COMPUTER SCIENCE (868)
CLASS XII
There will be two papers in the subject: Verify the laws of Boolean algebra using
Paper I: Theory……….. 3 hours….70 marks truth tables. Inputs, outputs for circuits like
half and full adders, majority circuit etc.,
Paper II: Practical…….. 3 hours….30 marks
SOP and POS representation; Maxterms &
PAPER I –THEORY – 70 MARKS Minterms, Canonical and Cardinal
SECTION A representation, reduction using Karnaugh
maps and Boolean algebra.
1. Boolean Algebra
(a) Propositional logic, well formed formulae, 2. Computer Hardware
truth values and interpretation of well formed
(a) Elementary logic gates (NOT, AND, OR,
formulae (wff), truth tables, satisfiable,
NAND, NOR, XOR, XNOR) and their use in
unsatisfiable and valid formulae. Equivalence
circuits.
laws and their use in simplifying wffs.
(b) Applications of Boolean algebra and logic
Propositional variables; the common logical
gates to half adders, full adders, encoders,
connectives (~ (not)(negation), ∧
decoders, multiplexers, NAND, NOR as
(and)(conjunction), ∨ (or)(disjunction), ⇒
universal gates.
(implication), ⇔ (biconditional); definition
of a well-formed formula (wff); Show the correspondence between Boolean
`representation of simple word problems as methods and the corresponding switching
wff (this can be used for motivation); the circuits or gates. Show that NAND and NOR
values true and false; interpretation of a wff; gates are universal by converting some circuits
truth tables; satisfiable, unsatisfiable and to purely NAND or NOR gates.
valid formulae. SECTION B
Equivalence laws: commutativity of ∧, ∨; The programming element in the syllabus (Sections B
associativity of ∧, ∨; distributivity; De and C) is aimed at algorithmic problem solving and
Morgan’s laws; law of implication (p ⇒ q ≡ not merely rote learning of Java syntax. The Java
~p ∨ q); law of biconditional ((p ⇔ q) ≡ version used should be 5.0 or later. For programming,
(p ⇒ q) ∧ (q ⇒ p)); identity (p ≡ p); law of the students can use any text editor and the javac and
negation (~ (~p) ≡ p); law of excluded java programs or any other development
middle (p ∨~p ≡ true); law of contradiction environment: for example, BlueJ, Eclipse, NetBeans
(p∧~p ≡ false); tautology and contingency etc. BlueJ is strongly recommended for its simplicity,
simplification rules for ∧, ∨. Converse, ease of use and because it is very well suited for an
inverse and contra positive. ‘objects first’ approach.
(b) Binary valued quantities; basic postulates 3. Implementation of algorithms to solve
of Boolean algebra; operations AND, OR and problems
NOT; truth tables.
The students are required to do lab assignments
(c) Basic theorems of Boolean algebra in the computer lab concurrently with the
(e.g. duality, idempotence, commutativity, lectures. Programming assignments should be
associativity, distributivity, operations with 0 done such that each major topic is covered in at
and 1, complements, absorption, involution); least one assignment. Assignment problems
De Morgan’s theorem and its applications; should be designed so that they are sufficiently
reducing Boolean expressions to sum of challenging. Students must do algorithm design,
products and product of sums forms; address correctness issues, implement and
Karnaugh maps (up to four variables). execute the algorithm in Java and debug where
necessary.
Self explanatory.
1
(ISC Revised Syllabus 2024)
, 4. Programming in Java (Review of Class XI 10. Arrays, Strings
Sections B and C)
Structured data types – arrays (single and multi-
Note that items 4 to 13 should be introduced dimensional), address calculations, strings.
almost simultaneously along with classes and Example algorithms that use structured data types
their definitions. (e.g. searching, finding maximum/minimum,
sorting techniques, solving systems of linear
While reviewing, ensure that new higher order
equations, substring, concatenation, length,
problems are solved using these constructs.
access to char in string, etc.).
5. Objects
Storing many data elements of the same type
(a) Objects as data (attributes) + behaviour requires structured data types – like arrays.
(methods); object as an instance of a class. Access in arrays is constant time and does not
Constructors. depend on the number of elements. Address
calculation (row major and column major),
(b) Analysis of some real-world programming
Sorting techniques (bubble, selection, insertion).
examples in terms of objects and classes.
Structured data types can be defined by classes –
(c) Basic input/output using Scanner from JDK; String. Introduce the Java library String class
input/output exceptions. Tokens in an input and the basic operations on strings (accessing
stream, concept of whitespace. individual characters, various substring
operations, concatenation, replacement, index of
6. Primitive values, Wrapper classes, Types and
operations).
casting
11. Recursion
Primitive values and types: byte, int, short, long,
float, double, boolean, char. Corresponding Concept of recursion, simple recursive methods
wrapper classes for each primitive type. Class as (e.g. factorial, GCD, binary search, conversion of
type of the object. Class as mechanism for user representations of numbers between different
defined types. Changing types through user bases).
defined casting and automatic type coercion for
Many problems can be solved very elegantly by
some primitive types.
observing that the solution can be composed of
7. Variables, Expressions solutions to ‘smaller’ versions of the same
problem with the base version having a known
Variables as names for values; named constants
simple solution. Recursion can be initially
(final), expressions (arithmetic and logical) and
motivated by using recursive equations to define
their evaluation (operators, associativity,
certain methods. These definitions are fairly
precedence). Assignment operation; difference
obvious and are easy to understand. The
between left hand side and right hand side of
definitions can be directly converted to a
assignment.
program. Emphasize that any recursion must
8. Statements, Scope have a base case. Otherwise, the computation
can go into an infinite loop.
Statements; conditional (if, if else, if else if,
switch case, ternary operator), looping (for, The tower of Hanoi is a very good example of
while, do while, continue, break); grouping how recursion gives a very simple and elegant
statements in blocks, scope and visibility of solution where as non-recursive solutions are
variables. quite complex.
9. Methods
SECTION C
Methods (as abstractions for complex user
defined operations on objects), formal arguments Inheritance, Interface, Polymorphism, Data
and actual arguments in methods; Static method structures, Computational complexity
and variables. The this Operator. Examples of 12. Inheritance, Interfaces and Polymorphism
algorithmic problem solving using methods
(number problems, finding roots of algebraic (a) Inheritance; super and derived classes;
equations etc.). member access in derived classes;
redefinition of variables and methods in
2
(ISC Revised Syllabus 2024)
CLASS XII
There will be two papers in the subject: Verify the laws of Boolean algebra using
Paper I: Theory……….. 3 hours….70 marks truth tables. Inputs, outputs for circuits like
half and full adders, majority circuit etc.,
Paper II: Practical…….. 3 hours….30 marks
SOP and POS representation; Maxterms &
PAPER I –THEORY – 70 MARKS Minterms, Canonical and Cardinal
SECTION A representation, reduction using Karnaugh
maps and Boolean algebra.
1. Boolean Algebra
(a) Propositional logic, well formed formulae, 2. Computer Hardware
truth values and interpretation of well formed
(a) Elementary logic gates (NOT, AND, OR,
formulae (wff), truth tables, satisfiable,
NAND, NOR, XOR, XNOR) and their use in
unsatisfiable and valid formulae. Equivalence
circuits.
laws and their use in simplifying wffs.
(b) Applications of Boolean algebra and logic
Propositional variables; the common logical
gates to half adders, full adders, encoders,
connectives (~ (not)(negation), ∧
decoders, multiplexers, NAND, NOR as
(and)(conjunction), ∨ (or)(disjunction), ⇒
universal gates.
(implication), ⇔ (biconditional); definition
of a well-formed formula (wff); Show the correspondence between Boolean
`representation of simple word problems as methods and the corresponding switching
wff (this can be used for motivation); the circuits or gates. Show that NAND and NOR
values true and false; interpretation of a wff; gates are universal by converting some circuits
truth tables; satisfiable, unsatisfiable and to purely NAND or NOR gates.
valid formulae. SECTION B
Equivalence laws: commutativity of ∧, ∨; The programming element in the syllabus (Sections B
associativity of ∧, ∨; distributivity; De and C) is aimed at algorithmic problem solving and
Morgan’s laws; law of implication (p ⇒ q ≡ not merely rote learning of Java syntax. The Java
~p ∨ q); law of biconditional ((p ⇔ q) ≡ version used should be 5.0 or later. For programming,
(p ⇒ q) ∧ (q ⇒ p)); identity (p ≡ p); law of the students can use any text editor and the javac and
negation (~ (~p) ≡ p); law of excluded java programs or any other development
middle (p ∨~p ≡ true); law of contradiction environment: for example, BlueJ, Eclipse, NetBeans
(p∧~p ≡ false); tautology and contingency etc. BlueJ is strongly recommended for its simplicity,
simplification rules for ∧, ∨. Converse, ease of use and because it is very well suited for an
inverse and contra positive. ‘objects first’ approach.
(b) Binary valued quantities; basic postulates 3. Implementation of algorithms to solve
of Boolean algebra; operations AND, OR and problems
NOT; truth tables.
The students are required to do lab assignments
(c) Basic theorems of Boolean algebra in the computer lab concurrently with the
(e.g. duality, idempotence, commutativity, lectures. Programming assignments should be
associativity, distributivity, operations with 0 done such that each major topic is covered in at
and 1, complements, absorption, involution); least one assignment. Assignment problems
De Morgan’s theorem and its applications; should be designed so that they are sufficiently
reducing Boolean expressions to sum of challenging. Students must do algorithm design,
products and product of sums forms; address correctness issues, implement and
Karnaugh maps (up to four variables). execute the algorithm in Java and debug where
necessary.
Self explanatory.
1
(ISC Revised Syllabus 2024)
, 4. Programming in Java (Review of Class XI 10. Arrays, Strings
Sections B and C)
Structured data types – arrays (single and multi-
Note that items 4 to 13 should be introduced dimensional), address calculations, strings.
almost simultaneously along with classes and Example algorithms that use structured data types
their definitions. (e.g. searching, finding maximum/minimum,
sorting techniques, solving systems of linear
While reviewing, ensure that new higher order
equations, substring, concatenation, length,
problems are solved using these constructs.
access to char in string, etc.).
5. Objects
Storing many data elements of the same type
(a) Objects as data (attributes) + behaviour requires structured data types – like arrays.
(methods); object as an instance of a class. Access in arrays is constant time and does not
Constructors. depend on the number of elements. Address
calculation (row major and column major),
(b) Analysis of some real-world programming
Sorting techniques (bubble, selection, insertion).
examples in terms of objects and classes.
Structured data types can be defined by classes –
(c) Basic input/output using Scanner from JDK; String. Introduce the Java library String class
input/output exceptions. Tokens in an input and the basic operations on strings (accessing
stream, concept of whitespace. individual characters, various substring
operations, concatenation, replacement, index of
6. Primitive values, Wrapper classes, Types and
operations).
casting
11. Recursion
Primitive values and types: byte, int, short, long,
float, double, boolean, char. Corresponding Concept of recursion, simple recursive methods
wrapper classes for each primitive type. Class as (e.g. factorial, GCD, binary search, conversion of
type of the object. Class as mechanism for user representations of numbers between different
defined types. Changing types through user bases).
defined casting and automatic type coercion for
Many problems can be solved very elegantly by
some primitive types.
observing that the solution can be composed of
7. Variables, Expressions solutions to ‘smaller’ versions of the same
problem with the base version having a known
Variables as names for values; named constants
simple solution. Recursion can be initially
(final), expressions (arithmetic and logical) and
motivated by using recursive equations to define
their evaluation (operators, associativity,
certain methods. These definitions are fairly
precedence). Assignment operation; difference
obvious and are easy to understand. The
between left hand side and right hand side of
definitions can be directly converted to a
assignment.
program. Emphasize that any recursion must
8. Statements, Scope have a base case. Otherwise, the computation
can go into an infinite loop.
Statements; conditional (if, if else, if else if,
switch case, ternary operator), looping (for, The tower of Hanoi is a very good example of
while, do while, continue, break); grouping how recursion gives a very simple and elegant
statements in blocks, scope and visibility of solution where as non-recursive solutions are
variables. quite complex.
9. Methods
SECTION C
Methods (as abstractions for complex user
defined operations on objects), formal arguments Inheritance, Interface, Polymorphism, Data
and actual arguments in methods; Static method structures, Computational complexity
and variables. The this Operator. Examples of 12. Inheritance, Interfaces and Polymorphism
algorithmic problem solving using methods
(number problems, finding roots of algebraic (a) Inheritance; super and derived classes;
equations etc.). member access in derived classes;
redefinition of variables and methods in
2
(ISC Revised Syllabus 2024)
