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Code
Optimization phase in mainly use to optimize the code for better utilization of
memory and reduce the time taken for execution. Code optimization takes input
from intermediate code generator and performs machine independent optimization.
Code optimizer may also take input from code generator and perform machine
dependent code optimization. Compilers that use code optimization transformations
are called as optimizing compilers. Code optimization does not consider target machine
properties for optimization (like register allocation and memory management) if
input is from intermediate code generator.
Code
optimization tries to optimize that part of the code which are executed more
number of times, like statements within flow control block of for statement and
while statement. This is because the most programs always spend maximum
execution time on executing only few statements Code
optimization
analysis programs in two levels control flow analysis and data flow analysis.
In control flow analysis code optimization concentrates more on improving the
code of inner loops than outer statements, as inner loops are executed more
number of times than outer ones. A detailed data flow
analysis is
required for debugging the optimized code. Data flow analysis collects the
information of statistics about statements being executed more number of times.
This information is used in the process if optimization. Code optimization
should be such that best results crop up with minimum
effort.
Code
Optimization has to mainly achieve two goals
1. Preserve the
meaning of code – The output generated before (without) Code Optimization should
be same as the code after optimization.
2. Optimization
should reduce the cost of execution considerably. The effort spent on code optimization
should be worth it.
It implies that
amount of time taken for optimization should be very less when compared to the reduction
of overall execution time. Generally, a fast non optimizing compilers are
preferred for debugging programs
Code improvement
always need not be in code optimization phase. It can be incorporated in source
program or in intermediate code or on target code. In source program say, for
sorting program, user can choose different algorithm based on the cost function
like minimum space or minimum time. Each algorithm can be efficient it its own
way or other, like quick sort is very fast on unsorted/random array where as
other sorting like bubble sort is efficient on partially sorted array.
Intermediate code can be improved by improving loops and efficient address
calculation may give better results. In final code generation phase, optimized
code can be efficiently generated by selecting appropriate instruction, use
registers efficiently and some instruction transformations. Example: Keeping
most
used variables
in registers which avoids frequent fetching and storing in memory location.
This chapter deals with optimization of intermediate code represented as three
address code. Intermediate code is relatively independent at target machine so
optimization is machine independent.
Programs are
represented as flow graphs to study control flow and temporary variables are
used to store intermediate results help in data flow analysis. It is seen that
compilation speed is proportional to the size at program being compiled hence
amount of time taken for code optimization should be relatively less.
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