Searching
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The document discusses searching algorithms, focusing on sequential and binary search methods. Sequential search examines elements one by one and has a time complexity of O(n), while binary search is more efficient, with a time complexity of O(log n), as it divides the array into halves. Examples of both algorithms and their respective program logic are provided.
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![SEQUENTIAL SEARCH pROGRAmSEQUENTIAL SEARCH pROGRAm
LOGICLOGIC
01/31/18 BY MS. SHAISTA QADIR 7
PROGRAM LOGIC:
public int seqsearch(int [ ]arr, int x)
{
for(int i=0; i< arr.length; i++)
if(arr [ i ] == x)
return i;
return -1;
}
Time Complexity of Sequential search algorithm is: O(n)3.](https://image.slidesharecdn.com/lecture6-180131100803/85/Searching-7-320.jpg)
![BINARY SEARCH pROGRAmBINARY SEARCH pROGRAm
lOGIClOGIC
01/31/18 BY MS. SHAISTA QADIR 12
PROGRAM LOGIC:
public static int binarysearch(int[ ] a, int x) {
int lo = 0; int hi = a.length;
while (lo < hi) {
int i = (lo + hi) / 2;
if (a[i] == x)
return i;
else if (a[i] < x)
lo = i+1;
else hi = I; }
return -1; }
Time Complexity of binary search algorithm is: O(logn)](https://image.slidesharecdn.com/lecture6-180131100803/85/Searching-12-320.jpg)
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Intelligence shows Russia is on a cyber rampage, leveraging FSB, SVR, and GRU resources to professionally target Ukraines critical infrastructures, military, and international diplomacy support efforts.
The number of total incidents against Ukraine, originating from Russia, has steadily increased from 1350 in 2021 to 4315 in 2024, but the number of actual critical incidents has been managed down from a high of 1048 in 2022 to a mere 59 in 2024showcasing how the rapid detection and response to cyberattacks has been impacted by Ukraines improved cyber resilience.
Even against a much larger adversary, Ukraine is showcasing outstanding cybersecurity, enabled by strong strategies and sound tactics. There are lessons to learn for any enterprise that could potentially be targeted by aggressive nation states.
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Utilities and water companies play a key role in the creation of clean drinking water. The creation and maintenance of clean drinking water is becoming a critical problem due to pollution and pressure on the environment. A lot of data is necessary to create clean drinking water. For fieldworkers, two types of data are key: Asset data in an asset management system (EAM for example) and Geographic data in a GIS (ArcGIS Utility Network ). Keeping this type of data up to date and in sync is a challenge for many organizations, leading to duplicating data and creating a bulk of extra attributes and data to keep everything in sync. Using FME, it is possible to synchronize Enterprise Asset Management (EAM) data with the ArcGIS Utility Network in real time. Changes (creation, modification, deletion) in ArcGIS Pro are relayed to EAM via FME, and vice versa. This ensures continuous synchronization of both systems without daily bulk updates, minimizes risks, and seamlessly integrates with ArcGIS Utility Network services. This presentation focuses on the use of FME at a Dutch water company, to create a sync between the asset management and GIS.The Future of Technology: 2025-2125 by Saikat Basu.pdf
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- 1. Chapter 6Chapter 6 searChingsearChing 01/31/18 BY MS. SHAISTA QADIR 1 PRESENTED BY Shaista Qadir Lecturer king khalid university
- 2. COntentsCOntents searChing seQUentiaL searCh exampLe aLgOrithm prOgram LOgiC BinarY searCh exampLe aLgOrithm prOgram LOgiC 01/31/18 BY MS. SHAISTA QADIR 2
- 3. searChingsearChing 01/31/18 BY MS. SHAISTA QADIR 3 Computer systems are often used to store large amounts of data. Sometimes data must be retrieved from storage based on a searching criteria. Efficient storage of data to facilitate fast searching.
- 4. seQUentiaL searChseQUentiaL searCh 01/31/18 BY MS. SHAISTA QADIR 4 The sequential search (also called the Linear Search) is the simplest search algorithm. It is also the least efficient. It simply examines each element sequentially, starting with the first element, until it finds the key element or it reaches the end of the array. Application: To search a person in the train
- 5. SEQUENTIAL SEARCH ExAmpLESEQUENTIAL SEARCH ExAmpLE 01/31/18 BY MS. SHAISTA QADIR 5 Example: Consider an array with the following numbers:
- 6. SEQUENTIAL SEARCHSEQUENTIAL SEARCH ALGORITHmALGORITHm 01/31/18 BY MS. SHAISTA QADIR 6 ALGORITHM: (Postcondition: either the index i is returned where si = x, or 1 is returned.) 1. Repeat steps 23, for i = 0 to n 1. 2. If si = x, return i . 3. Return 1.
- 7. SEQUENTIAL SEARCH pROGRAmSEQUENTIAL SEARCH pROGRAm LOGICLOGIC 01/31/18 BY MS. SHAISTA QADIR 7 PROGRAM LOGIC: public int seqsearch(int [ ]arr, int x) { for(int i=0; i< arr.length; i++) if(arr [ i ] == x) return i; return -1; } Time Complexity of Sequential search algorithm is: O(n)3.
- 8. BINARY SEARCHBINARY SEARCH 01/31/18 BY MS. SHAISTA QADIR 8 The binary search is the standard algorithm for searching through a sorted sequence. It is much more efficient than the sequential search. It repeatedly divides the sequence in two, each time restricting the search to the half that would contain the element Application: Binary search is used to search a word in a dictionary.
- 9. BINARY SEARCH ExAmplEBINARY SEARCH ExAmplE 01/31/18 BY MS. SHAISTA QADIR 9 Example: Condition : The array must be sorted. Consider an array with the following numbers: Divide-and-Conquer Strategy Search for the number 16. Calculate: mid=(First + last)/2
- 10. BINARY SEARCH ExAmplEBINARY SEARCH ExAmplE 01/31/18 BY MS. SHAISTA QADIR 10 Example: Condition : The array must be sorted. Return the position of 16 which is 3
- 11. BINARY SEARCH AlGORITHmBINARY SEARCH AlGORITHm 01/31/18 BY MS. SHAISTA QADIR 11 ALGORITHM: (Precondition:1. s={s0, s1, . . ., sn1} is a sorted sequence of n values of the same type as x.either the index i is returned where si = x, or 1 is returned.) 1. Let ss be a subsequence of the sequence s, initially set equal to s. 2. If the subsequence ss is empty, return 1. 3. Let si be the middle element of ss. 4. If si = x, return its index i . 5. If si < x, repeat steps 26on the subsequence that lies above si. 6. Repeat st
- 12. BINARY SEARCH pROGRAmBINARY SEARCH pROGRAm lOGIClOGIC 01/31/18 BY MS. SHAISTA QADIR 12 PROGRAM LOGIC: public static int binarysearch(int[ ] a, int x) { int lo = 0; int hi = a.length; while (lo < hi) { int i = (lo + hi) / 2; if (a[i] == x) return i; else if (a[i] < x) lo = i+1; else hi = I; } return -1; } Time Complexity of binary search algorithm is: O(logn)
- 13. 01/31/18 BY MS. SHAISTA QADIR 13 THANK YOUTHANK YOU