1. Overview of program analysis Mooly Sagiv html://www.math.tau.ac.il/~msagiv/courses/wcc03.html

2. Exam Format (Moed A 02) Compile- vs Run-time events (25) American style question (10) Handling new language feature in TC (40) Understanding (25)

3. Outline What is (static) program analysis Examples Undecidability Algorithms

4. Static Analysis Automatic derivation of static properties which hold on every execution leading to a program location Usages –Compiler optimizations –Code quality tools Identify bugs Prove absence of certain bugs

5. Example Static Analysis Problem Find variables with constant value at a given program location int p(int x){ return x *x ; } void main() { int z; if (getc()) z = p(6) + 8; else z = p(5) + 7; printf (z); } int p(int x){ return (x *x) ; } void main() { int z; if (getc()) z = p(3) + 1; else z = p(-2) + 6; printf (z); }

6. Example Static Analysis Problem Find variables which are live at a given program location

7. A Simple Example /* c */ L0: a := 0 /* ac */ L1:b := a + 1 /* bc */ c := c + b /* bc */ a := b * 2 /* ac */ if c < N goto L1 /* c */ return c ab c

8. List reverse(Element  head) { List rev, n; rev = NULL; while (head != NULL) { n = head  next; head  next = rev; head = n; rev = head; } return rev; } Memory Leakage leakage of address pointed to by head

9. Memory Leakage Element  reverse(Element  head) { Element  rev,  n; rev = NULL; while (head != NULL) { n = head  next; head  next = rev; rev = head; head = n; } return rev; } ✔ No memory leaks

10. Compiler Scheme String Scanner Parser Semantic Analysis Code Generator Static analysis Transformations Tokens source-program tokens AST IR IR +information

11. Undecidability issues It is impossible to compute exact static information Finding if a program point is reachable Difficulty of interesting data properties

12. Undecidabily A variable is live at a given point in the program –if its current value is used after this point prior to a definition in some execution path It is undecidable if a variable is live at a given program location

13. Proof Sketch Pr L: x := y Is y live at L?

14. Conservative (Sound) The compiler need not generate the optimal code Can use more registers (“spill code”) than necessary Find an upper approximation of the live variables Err on the safe side A superset of edges in the interference graph Not too many superfluous live variables

15. Conservative Software Quality Tools Can never miss an error Buy may produce false alarms –Warning on non existing errors

16. Iterative computation of conservative static information Construct a control flow graph Optimistically start with the best value at every node “Interpret” every statement in a conservative way Stop when no changes occur

17. /* c */ L0: a := 0 /* ac */ L1:b := a + 1 /* bc */ c := c + b /* bc */ a := b * 2 /* ac */ if c < N goto L1 /* c */ return c a := 0 ; b := a +1 ; c := c +b ; a := b*2 ; c <N goto L1 return c ;

18. a := 0 ; b := a +1 ; c := c +b ; a := b*2 ; c <N goto L1 return c ;      

19. a := 0 ; b := a +1 ; c := c +b ; a := b*2 ; c <N goto L1 return c ;  {c}    

20. a := 0 ; b := a +1 ; c := c +b ; a := b*2 ; c <N goto L1 return c ;  {c}   

21. a := 0 ; b := a +1 ; c := c +b ; a := b*2 ; c <N goto L1 return c ;  {c} {c, b}  

22. a := 0 ; b := a +1 ; c := c +b ; a := b*2 ; c <N goto L1 return c ;  {c} {c, b} 

23. a := 0 ; b := a +1 ; c := c +b ; a := b*2 ; c <N goto L1 return c ;  {c} {c, b} {c, a} {c, b}

24. a := 0 ; b := a +1 ; c := c +b ; a := b*2 ; c <N goto L1 return c ;  {c, a} {c} {c, b} {c, a} {c, b}

25. a := 0 ; b := a +1 ; c := c +b ; a := b*2 ; c <N goto L1 return c ;  {c, a} {c, b} {c, a} {c, b}

26. Summary Program analysis provides non-trivial insights on the runtime executions of the program Mathematically justified –Operational semantics –Abstract interpretation (lattice theory) Employed in compilers Will be employed in software quality tools But the course in TAU is theoretical