Multiple Values Bidirectional Square Root Search

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```					                                                        (IJCSIS) International Journal of Computer Science and Information Security,
Vol. 8, No. 4, July 2010

Multiple Values Bidirectional Square Root Search

Syed Zaki Hassan Kazmi                                                      Syeda Shehla Kazmi
Department of Computer Science                                     Department of Computing & Mathematics
IQRA University Islamabad Campus,                                Manchester Metropolitan University, United Kingdom
Pakistan                                                       shehla_kazmi@hotmail.com
zaki.mzd@gmail.com
Syeda Sobia Hassan Kazmi
Jamil Ahmad                                                   Department of Computer Science
Department of Computer Science                                       University Of Azad Jammu And Kashmir
Pakistan                                                          fajar_zara@hotmail.com
jamil@iqraisb.edu.pk

Abstract—The research in hand is an effort to introduce a new             its efficiency. Searching is of considerable importance as the
efficient searching technique known as Multiple Values                    human        is      possessed       in     searching      the
Bidirectional Square Root Search. In this technique, a sorted             information/knowledge. To search the information
list of values can be searched from another sorted list very              efficiently the efficient searching technique is very
efficiently. The overall time for sorting the values to be
searched and searching is less than the time taken by the
important. To facilitate the human, computers consume a
Linear Search and Binary Search. In this technique, the size of           substantial time in searching the data.
targeting list is reduced for every next value to be searched. As              This paper is organized as follows; Section II presents a
a result the searching time of remaining values to be searched            brief review of existing searching algorithms. Section III
is reduced, while in linear search and binary search the size of          presents the description of proposed solution. Section IV
target list remains same for every value to be searched. In               presents the proposed algorithm. Section V presents
other words, we can say that the targeting list is traversed              Running Cost Analysis. Section VI present comparison
completely each time for every value to be searched from                  between multiple values bidirectional square root search
beginning to end. Running Cost analysis and the result                    with linear search and binary search. Section VII ends with
obtained after implementation are provided in the graphical
form with an objective to compare the efficiency of the
concluding remarks.
technique with linear search as well as binary search, as binary                 II.   A BRIEF REVIEW OF EXISTING SEARCHING
search is consider as an efficient and fast one.
ALGORITHMS
Keywords-Searching; Linear Search; Binary Search.                          A number of searching techniques are currently used in
the field of computer science. This section will briefly
I.    INTRODUCTION                                  discuss some of the trendy searching techniques among
them. These are following:
Algorithms have a vital and key role in solving the
computational problems, informally an algorithm is a well                 A. Linear Search
defined computational procedure that takes input and                          It is the simplest method to find the particular element in
produces output. Algorithm is a tool or a sequence of steps               the list. It checks all of the elements in the list and
to solve the computational problems [1].                                  particularly checks in sequence and one at a time to reach the
In computer science, a searching algorithm, broadly                   particular value. It is the special case of Brute Force Search.
speaking, is an algorithm that finds a particular data from a             Its worst case cost is proportional to the number of elements
data set. Searching takes a problem as input and returns a                in the list. It is O (n) [9].
solution to the problem, usually after evaluating a number of
B.   Binary Search
possible solutions. Efficient searching is important to
optimizing the use of other algorithms (such as sorting                       “In computer science, a binary search is an algorithm
algorithms) that require searching the location of new item               for locating the position of an element in a sorted list. It
in sorted list such as in insertion sort. There are a lot of              inspects the middle element of the sorted list: if equal to the
searching techniques, currently used in industry and                      sought value, then the position has been found; otherwise,
academia, to find the data of various forms and from                      the upper half or lower half is chosen for further searching
different areas.                                                          based on whether the sought value is greater than or less
The study in hand proposes a new searching technique                  than the middle element. The method reduces the number of
that is tested and analyzed against binary search to provide              elements needed to be checked by a factor of two each time,

ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 8, No. 4, July 2010

and finds the sought value if it exists in the list or if not                         IV.    ALGORITHM : PSEUDO CODE
determines "not present", in logarithmic time. A binary                      "arr" list of data element and "Data" is the list of value
search is a dichotomic divide and conquer search algorithm.              to be search.
Its running time complexity is O(logn)”[5].
III.   MULTIPLE VALUES BIDIRECTIONAL SQUARE ROOT                          Multi Values Bidirectional Square Root Search
SEARCH                                                (arr,Data)
Sqr:=square root of "len"
In this technique, a sorted list of values can be searched                      Len:=length[arr]-1
from another sorted list very efficiently. The overall time for                   i:=0
sorting the values to be searched and searching is less than                      l:=len
the time taken by the Linear Search and Binary Search. In                         f:=0
this technique, the size of targeting list is reduced for every                   for f = 0; f <length[Data]; f++
next value to be searched. As a result the searching time of                      {
remaining values to be searched is reduced, while in linear                        item = data[f];
search and binary search the size of target list remains same                      j = len;
for every value to be searched. In other words, we can say                         temp = i;
that the targeting list is traversed completely each time for                      sqr = square root of "l"
every value to be searched from beginning to end. The steps                        while arr[i] != item && arr[j] != item && sqr != 1
of the proposed Multiple Values Bidirectional Square Root                           {
Search algorithm are as follows:                                                      if arr[i] < item && arr[j] > item
{
1.    Take 1st element from the item list and assign it to                              i = i + sqr
"item"                                                                            j = j - sqr
2. Assign 1st element of the Data list to left pointer and                           }
last element of the Data list to right pointer.                               else
3. Take square root of list length and assign to "sqr".                              {
4. If value on the left pointer is less then item                                      if arr[i]>item
,increment left pointer .The new location of left                                   {
pointer is getting by adding left pointer current                                     j=i-1
location with "sqr".                                                                  i = i - sqr + 1
5. If value on the left pointer is greater then item,                                      sqr = square root of "sqr"
change the location of right pointer by calculating                                 }
new location as subtracting 1 from current location of                            else
left pointer. Also change the location of left pointer                              {
by subtracting left pointer current location with "sqr"                               i=j+1
and increment by 1. The new value of "sqr" is                                         j = j + sqr - 1
calculated by taking square root of "sqr".                                            sqr = square root of "sqr"
6. Similarly If value on the right pointer is greater then                               }
item, decrement right pointer .the new location of
right pointer is getting by subtracting right pointer                           }
current location with "sqr".                                                }
7. If value on the right pointer is less then item, change                      if arr[i] == item
the location of left pointer by calculating new                              {
location as adding 1 with current location of right                            Found Item at "i"
pointer. Also change the location of right pointer by                          while arr[i] == item && i!=temp
adding right pointer current location with "sqr" and                             {
decrement by 1. The new value of "sqr" is calculated                               i=i-1
by taking square root of "sqr".                                                  }
8. Repeat step 3 to 6 until value of left pointer or right                          if i==temp
pointer match with item, or the value of "sqr" become                            {
1.                                                                                 i=i+1
If the value of right pointer match with the item then                               }
assign right pointer to left pointer. Assign data list length to                       else
right pointer and next element in item list to item, go to step                          i=i+2
3.Repeat this process till all the element in the item list will                     }
be processed.                                                                       else

ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 8, No. 4, July 2010

{                                                              Inner Loop Runs: n1/2 + n1/4+ n1/8………………+ n1/k
if arr[j] == item                                         Where n1/k ≥1
{                                                       Comparison Statements: c
Found Item at "j"                                     So the running time of Multiple Values bidirectional
while arr[j]==item                               square root search can be written as,
{                                               T (n) = r*(n1/2 (c+c+c)+ n1/4 (c+c+c) + n1/8(c+c+c)+ ……+
j=j-1                                         n1/k (c+c+c) )
}                                               T (n) = r*(n1/2 (3c)+ n1/4 (3c) + n1/8(3c)+ ………………+
i=j+2                                            n1/k (3c) )
Ignoring Constants and smaller values we can write it as
}                                                                             T (n) =O (r√n)
else
{                                       VI. COMPARISON OF MULTIPLE VALUES BIDIRECTIONAL
if arr[i+1] == item                             SQUARE ROOT SEARCH WITH LINEAR SEARCH AND BINARY
{                                                                    SEARCH
Found Item at "i+1"                                 Table 1 shows the comparison of the proposed
i=i+2                                algorithm (Multiple Values Bidirectional Square Root
}                                          Search) with the traditional searching algorithms on the
else                                  basis of no. of iterations. Graphical view of the same
}
}
l = len – i
}
V.    RUNNING COST ANALYSIS
A. Best Case:
The main structure of the algorithm depicts that there is
an outer main loop within which there lies another inner
loop , after number of inner while loop iterations, we will
Multiple Values Bidirectional Square Root Search Best
Case Occur when items are 1st or last element of the Data
List. Let T (n) be the running time of Multiple Values
Bidirectional Square Root Search on an input list of size n.
then running time of Multiple Values Bidirectional Square
Root Search Can be calculated as
Length of input array: n
Length of items array: r
Outer Loop runs: r
Inner Loop Runs: 1
so the running time of Multiple Values bidirectional square
root search can be written as,
T (n) = O (r * 1)
B. Average and Worst Case:
The main structure of the algorithm depicts that there is
an outer main loop within which there lies another inner
loop , after number of inner while loop iterations, we will
have found our item or concluded that it was not found. Let
T(n) be the running time of Multiple Values Bidirectional
Square Root Search on an input list of size n. then running
time of Multiple Values Bidirectional Square Root Search                 Table 1: Multiple Values Bidirectional Square Root Search Vs Binary
Can be calculated as                                                                        Search and Linear Search
Length of input array: n
Length of items array: r
Outer Loop runs: r

ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 8, No. 4, July 2010

36                                                                                          120000                                               Multiple Values
100000                                               Bidirectional
31                                                                                                                                               Square Root

No. of  Comparisons
80000                                               Search
26
Multiple Values Bidirectional                                   60000                                               Binary Search
No. of Iteration

21                           Square Root Search
40000
16                           Binary Search
20000
11                                                                                               0
Linear Search                                                                                                       Linear Search
6

12

0

88
1

00
56
1

8

00
10

50

89

10
1
Data Values
59      85         91
Data Values
FIGURE 2: MULTIPLE VALUES BIDIRECTIONAL SQUARE ROOT SEARCH V/S
BINARY SEARCH AND LINEAR SEARCH
Figure 1: Multiple Values Bidirectional Square Root Search v/s Binary
Search and Linear Search                                               It can be observed from the Table 2 and graph presented
in Figure 2 that performance of proposed algorithm
It can be observed from the Table 1 and graph                                       (Multiple Values Bidirectional Square Root Search) is far
presented in Figure 1 that performance of proposed                                        better than the linear search. Also it shows good result in
algorithm (Multiple Values Bidirectional Square Root                                      comparison with Binary Search and show good competition.
Search) is far better than the linear search. Also it shows
good result in comparison with Binary Search and show                                         Table 3 shows the comparison of the proposed algorithm
good competition.                                                                         (Multiple Values Bidirectional Square Root Search) with the
traditional searching algorithms on the basis of execution
Table 2 shows the comparison of the proposed                                        time (in ms). Graphical view of the same analysis is
algorithm (Multiple Values Bidirectional Square Root                                      presented in the Figure 3. Total values in data list =
Search) with the traditional searching algorithms on the                                  1000000(1…..1000000)
basis of No. of comparisons. Graphical view of the same
analysis is presented in the Figure 2. Total values in data list                             No. of                                 Execution Time(millisecond)
= 100000(1…..100000)                                                                        Elements                            Linear        Multiple       Binary
Values                    Comparisons                                                                                       Search         Values        Search
Linear        Multiple          Binary                                                                                      Bidirectional
Search         Values           Search                                                                                      Square Root
Bidirectional                                                                                                      Search
Square Root                                                                             50000        19578          15.6          15.6
Search                                                                              100000        40950          31.2          46.8
1           1              1               48                                                               200000       80979.6         62.4          93.6
948        948              9               40                                                               300000       122226            78          109.2
10112       10112            32               43                                                               500000       210678          109.2          187
30336       30336            67               38                                                               600000       350107           124           234
50560       50560            67               32                                                Table 3: Multiple Values Bidirectional Square Root Search Vs Binary
69032       69032            75               38                                                                   Search and Linear Search
89888       89888            33               37
97156       97156            10               41
100000 100000                 1               35
Table 2: Multiple Values Bidirectional Square Root Search Vs Binary
Search and Linear Search

ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 8, No. 4, July 2010

[4] Donald Knuth. The Art of ComputerProgramming, Volume 3: Sorting
and Searching, Third Edition. Addison-Wesley, 1997. ISBN 0-201-
400000                                                           89685-0. pp. 106–110 of section 5.2.2: Sorting by Exchanging.
Multiple Values          [5] Binary_search, (2010), Binary search,
350000                                                           http://en.wikipedia.org/wiki/Binary_search, Accessed January 01, 2010
Bidirectional
[6] Donald Knuth. The Art of Computer Programming, Volume 3: Sorting
300000                              Square Root                  and Searching, Third Edition. Addison-Wesley, 1997. ISBN 0-201-
Search                       89685-0., pp. 138–141, of Section 5.2.3: Sorting by Selection.
250000                              Binary Search            [7] Seymour Lipschutz. Theory and Problems of Data Structures,Schaum’s
Execution Time(ms)

Outline Series: International Edition, McGraw- Hill, 1986. ISBN 0-07-
200000                                                           099130-8., pp. 324–325, of Section 9.4: Selection Sort.
[8] Seymour Lipschutz. Theory and Problems of Data Structures,Schaum’s
150000                                                           Outline Series: International Edition, McGraw- Hill, 1986. ISBN 0-07-
Linear Search                099130-8., pp. 322–323, of Section 9.3: Insertion Sort.
100000                                                       [9] Linear_search, (2010), Linear search,
http://en.wikipedia.org/wiki/Linear_search,     Accessed      January
50000                                                           01,2010.

0
00

0

0
00

00
0
50

0

0
20

50

No. of Elements

Figure 3: Multiple Values Bidirectional Square Root Search v/s Binary
Search and Linear Search

It can be observed from the Table 3 and graph presented
in Figure 3 that performance of proposed algorithm
(Multiple Values Bidirectional Square Root Search) is far
better than the linear search. Also it shows good result in
comparison with Binary Search and show good competition.
VII. CONCLUSION
By analyzing the graphs above, it can be easily
examined that Multiple Values Bidirectional square root
search efficient then linear search and also give good
competition to binary search. The common thing between
Multiple Values Bidirectional Square Root Search and
Binary Search is that for both, the list of element should be
sorted. In future, we are foreseeing to come up with a new
searching technique, which hopefully will be more efficient.
ACKNOWLEDGMENT
We acknowledge the support and contribution from our
loving and caring families, teachers and friends in
continuing the education and research. With their moral and
financial support, we are in higher education, which
encourages us to write this research for the ease of human
kind. Thank you all.
REFERENCES
[1] Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and
Clifford Stein. Introduction to Algorithms, Second Edition. MIT Press
and McGraw-Hill, 2001. ISBN 0-262-03293-7. Section 1.1:
Algorithms, pp.5–6.
[2] D. A. Bailey, Java Structure:Data Structure in Java for Principled
Programmer, 2nd ed. McGraw-Hill, 2003.
Wesley, 1992.

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Description: The International Journal of Computer Science and Information Security is a monthly periodical on research articles in general computer science and information security which provides a distinctive technical perspective on novel technical research work, whether theoretical, applicable, or related to implementation. Target Audience: IT academics, university IT faculties; and business people concerned with computer science and security; industry IT departments; government departments; the financial industry; the mobile industry and the computing industry. Coverage includes: security infrastructures, network security: Internet security, content protection, cryptography, steganography and formal methods in information security; multimedia systems, software, information systems, intelligent systems, web services, data mining, wireless communication, networking and technologies, innovation technology and management. Thanks for your contributions in July 2010 issue and we are grateful to the reviewers for providing valuable comments. IJCSIS July 2010 Issue (Vol. 8, No. 4) has an acceptance rate of 36 %.