The document discusses imperative programming paradigms, emphasizing that they focus on how a program operates through a sequence of instructions that can alter memory states and allow side effects. It also covers the importance of data types, variable scope, and the concept of procedural programming as a subtype of imperative programming aimed at modularity and code reuse. Additionally, it includes a case study on stack implementation in C, detailing operations like push and pop.

1. R E H A B B E N A B D U L L A
R E H A B B E N A B D U L L A @ G M I L . C O M
Imperative programming
paradigms
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2. Imperative programming paradigms
 Imperative programming focuses on describing how a
program operates.
 Imperative programs describe
the details of HOW the results are to be obtained, in terms of
the underlying machine model.
 An imperative program consists of commands for
the computer to perform.
 In imperative paradigm we solve problems step by step by
telling the computer what to do next.
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3. Imperative programming paradigms
 An imperative program is a list, or sequence, of
instructions.
 The execution of each operation can alter the
memory state.
 Imperative programming allows side effects.
 Change the value of variables.
 This style of programming is directly inspired by
assembly programming.
 You find it in the earliest general-purpose
programming languages (Fortran, C, Pascal, etc.)
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4. Imperative programming paradigms
 Data and Computation
 In imperative programming we must consider how the data is
represented and how the computations are carried out.
 Data
 Variables
 Data types
 Computation
 Assignments and expressions
 Control structures
 Subprograms / routines
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5. Data and Computation
 Name and Scope
 Declaration
 Identifier rules and significant characters
 Scope
 range of instructions over which variable name is known
 namespaces
 Blocks (as in Pascal or C)
 Static vs dynamic scope binding
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6. Data and Computation
 Why Use Data Types?
 Purpose: classification and protection
 note that all data are ultimately represented as bit-strings
 Advantages:
 abstraction
 compile-time checking and resolution
 explicit specification
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7. Data and Computation
 Type
 Consists of
 Set of values
 Operations
 Built-in/Primitive vs User-defined types
 binding?
 Implicit declarations
 e.g., FORTRAN and first letter of a variable and first assignment in
BASIC or Foxpro
 Dynamic typing
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8. Data and Computation
 Complex Data Types
 User-defined enumeration types
 Composite types
 Aggregations
 cartesian product (records or structures)
 mapping (arrays)
 Unions
 Abstract Data Types.
 ADTs specify/describe behaviors.
 classes
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9. Data and Computation
 Variable
 A named location in memory that can hold a value
 name
 scope
 type
 l-value
 r-value
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10. Data and Computation
 Binding
 Program units/entities have attributes
 e.g., a variable has a name, a statement has associated actions
 Binding
 setting the value of an attribute
 Binding time
 when binding occurs
 Language definition time
 Language implementation time
 Compile-time
 Execution-time
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11. Data and Computation
 Control Statements and Routines
 Expressions and statements
 Conditional execution
 Iteration
 Routines
 Parameter Passing
 Modules and Program Structure
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12. Data and Computation
 Routines
 Program unit; sequence of instructions
 Also a 5-tuple:
 name
 scope
 type
 l-value
 r-value
 Parameter Passing
 By value
 By reference
 Others?
 Activation Records
 Recursion
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13. Procedural programming paradigms
 Procedural programming can be defined as a subtype
of imperative programming as a programming
paradigm.
 Based upon the concept of procedure calls.
 Statements are structured into procedures (also
known as subroutines or functions).
 Why we need procedures or functions?
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14. Procedural programming paradigms
 The focus of procedural programming is to break
down a programming task into a collection of
variables, data structures, and subroutines.
 Writing good functions and procedures
 use the most appropriate implementation and employ correct
efficient algorithms
 To get the benefit of:
 Code reuse.
 Modifiable or updateable variables (side effect).
 Abstraction and modularity.
 Hiding details
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15. Case study: stack
 Stack’s rule is:
 FILO (first in last out).
 The tasks are:
 Push and pop operations.
 The data can be implemented as:
 Array, linked list or other implementations.
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16. Stack program in C
serial program
 Void main()
{
Int max=100;
Int MyStack[max];
Int top=0;
Int x=7;
if(top<max)
MyStack[top++]=x;
elas
printf(“full”)
if(top>0)
x=(MyStack[top--]);
elas
printf(“empty”)
...
...
}
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17. Stack program in C
structured program
Int max=100;
Int MyStack[max];
Int top=0;
Void push(int x)
{
if(top<max)
MyStack[top++]=x;
else
printf(“full”);
}
int pop()
{
if(top>0)
return(MyStack[top--]);
elas
printf(“empty”)
}
Void main()
{
Push(2);
Push(5);
Push(6);
Printf(“%d”,Pop());
...
}
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18. Stack program in C
• One source file
• MyStack and top are global variables
• Stack and application functions
defined at the same level (file)
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19. Procedural programming paradigms:
 Emphasis on procedural abstraction.
 Top-down design;
Step-wise refinement.
 Suited for programming in the small.
 New operations cause additive changes in
procedural style,
 New data representations require modifications to
all “procedure modules”.
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