Table of contents
1.
Introduction
2.
Basic Blocks and Flow Graphs
2.1.
Loops
2.2.
Structure-Preserving Transformation
3.
Next Use Information
3.1.
Applications of Next Use Information
3.2.
Algorithms for Next Use Information
4.
Frequently Asked Questions
4.1.
What is Parsing?
4.2.
What Is Code Motion?
4.3.
What is Symbol Table?
5.
Conclusion
Last Updated: Mar 27, 2024

Next Use Information in Compiler Design

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Introduction

Welcome back, Ninja! We hope you all are doing well. Predicting the next use of a variable's value is crucial for writing effective code. A register can be assigned to another variable if the value of a variable that is now stored there won't ever be used again.

Next Use Information in Compiler Design

The fundamental ideas of flow graphs and next-use information are covered in this article. The produced code's effectiveness, functionality, and security can all be enhanced by incorporating next-use information into compiler design.

Basic Blocks and Flow Graphs

An instruction block with exactly one entry point and one exit point is called a basic block. If branch instructions are considered, there may be multiple exit points. A control flow graph (CFG) is a directed graph with basic blocks. Bi as its vertices and edges Bi->Bj if and only if Bj is capable of being performed right after Bi. 

The scanner and parser of the compiler provide an intermediate representation of the source code during the front-end phase of compilation, which frequently takes the shape of a control flow graph. The control flow graph depicts the program's control flow by breaking it down into fundamental building parts and showing the control flow between them.

An example of a flow graph for the vector dot product is given as follows:

Example of Flow Graph

The initial node is B1. There is an edge from B1 to B2 because B2 comes after B1 immediately. There is an edge from B1 (final statement) to B2 (first statement), as the objective of the jump from B1's last statement is B2's first statement. B1 is the predecessor of B2, while B2 is a successor of B1.

Loops

A flow graph comprises fundamental building components that indicate the control flow direction. This flow graph can occasionally create a loop that circles back around to the fundamental building elements. A loop is made from building blocks so that;

  • The collection's blocks are all strongly related. A tightly connected loop is one in which there is a path of length one or more from each node to any other node inside the loop.
     
  • The collection of blocks has a singular entry, and using this entry is the only way to access a block in the loop.
     

Inner loops are loops that do not contain any other loops. An outside loop is a loop that has one or more inside loops.

Structure-Preserving Transformation

  • Elimination of Frequently Used Sub-Expressions: If a specific expression appears multiple times in a block, it is considered common. This could be eliminated to avoid unnecessary computation. For example, consider the given set of statements:
     
a:=b+c
b:=a-d
c:=b+c
d:=a-d

 

In the above example, the second and fourth expressions compute the same expression, so the basic block can be transformed by replacing the (a-d) with b. So the set of       set statements can be represented as:

a:=b+c
b:=a-d
c:=b+c
d:=b

 

  • Removal of dead code: An instruction is considered dead in a basic block if a specific variable or assignment isn't going to be used. Assume that x is dead, or never used again, at the time the fundamental block phrase x: = y + z appears. The basic block's value can then be safely left unchanged by removing this sentence.
     
  • Temporary variable renaming: Temporary variables are defined to translate instructions into three-address codes. To efficiently optimize the finished code, these variables are renamed. For example, the statement a:=p+q can be changed to b:=p+q where b is the new temporary variable.
     
  • Changing two separate, neighboring statements: An optimized code is produced by rearranging the instructions, and this transformation enables the swapping of two adjacent independent statements. As an example, let's suppose a block has the two adjacent sentences given below:
     
P1 : = b + c
P2 : = x + y

 

We can swap the two lines without changing the value if and only if neither x nor y is P1 and neither b nor c is P2.

Next Use Information

A sort of data flow analysis used in compiler design called the next use information can be used to optimize register allocation in a computer's central processor unit (CPU). The next use analysis aims to identify which program variables will be used soon and should be kept in a register for quicker access rather than main memory. The speed of a compiled program can be further enhanced by combining next usage analysis with other optimization strategies like register allocation and live range analysis.

For a better understanding, consider the given code snippet:

x = y + z;
a = x + b;
c = x + d;

 

The variable x is used three times in this code to store the results; once for the result of y + z, once for the result of x + b, and once for the result of x + d. By removing the load and store operations for x in between usage, the compiler can use this knowledge to optimize the code. 

The compiler might, as an example, produce the following code: 

t1 = y + z;
a = t1 + b;
c = t1 + d;

 

This code has been optimized, and the variable x has been swapped out with the temporary variable t1. This optimization can increase the performance of the generated code by lowering the number of load and store operations.

Applications of Next Use Information

Some of the significant applications of next-use information are given below:

  • The allocation of registers in a computer's CPU is optimized using the knowledge from the next use.
     
  • It aids the compiler in selecting the variables that should be kept in registers for quicker access.
     
  • It can enhance a compiled program's overall performance and lower the number of memory accesses needed.
     
  • It can be used with other optimization strategies, including live range analysis, to enhance performance even further.
     
  • The compiler can produce machine code that is more efficient by using next-usage information.
     
  • It is used to optimize register allocation in a CPU to boost compiled program performance.

Algorithms for Next Use Information

A few examples of algorithms that could be applied in compiler design are as follows:

  • Next use information using Huffman coding: With this algorithm, data is compressed by using fewer bits to encode it than in its original form. The data produced by the compiler can be compressed using Huffman coding, which can reduce the size of the built code and speed up execution.
     
  • Data flow analysis: This approach is used to examine the data flow through a program and find areas for improvement. By removing pointless computations or rearranging instructions to better utilize hardware resources, data flow analysis can be used to optimize the code produced by the compiler.
     
  • Lexical analysis: This approach is used to examine the organization of the source code and pinpoint the program's tokens (basic units of meaning, such as keywords and identifiers). The initial step in the compilation of a program is often Lexical Analysis.
     
  • Syntax analysis: This algorithm examines the source code's organization and creates an abstract syntax tree (AST), which symbolizes the program's hierarchical structure. The compiler can provide optimized code by using the AST. 

Must Read Recursive Descent Parser.

Frequently Asked Questions

What is Parsing?

Parsing is the process of converting information between different formats. This task can be carried out automatically via parsing. The parser is a part of the translator that aids in organizing linear text structure in accordance with the grammar, which is a collection of established rules.

What Is Code Motion?

Code motion is an optimization method that reduces the amount of code in a loop. This transformation can be applied to any expression that produces the same outcome regardless of how many times the loop is run. A statement of this kind comes before the loop.

What is Symbol Table?

A symbol table is a data structure that has a record for every identifier and fields for each identifier's properties. We can rapidly store or retrieve data from a record by using the data structure to locate the record for each identifier.

Conclusion

This blog centers around basic blocks and flow graphs, loops, structure-preserving transformation, the next use information, its applications, algorithms, and some frequently asked questions. 

We sincerely hope you enjoyed the article and learned a lot about it. You can further refer to Compiler designphases of a compiler, and basic blocks and flow graphs for more understanding of the compiler design topics.

For more information, refer to our Guided Path on Coding Ninjas Studio to upskill yourself in PythonData Structures and Algorithms, Competitive ProgrammingSystem Design, and many more!  Head over to our practice platform, Coding Ninjas Studio, to practice top problems, attempt mock tests, read interview experiences and interview bundles, follow guided paths for placement preparations, and much more! 

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