Class 11th
IMP QUESTION
Informatics Practices (065)
Class XI – Sample Paper Solutions (2024-25)
SECTION A
Q1. Outline one step to gather information about a corrupted external hard drive.
Ask the client when the hard drive stopped working and what error message appears when connecting it to the computer.
Q2. 1 TB = ______ GB
1024 GB
Q3. Which unit performs arithmetic and logical operations?
ALU (Arithmetic Logic Unit)
Q4. Software designed specifically for restaurant management is called?
Specific Purpose Software
Q5. What should be avoided when naming identifiers in Python?
Using reserved keywords
Q6. Correct way to calculate average of three subjects.
avg = (marksMaths + marksEnglish + marksIP) / 3
Q7. Correct syntax of Python if statement.
if a > 10:
Q8. What does NULL represent in MySQL?
NULL represents a missing or unknown value.
Q9. Correct SQL statement to insert 80 into Marks column.
INSERT INTO Student (Marks) VALUES (80);
Q10. An attribute is a set of values of dissimilar data types.
False
Q11. Which SQL command category removes a column?
DDL (Data Definition Language)
Q12. Identify the error in CREATE TABLE Books;
Column definitions are missing.
Q13. Domain of FurnitureName.
Alphabets and space
Q14. Store table initially has 6 rows and 4 columns. One row added.
Degree = 4
Cardinality = 7
Cardinality = 7
Q15. Cloud service suitable for running custom applications.
Platform as a Service (PaaS)
Q16. AI branch that processes human language.
Natural Language Processing (NLP)
Q17. Assertion-Reason (Dictionary indexing).
Both Assertion and Reason are False.
Q18. Assertion-Reason (Tuple represents row).
Both are True and Reason correctly explains Assertion.
SECTION B
Q19. Explain: Hardware is useless without software.
Hardware requires software instructions to perform tasks. Software programs run only when hardware executes them. Therefore both depend on each other.
Q20. Predict the output:
i = 1
sum_squares = 0
while i <= 7:
sum_squares = sum_squares + i**2
i = i + 2
print(sum_squares)
1
10
35
84
10
35
84
Q21. Correct the program.
i = 10
difference = 0
for i in range(10,0,-3):
if i % 2 == 0:
difference = difference - i
else:
difference = difference - i
print(difference)
Q22. Evaluate the expressions.
(i) Result = 28
(ii) Result = True
(ii) Result = True
Q23. Correct SQL statements.
ALTER TABLE Employee MODIFY Name VARCHAR(30);
UPDATE Employee
SET Dept='Analyst'
WHERE DeptID=2 AND Salary>40000;
Q24. SQL queries for Netflix table.
DELETE FROM Netflix WHERE MovieID IN (1,4);
SELECT * FROM Netflix WHERE MovieID NOT IN (1,4);
Q25. Resolve database error.
USE Employee;CREATE DATABASE Employee;
SECTION C
Q26. Convert while loop into for loop.
for num in range(30,9,-10):
print(num)
Loop executes 3 times.
Q27. Output of program.
Length of my_list: 5
[10, 20]
Sorted list: [10, 20, 30, 40, 50]
[10, 20]
Sorted list: [10, 20, 30, 40, 50]
Q28. SQL command to add 5 students.
UPDATE School SET NoOfStudents = NoOfStudents + 5;
Reason: NULL + 5 remains NULL.
Q29. Output of SQL query.
1
0
0
0
0
Q30. Identify field of application.
| Application | Field |
|---|---|
| Voice assistant | AI |
| Smart thermostat | IoT |
| Sentiment analysis | NLP |
SECTION D
Q31. Match the following.
| Item | Answer |
|---|---|
| Interpreter | Language Processor |
| Backup Software | Utility Software |
| PowerPoint | Application Software |
| Linux | System Software |
Input and Output Devices
Input: Scanner, Barcode Reader
Output: Plotter, Speaker
Output: Plotter, Speaker
Q32. Output of dictionary and list programs.
Dictionary Output:
{'Aman': 80, 'Sumit': 30, 'Dinesh': 50, 'Suresh': 80}
{'Aman': 80, 'Sumit': 30, 'Dinesh': 30, 'Suresh': 20}
List Output:
[10,20,30,40,50,60]
[10,20,40,50,60]
{'Aman': 80, 'Sumit': 30, 'Dinesh': 50, 'Suresh': 80}
{'Aman': 80, 'Sumit': 30, 'Dinesh': 30, 'Suresh': 20}
List Output:
[10,20,30,40,50,60]
[10,20,40,50,60]
SECTION E
Q33. SQL Queries
SELECT CarName FROM Carden WHERE Colour='Silver';
ALTER TABLE Carden ADD Charges INT;
SELECT Ccode FROM Carden WHERE CarName='Indigo';
UPDATE Carden SET CarName='Fortuner' WHERE Capacity=7;
SELECT Make FROM Carden WHERE Capacity>3;
Q34. SQL Query Outputs
John Doe
Michael Johnson
Green Party
Liberal Party
Conservative Party
No Output
District C
District B
4050
Michael Johnson
Green Party
Liberal Party
Conservative Party
No Output
District C
District B
4050
Q35. Python Dictionary Operations
print(indian_library_catalog["Literary Fiction"])
del indian_library_catalog["Novel"]
print(len(indian_library_catalog))
print(indian_library_catalog.values())
indian_library_catalog["Thriller"] = "The Girl on the Train"
Q.1 Explain Codd’s Rules.
Answer :-
Codd’s rules, proposed by Dr. Edgar F. Codd in 1985, serve as a benchmark for evaluating whether a database management system (DBMS) is truly relational.
Codd originally defined 12 rules, including a rule 0, which collectively outline the characteristics a system must exhibit to qualify as a relational database.
These rules ensure data integrity, independence, and consistency in relational database management systems (RDBMS).
Rule 0: Foundation Rule :
For a system to qualify as a relational database, it must manage data entirely through its relational capabilities.
The system must use relational techniques for data storage, retrieval, and manipulation without relying on external tools or approaches.
Rule 1: Information Rule :
All information in the database is represented in a single logical way—as values in tables.
Data is stored in tables, with each table consisting of rows (tuples) and columns (attributes).
The database uses these tables as the sole method to represent both the data and its metadata (e.g., table names, column names).
Rule 2: Guaranteed Access Rule
Every data element is accessible by a combination of table name, primary key, and column name.
This rule ensures that every piece of information in the database can be uniquely identified and accessed.
Rule 3: Systematic Treatment of Null Values
Null values are uniformly supported for representing missing or inapplicable data.
Null values must be distinctly handled, separate from zero or an empty string.
Nulls indicate that a value is either unknown, missing, or irrelevant.
Rule 4: Active Online Catalog
The database must have a self-describing nature, storing metadata within the database itself and making it accessible via query.
Metadata (such as table structures, relationships, and constraints) is stored in a format that users can query using the same methods as data.
Rule 5: Comprehensive Data Sub-Language Rule
A single language, such as SQL, must support all tasks, including:
Data Definition Language (DDL) for creating and modifying schemas.
Data Manipulation Language (DML) for querying and updating data.
Data Control Language (DCL) for managing access permissions.
Rule 6: View Updating Rule
Any view that is theoretically updatable must be updatable through the system.
A view (virtual table) provides a filtered or transformed perspective of data.
If a view logically supports updates, the database must allow users to perform updates on the view, which will reflect on the base table.
Rule 7: High-Level Insert, Update, and Delete
The database must support set-level operations for modifying data.
Users should be able to insert, update, or delete multiple rows simultaneously using a single command, rather than operating on rows individually.
Rule 8: Physical Data Independence
Changes to the physical storage structure should not affect how data is accessed at the logical level.
For example, reorganizing data on disk, adding indexes, or changing storage devices should not require modifications to user queries or applications.
Rule 9: Logical Data Independence
Changes to the logical structure (schema) of the database should not affect existing applications.
For instance, adding a new column to a table should not disrupt existing queries that do not use that column.
Rule 10: Integrity Independence
Integrity constraints must be defined in the database and not in application programs.
Constraints such as primary keys, foreign keys, and check conditions should be enforced by the database itself, ensuring data integrity regardless of the application interacting with the database.
Rule 11: Distribution Independence
The database should function as if it were centralized, even if the data is distributed across multiple locations.
Users and applications should not need to know whether the data is stored locally or across various servers.
Rule 12: Non-Subversion Rule
No low-level operation should bypass the integrity rules defined in the database.
If the system provides alternative access methods (e.g., direct file manipulation), they must not compromise the integrity constraints or relational principles.
