Dead code elimination

In compiler theory, dead code elimination is a compiler optimization to remove code which does not affect the program results. Removing such code has two benefits: it shrinks program size, an important consideration in some contexts, and it allows the running program to avoid executing irrelevant operations, which reduces its running time. Dead code includes code that can never be executed (unreachable code), and code that only affects dead variables, that is, variables that are irrelevant to the program.

Examples

Consider the following example written in C.

 int foo(void)
 {
   int a = 24;
   int b = 25; /* Assignment to dead variable */
   int c;
   c = a << 2;
   return c;
   b = 24; /* Unreachable code */
   return 0;
 }

Because the return statement is executed unconditionally, no feasible execution path reaches the assignment to b. Thus, the assignment is unreachable and can be removed. (In a procedure with more complex control flow, such as a label after the return statement and a goto elsewhere in the procedure, then a feasible execution path might exist through the assignment to b.)

Simple analysis of the uses of values would show that the value of b is not used inside foo. Furthermore, b is declared as a local variable inside foo, so its value cannot be used outside foo. Thus, the variable b is dead and an optimizer can reclaim its storage space and eliminate its initialization.

Also, even though some calculations are performed in the function, their values are not stored in locations accessible outside the scope of this function. Furthermore, given the function returns a static value (96), it may be simplified to the value it returns (this simplification is called Constant folding).

Most advanced compilers have options to activate dead code elimination, sometimes at varying levels. A lower level might only remove instructions that cannot be executed. A higher level might also not reserve space for unused variables. Yet a higher level might determine instructions or functions that serve no purpose and eliminate them.

A common use of dead code elimination is as an alternative to optional code inclusion via a preprocessor. Consider the following code.

 int main(void) {
   int a = 5;
   int b = 6;
   int c;
   c = a * (b >> 1);
   if (0) {   /* DEBUG */
     printf("%d\n", c);
   }
   return c;
 }

Because the expression 0 will always evaluate to false, the code inside the if statement can never be executed, and dead code elimination would remove it entirely from the optimized program. This technique is common in debugging to optionally activate blocks of code; using an optimizer with dead code elimination eliminates the need for using a preprocessor to perform the same task.

In practice, much of the dead code that an optimizer finds is created by other transformations in the optimizer. For example, the classic techniques for operator strength reduction insert new computations into the code and render the older, more expensive computations dead.^[1] Subsequent dead code elimination removes those calculations and completes the effect (without complicating the strength-reduction algorithm).

Historically, dead code elimination was performed using information derived from data-flow analysis.^[2] An algorithm based on static single assignment form appears in the original journal article on SSA form by Cytron et al.^[3] Shillner improved on the algorithm and developed a companion algorithm for removing useless control-flow operations.^[4]

See also

Computer Science portal

• dead store
• redundant code
• unreachable code
• elimination theory
• conjunction elimination
• mathematical elimination

References

Partial dead code elimination using slicing transformations Found in: Proceedings of the ACM SIGPLAN 1997 conference on Programming language design and implementation (PLDI '97) By Rastislav Bodík , Rajiv Gupta Issue Date:June 1997 pp. 682–694

1. ^ Frances Allen, John Cocke, and Ken Kennedy. Reduction of Operator Strength. In Program Flow Analysis, Muchnick and Jones (editors), Prentice-Hall, 1981.
2. ^ Ken Kennedy. A Survey of Data-flow Analysis Techniques. In Program Flow Analysis, Muchnick and Jones (editors), Prentice-Hall, 1981.
3. ^ Ron Cytron, Jeanne Ferrante, Barry Rosen, and Ken Zadeck. Efficiently Computing Static Single Assignment Form and the Program Dependence Graph. ACM TOPLAS 13(4), 1991.
4. ^ Keith D. Cooper and Linda Torczon, Engineering a Compiler, Morgan Kaufmann, 2003, pages 498ff.

Book references

• Aho, Alfred V.; Sethi, Ravi; Ullman, Jeffrey D. (1986). Compilers - Principles, Techniques and Tools. Addison Wesley Publishing Company. ISBN 0-201-10194-7. 

• Muchnick, Steven S. (1997). Advanced Compiler Design and Implementation. Morgan Kaufmann Publishers. ISBN 1-55860-320-4. 

• Grune, Dick; Bal, Henri E.; Jacobs, Ceriel J.H.; Langendoen, Koen G. (2000). Modern Compiler Design. John Wiley & Sons, Inc.. ISBN 0-471-97697-0. 

External Links

• How to trick C/C++ compilers into generating terrible code?