Expression Parsing | Programming and Data Structures - Computer Science Engineering (CSE) PDF Download

Introduction

The way to write arithmetic expression is known as a notation. An arithmetic expression can be written in three different but equivalent notations, i.e., without changing the essence or output of an expression. These notations are:

  • Infix Notation
  • Prefix (Polish) Notation
  • Postfix (Reverse-Polish) Notation

These notations are named as how they use operator in expression. We shall learn the same here in this chapter.

Infix Notation

We write expression in infix notation, e.g. a - b + c, where operators are used in-between operands. It is easy for us humans to read, write, and speak in infix notation but the same does not go well with computing devices. An algorithm to process infix notation could be difficult and costly in terms of time and space consumption.

Prefix Notation

In this notation, operator is prefixed to operands, i.e. operator is written ahead of operands. For example, +ab. This is equivalent to its infix notation a + b. Prefix notation is also known as Polish Notation.

Postfix Notation

This notation style is known as Reversed Polish Notation. In this notation style, the operator is postfixed to the operands i.e., the operator is written after the operands. For example, ab+. This is equivalent to its infix notation a + b.
The following table briefly tries to show the difference in all three notations −
Expression Parsing | Programming and Data Structures - Computer Science Engineering (CSE)

Parsing Expressions

As we have discussed, it is not a very efficient way to design an algorithm or program to parse infix notations. Instead, these infix notations are first converted into either postfix or prefix notations and then computed.
To parse any arithmetic expression, we need to take care of operator precedence and associativity also.

Precedence
When an operand is in between two different operators, which operator will take the operand first, is decided by the precedence of an operator over others. For example:
Expression Parsing | Programming and Data Structures - Computer Science Engineering (CSE)As multiplication operation has precedence over addition, b * c will be evaluated first. A table of operator precedence is provided later.

Associativity
Associativity describes the rule where operators with the same precedence appear in an expression. For example, in expression a + b − c, both + and – have the same precedence, then which part of the expression will be evaluated first, is determined by associativity of those operators. Here, both + and − are left associative, so the expression will be evaluated as (a + b) − c.
Precedence and associativity determines the order of evaluation of an expression. Following is an operator precedence and associativity table (highest to lowest) −
Expression Parsing | Programming and Data Structures - Computer Science Engineering (CSE)
The above table shows the default behavior of operators. At any point of time in expression evaluation, the order can be altered by using parenthesis. For example −
In a + b*c, the expression part b*c will be evaluated first, with multiplication as precedence over addition. We here use parenthesis for a + b to be evaluated first, like (a + b)*c.

Postfix Evaluation Algorithm

We shall now look at the algorithm on how to evaluate postfix notation:
Step 1: scan the expression from left to right
Step 2: if it is an operand push it to stack
Step 3: if it is an operator pull operand from stack and perform operation
Step 4: store the output of step 3, back to stack
Step 5: scan the expression until all operands are consumed
Step 6: pop the stack and perform operation

The document Expression Parsing | Programming and Data Structures - Computer Science Engineering (CSE) is a part of the Computer Science Engineering (CSE) Course Programming and Data Structures.
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FAQs on Expression Parsing - Programming and Data Structures - Computer Science Engineering (CSE)

1. What is expression parsing?
Ans. Expression parsing refers to the process of analyzing a mathematical or logical expression and breaking it down into its individual components, such as operators and operands, in order to evaluate or manipulate it.
2. Why is expression parsing important?
Ans. Expression parsing is important because it allows computer programs to understand and interpret mathematical or logical expressions provided by the user. It enables the program to perform calculations, make decisions, and execute specific commands based on the expression's meaning.
3. What are the different types of expressions that can be parsed?
Ans. There are different types of expressions that can be parsed, including arithmetic expressions (e.g., addition, subtraction, multiplication), logical expressions (e.g., AND, OR), relational expressions (e.g., greater than, less than), and conditional expressions (e.g., if-else statements).
4. How is expression parsing typically implemented in programming languages?
Ans. Expression parsing is typically implemented by using algorithms and data structures, such as recursive descent parsing or the use of expression trees. These techniques help in analyzing and evaluating the expression by breaking it down into smaller components and applying the appropriate operations.
5. What are some challenges in expression parsing?
Ans. Some challenges in expression parsing include handling operator precedence and associativity, dealing with parentheses and nested expressions, handling error cases such as division by zero or invalid syntax, and ensuring efficient evaluation of complex expressions.
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