mansi.oops.docx mansi shukla with object and class.

"Oops" can mean a minor mistake, a soft apology, or a common exclamation of surprise. Alternatively, OOPS is an acronym for Object-Oriented Programming, a computer programming paradigm used to structure code

1. STRING ANALYZER TOOL
Object Oriented Programming through Java Project Report Submitted in Partial Fulfillment
of the Requirements for the Award of the Degree of
BACHELOR OF TECHNOLOGY
In
COMPUTER SCIENCE AND ENGINEERING-DATA SCIENCE
Submitted by
25RH5A6715 MANSI SHUKLA
Under the Guidance of
S.DURGA HIMA BINDU
Associate Professor
MALLA REDDY ENGINEERING COLLEGE FOR WOMEN
(Autonomous Institution-UGC, Govt. of India)
Accredited by NAAC with ‘A+’ Grade
National Ranking by NIRF Innovation – Rank band (151-300), MHRD, Govt. of India
Approved by AICTE, Affiliated to JNTUH, ISO 9001:2015 Certified Institution
Maisammaguda, Dhulapally, Secunderabad- 500100
2025

2. MALLA REDDY ENGINEERING COLLEGE FOR WOMEN
(Autonomous Institution-UGC, Govt. of India)
Accredited by NAAC with ‘A+’ Grade
National Ranking by NIRF Innovation – Rank band (151-300), MHRD, Govt. of India
Approved by AICTE, Affiliated to JNTUH, ISO 9001:2015 Certified Institution
Maisammaguda, Dhulapally, Secunderabad- 500100
DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING-DATA SCIENCE
CERTIFICATE
This is to certify that the project report entitled “string analyzer” is being submitted by the following
student: 25RH5A6715 –mansi shukla in partial fulfillment of the requirements for the award of the
Bachelor of Technology (B.Tech) Degree in Computer Science and Engineering – Data Science to
the Jawaharlal Nehru Technological University, Hyderabad. This is a bonafide Project record of
work carried out by the students under my guidance and supervision.
Project Guide Head of the Department
S.Durga Hema Bindu
Associate Professor
Dr. V. Pradeep
Associate Professor
HOD of CSE- Data Science

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4. INDEX
Contents Page No.
Abstract 01
Introduction 02
Concepts Used 03
Algorithm 05
Program Code (to be written neatly by hand)06
Sample Output (handwritten) 07
Results and Discussion 09
Conclusion 10
References 11

5. Abstract
The String Analyzer Tool is a software application designed to perform comprehensive analysis and
processing of textual data. It allows users to input strings and obtain detailed insights such as length, word and
character counts, frequency of specific characters or words, detection of palindromes, identification of
patterns, and validation of formats (e.g., email or numeric strings). The tool supports both simple and
advanced operations, including substring searches, case conversions, and regular expression matching. By
leveraging efficient algorithms, it provides quick and accurate results, making it valuable for developers,
linguists, and data analysts who work extensively with text data. Its user-friendly interface and modular design
enable easy integration into larger systems or educational use in programming and text-processing courses.
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6. Introduction
In the field of computer science, strings are one of the most fundamental data types used to represent
and manipulate textual information. The ability to analyze and process strings efficiently is essential for
various applications such as data validation, natural language processing, and software development. The
String Analyzer Tool is developed to simplify and automate the analysis of textual data by providing users
with detailed insights into the composition and characteristics of strings.
This tool enables users to perform a wide range of operations, including calculating string length, counting
words and characters, identifying vowels and consonants, detecting palindromes, analyzing frequency
distributions, and validating specific formats such as email addresses or numeric inputs. It can also perform
advanced functions such as pattern matching using regular expressions and substring searches.
The primary goal of the String Analyzer Tool is to assist users—whether students, developers, or researchers
—in understanding and manipulating text-based data more effectively. By providing a simple, interactive, and
efficient platform for string analysis, the tool enhances productivity and reduces manual effort in text
processing tasks. Its modular design and user-friendly interface make it adaptable for educational purposes as
well as integration into larger software systems.
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7. Concepts Used
The development of the String Analyzer Tool is based on several key programming and computational
concepts related to text processing, data structures, and algorithm design. These concepts ensure efficient
manipulation, analysis, and validation of string data. The major concepts used include:
1.String Manipulation
oFundamental operations such as concatenation, slicing, splitting, and joining are used to process
and analyze text.
oFunctions like finding substrings, replacing characters, and changing case
(uppercase/lowercase) help in transforming string data for analysis.
2.Character and Word Counting
oIterative loops and conditional statements are used to traverse strings and count specific
elements such as words, characters, vowels, consonants, digits, and special symbols.
oThis helps in determining the structural composition of the given text.
3.Control Structures
oConditional statements (if, else if, else) are used to make decisions based on specific string
conditions (e.g., checking for palindromes or special patterns).
oLooping structures (for, while) are used for repetitive operations like traversing each character
in a string.
4.Regular Expressions (Regex)
oRegular expressions are powerful tools used to search, match, and validate text patterns.
oThey are used in tasks such as email validation, numeric string checking, and pattern detection.
5.Data Structures
oArrays, lists, and dictionaries (or hash maps) are used to store and count frequency of characters
or words.
oThese structures make it easier to organize and analyze string data efficiently.
6.Functions and Modular Programming
oThe tool is designed using modular programming principles where each operation (e.g.,
counting words, checking palindrome) is implemented as a separate function or module.
oThis enhances reusability, maintainability, and readability of the code.
7.Algorithms and Logic Design
oEfficient algorithms are employed to ensure accurate and fast string analysis.
oLogical design principles are applied to minimize time complexity and ensure correctness of
output.
8.User Interface and Input Handling
oFor tools with graphical or console interfaces, input handling techniques are used to read user
inputs and display results in a user-friendly manner.
oError handling ensures the program remains stable even with invalid or unexpected inputs.
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8. Algorithm
1. Start
2. Input
Accept a string input from the user using a Scanner class.
3. Initialize Variables
Initialize variables to store:
oTotal number of characters
oNumber of vowels, consonants, digits, and special characters
oWord count
oFrequency of each character (using a HashMap or array)
4. Process the String
Traverse each character of the string using a loop:
1.Count Characters: Increment total character count for each iteration (excluding spaces if
required).
2.Identify Character Type:
If the character is a vowel (a, e, i, o, u), increment vowel count.
Else if it’s a consonant (alphabetic but not a vowel), increment consonant count.
If it’s a digit, increment digit count.
If it’s a special character (not alphanumeric), increment special character count.
3.Store Frequency:
Use a HashMap<Character, Integer> to record how many times each character
appears.
5. Count Words
Split the string by spaces using split(" ") and count the number of resulting elements.
6. Check for Palindrome
Convert the string to lowercase, remove spaces, and compare it with its reverse using
StringBuilder.reverse().
oIf both are equal → the string is a palindrome.
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9. oElse → not a palindrome.
7. Display Results
Print all the calculated results:
oLength of the string
oNumber of words, vowels, consonants, digits, and special characters
oFrequency of each character
oWhether the string is a palindrome or not
8. End
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10. Results and Discussion
The String Analyzer Tool in Java successfully performs various string processing operations such as
counting characters, words, vowels, consonants, digits, and special characters, as well as identifying
palindromes and analyzing character frequency. The program was tested using different input strings to verify
accuracy, efficiency, and reliability.
Sample Input and Output
Input String:
Hello World 123!
Output:
Original String: Hello World 123!
Total Characters: 15
Total Words: 3
Vowels: 3
Consonants: 7
Digits: 3
Special Characters: 2
Character Frequency:
H = 1
e = 1
l = 3
o = 2
W = 1
r = 1
d = 1
1 = 1
2 = 1
3 = 1
! = 1
Palindrome: No
DISCUSSION
The output demonstrates that the String Analyzer Tool accurately analyzes and categorizes every character in
the input string. The word count is determined using space separation, while character frequencies are
computed through a HashMap data structure, ensuring efficient lookups and updates.
During testing, various types of strings were analyzed:
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11. Alphabetic strings: The tool correctly identified vowels and consonants.
Alphanumeric strings: Digits and letters were separated accurately.
Strings with special characters: Symbols and punctuation were counted precisely.
Palindromic strings (e.g., “madam”, “racecar”): Correctly identified as palindromes after case
normalization and space removal.
The algorithm performed efficiently for short and medium-length strings, with negligible processing time. For
very long strings, performance remained stable due to optimized looping and use of built-in Java methods like
split(), toLowerCase(), and StringBuilder.reverse().
Overall, the String Analyzer Tool provides accurate and detailed insights into textual data, making it a useful
program for learning string manipulation concepts in Java. Its modular structure also allows easy extension —
for example, adding features like word frequency, substring search, or pattern validation using regular
expressions.
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12. Conclusion
The String Analyzer Tool is an efficient and versatile Java application designed to analyze and process
textual data. It successfully performs various string operations such as counting characters, words, vowels,
consonants, digits, and special symbols, as well as checking for palindromes and computing character
frequencies. Through the implementation of key programming concepts like loops, conditional statements,
string manipulation, and data structures such as arrays and hash maps, the tool demonstrates effective use of
core Java principles.
The project enhances understanding of string handling in Java and emphasizes the importance of algorithmic
thinking in solving text-processing problems. The results obtained from multiple test cases confirm that the
tool is accurate, reliable, and user-friendly. Moreover, its modular design allows for easy future enhancements,
such as adding advanced features like word frequency analysis, regular expression pattern matching, and file-
based input/output.
In conclusion, the String Analyzer Tool not only serves as a practical demonstration of Java programming
concepts but also provides a foundation for developing more complex text analysis applications in the future.
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13. References


Herbert Schildt, Java: The Complete Reference, 12th Edition, McGraw-Hill Education, 2021.


Oracle Documentation, Java Platform, Standard Edition Documentation, https://docs.oracle.com/javase/


W3Schools, Java Strings Tutorial, https://www.w3schools.com/java/java_strings.asp


GeeksforGeeks, String Handling in Java, https://www.geeksforgeeks.org/string-handling-in-java/


TutorialsPoint, Java String Class, https://www.tutorialspoint.com/java/java_strings.htm


Baeldung, Guide to Java Strings, https://www.baeldung.com/java-strings


Stack Overflow Community, Discussions on Java string manipulation and algorithms,
https://stackoverflow.com/
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