Bug Isolation via Remote Program Sampling

1. Bug Isolation viaRemote Program Sampling Ben Liblit Alex Aiken Alice X. Zheng Michael Jordan Presented By : Arpita Gandhi

2. Motivation • All deployed software systems have bugs • Resources for improvement are limited • The user community outnumbers the testing team • Current systems are not systematic and automated

3. Related Applications • Commercial databases produce log files and inspect them when the user reports a problem • Netscape/Mozilla, Microsoft, GNOME,KDE have opt-in crash reporting systems • Problems?

4. Goals • Gather information systematically from user executions • Perform automatic analysis to fix software quality problems using this information • Speed up the process of bug isolation • Develop an efficient, low overhead system

5. Discussion What do you think about the idea of using users as debuggers? Bugzilla showed 36,937 bugs and an additional 60,191 bugs as duplicates of already reported bugs

6. Design Goals • Modest impact on program performance • Statistically fair and uniformly random sampling • Efficient transmission of client data

7. Sampling Blocks Consider the following piece of code { check(p != NULL); p = p->next; check(i < max); total += sizes[i]; } We want to sample 1/100th of these checks

8. Sampling Blocks • Solution 1 : Maintain a global counter modulo 100 • Problem? for(i = 0 ; i < 10; i++) { check(p != NULL); p = p->next; check(i < max); total += sizes[i]; }

9. Sampling Blocks • Solution 2: Use a random number generator { if(rnd(100) == 0)check (p != NULL); p = p->next; if(rnd(100) == 0) check (i < max); total += sizes[i]; } • Problem?

10. Sampling Blocks • Solution 3: Anticipate future samples Requires two versions of code: • Slow path: • Code with the sampled instrumentation • Fast path: • Code w/o the sampled instrumentation

11. Sampling Blocks Fast Path Code Slow Path Code if (countdown > 2) { p = p->next; total += sizes[i]; } if( countdown-- == 0 ) { check(p != NULL); countdown = getNextCountdown(); } p = p->next; if( countdown-- == 0 ) { check( i < max ); countdown = getNextCountdown(); } total += sizes[i];

12. Sampling Functions • Represent sampling blocks as a CFG • Weight of path is the maximum number of instrumentation sites • Place a countdown threshold check on each acyclic region • For each region r: If (next-sample countdown >weight) no samples taken

13. >4? Instrumented Code Layout

14. Optimizations • Problem: A new threshold check before each function call • Solution: Identify and ignore weightless functions • No threshold checks, instrumented code • Compiled without any modification

15. Optimizations • Problem: Use of global variable for countdown management expensive • Solution: Use Local Variables global Function entry Function exit Local 2 Local 1 Local 3 Use for threshold check, sampling decisions, decrements

16. Issues in Program Sampling • Factors that hamper performance • Remote monitoring • Local storage • Use of network bandwidth • Storage on central server • For smaller level deployment? • Adaptive refinement of instrumentation

17. Other Issues • Social and ethical concern • Users’ interest in contribution • Learning curve with software • More testers vs. remote sampling?

18. Applications • Sharing cost of assertions • Isolating deterministic bugs • Isolating non – deterministic bugs

19. Experiments • Sharing the cost of assertions • Sample assert ( ) statements in CCURED code • Overhead incurred:

20. Effectiveness of Sampling • At density 1/1000 for observing rare program behavior? To achieve confidence level =90%, Least number of runs needed = 230,258 ! Solution: No. of licensed Office XP users = 16 million 2 runs/week/user = 230258 runs every 19 min!

21. References • Sampling User Executions for Bug Isolation • Public Deployment of Cooperative Bug Isolation • Scalable Statistical Bug Isolation • www.cs.wisc.edu/liblit

22. Thank You