.txt
Base : 0 :P[ 0]=0.2500000 P[ 1]=0.2500000 P[ 2]=0.2500000 P[ 3]=0.2500000
Iter : 1 :P[ 0]=0.2500000 P[ 1]=0.2500000 P[ 2]=0.1437500 P[ 3]=0.1437500
Iter : 2 :P[ 0]=0.2500000 P[ 1]=0.1596875 P[ 2]=0.1437500 P[ 3]=0.1437500
Iter : 3 :P[ 0]=0.1732344 P[ 1]=0.1596875 P[ 2]=0.1437500 P[ 3]=0.1437500
Iter : 4 :P[ 0]=0.1732344 P[ 1]=0.1596875 P[ 2]=0.1111246 P[ 3]=0.1111246
Iter : 5 :P[ 0]=0.1732344 P[ 1]=0.1319559 P[ 2]=0.1111246 P[ 3]=0.1111246
Iter : 6 :P[ 0]=0.1496625 P[ 1]=0.1319559 P[ 2]=0.1111246 P[ 3]=0.1111246
Iter : 7 :P[ 0]=0.1496625 P[ 1]=0.1319559 P[ 2]=0.1011066 P[ 3]=0.1011066
Iter : 8 :P[ 0]=0.1496625 P[ 1]=0.1234406 P[ 2]=0.1011066 P[ 3]=0.1011066
Iter : 9 :P[ 0]=0.1424245 P[ 1]=0.1234406 P[ 2]=0.1011066 P[ 3]=0.1011066
Iter : 10 :P[ 0]=0.1424245 P[ 1]=0.1234406 P[ 2]=0.0980304 P[ 3]=0.0980304
Iter : 11 :P[ 0]=0.1424245 P[ 1]=0.1208259 P[ 2]=0.0980304 P[ 3]=0.0980304
Iter : 12 :P[ 0]=0.1402020 P[ 1]=0.1208259 P[ 2]=0.0980304 P[ 3]=0.0980304
Iter : 13 :P[ 0]=0.1402020 P[ 1]=0.1208259 P[ 2]=0.0970858 P[ 3]=0.0970858
Iter : 14 :P[ 0]=0.1402020 P[ 1]=0.1200230 P[ 2]=0.0970858 P[ 3]=0.0970858
Iter : 15 :P[ 0]=0.1395195 P[ 1]=0.1200230 P[ 2]=0.0970858 P[ 3]=0.0970858
% ./pgrk -3 -1 samplegraph.txt
Base : 0 :P[ 0]=0.2500000 P[ 1]=0.2500000 P[ 2]=0.2500000 P[ 3]=0.2500000
Iter : 1 :P[ 0]=0.2500000 P[ 1]=0.2500000 P[ 2]=0.1437500 P[ 3]=0.1437500
Iter : 2 :P[ 0]=0.2500000 P[ 1]=0.1596875 P[ 2]=0.1437500 P[ 3]=0.1437500
Iter : 3 :P[ 0]=0.1732344 P[ 1]=0.1596875 P[ 2]=0.1437500 P[ 3]=0.1437500
Iter : 4 :P[ 0]=0.1732344 P[ 1]=0.1596875 P[ 2]=0.1111246 P[ 3]=0.1111246
Iter : 5 :P[ 0]=0.1732344 P[ 1]=0.1319559 P[ 2]=0.1111246 P[ 3]=0.1111246
Iter : 6 :P[ 0]=0.1496625 P[ 1]=0.1319559 P[ 2]=0.1111246 P[ 3]=0.1111246
Iter : 7 :P[ 0]=0.1496625 P[ 1]=0.1319559 P[ 2]=0.1011066 P[ 3]=0.1011066
Iter : 8 :P[ 0]=0.1496625 P[ 1]=0.1234406 P[ 2]=0.1011066 P[ 3]=0.1011066
Iter : 9 :P[ 0]=0.1424245 P[ 1]=0.1234406 P[ 2]=0.1011066 P[ 3]=0.1011066
Iter : 10 :P[ 0]=0.1424245 P[ 1]=0.1234406 P[ 2]=0.0980304 P[ 3]=0.0980304
Iter : 11 :P[ 0]=0.1424245 P[ 1]=0.1208259 P[ 2]=0.0980304 P[ 3]=0.0980304
Iter : 12 :P[ 0]=0.1402020 P[ 1]=0.1208259 P[ 2]=0.0980304 P[ 3]=0.0980304
Iter : 13 :P[ 0]=0.1402020 P[ 1]=0.1208259 P[ 2]=0.0970858 P[ 3]=0.0970858
% ./pgrk 0 -1 verylargegraph.txt
Iter : 4
P[ 0]=0.0136364
P[ 1]=0.0194318
P[ 2]=0.0310227
... other vertices omitted
For the HITS algorithm, you need to print two values not one. Follow the convention of the Subject notes
Base : 0 :A/H[ 0]=0.3333333/0.3333333 A/H[ 1]=0.3333333/0.3333333 A/H[ 2]=0.3333333/0.3333333
Iter : 1 :A/H[ 0]=0.0000000/0.8320503 A/H[ 1]=0.4472136/0.5547002 A/H[ 2]=0.8944272/0.0000000
or for large graphs
Iter : 37
A/H[ 0]=0.0000000/0.0000002
A/H[ 1]=0.0000001/0.0000238
A/H[ 2]=0.0000002/1.0000000
A/H[ 3]=0.0000159/0.0000000
...
Deliverables. Include source code of all implemented functions or classes in an archive per Handout 2
guidelines. Document bugs; no bug report no partial points.

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