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CS5103 Software Engineering

CS5103 Software Engineering. Lecture 16 Debugging. Today’s class. Delta Debugging Motivation Algorithm In practice Statistical Debugging Tarantula Dynamic Slicing. 2. Debugging. Something we do when testing find a bug Basic Process Reproduce the bug Locate the fault Fix

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CS5103 Software Engineering

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  1. CS5103 Software Engineering Lecture 16 Debugging

  2. Today’s class Delta Debugging Motivation Algorithm In practice Statistical Debugging Tarantula Dynamic Slicing 2

  3. Debugging Something we do when testing find a bug Basic Process Reproduce the bug Locate the fault Fix Bug localization: Basic idea Reduce Suspicious Input Reduce Suspicious Code 3

  4. Debugging Sometimes the inputs is too complex… Quite common in real world (compiler, office, browser, database, OS, …) Locate the relevant inputs 4

  5. Consider Mozilla Firefox Taking html pages as inputs A large number of bugs are related to loading certain html pages Corner cases in html syntax Incompatibility between browsers Corner cases in Javascripts, css, … Error handling for incorrect html, Javascript, css, … 5

  6. How do we go from this <SELECT NAME="op sys" MULTIPLE SIZE=7> <OPTION VALUE="All">All<OPTION VALUE="Windows 3.1">Windows 3.1<OPTION VALUE="Windows 95">Windows 95<OPTION VALUE="Windows 98">Windows 98<OPTION VALUE="Windows ME">Windows ME<OPTION VALUE="Windows 2000">Windows 2000<OPTION VALUE="Windows NT">Windows NT<OPTION VALUE="Mac System 7">Mac System 7<OPTION VALUE="Mac System 7.5">Mac System 7.5<OPTION VALUE="Mac System 7.6.1">Mac System 7.6.1<OPTION VALUE="Mac System 8.0">Mac System 8.0<OPTION VALUE="Mac System 8.5">Mac System 8.5<OPTION VALUE="Mac System 8.6">Mac System 8.6<OPTION VALUE="Mac System 9.x">Mac System 9.x<OPTION VALUE="MacOS X">MacOS X<OPTION VALUE="Linux">Linux<OPTION VALUE="BSDI">BSDI<OPTION VALUE="FreeBSD">FreeBSD<OPTION VALUE="NetBSD">NetBSD<OPTION VALUE="OpenBSD">OpenBSD<OPTION VALUE="AIX">AIX<OPTION VALUE="BeOS">BeOS<OPTION VALUE="HP-UX">HPUX< OPTION VALUE="IRIX">IRIX<OPTION VALUE="Neutrino">Neutrino<OPTION VALUE="OpenVMS">OpenVMS<OPTION VALUE="OS/2">OS/2<OPTION VALUE="OSF/1">OSF/1<OPTION VALUE="Solaris">Solaris<OPTION VALUE="SunOS">SunOS<OPTION VALUE="other">other</SELECT> </td> <td align=left valign=top> <SELECT NAME="priority" MULTIPLE SIZE=7> <OPTION VALUE="--">--<OPTION VALUE="P1">P1<OPTION VALUE="P2">P2<OPTION VALUE="P3">P3<OPTION VALUE="P4">P4<OPTION VALUE="P5">P5</SELECT> </td> <td align=left valign=top> <SELECT NAME="bug severity" MULTIPLE SIZE=7> <OPTION VALUE="blocker">blocker<OPTION VALUE="critical">critical<OPTION VALUE="major">major<OPTION VALUE="normal">normal<OPTION VALUE="minor">minor<OPTION VALUE="trivial">trivial<OPTION VALUE="enhancement">enhancement< 6

  7. To this… <SELECT NAME="priority" MULTIPLE SIZE=7> 7

  8. Motivation Turning bug reports with real web pages to minimized test cases The minimized test case should still be able to reveal the bug Benefit of simplification Easy to communicate Remove duplicates Easy debugging Involve less potentially buggy code Shorter execution time 8

  9. Delta Debugging The problem definition A program exhibit an error for an input The input is a set of elements E.g., a sequence of API calls, a text file, a serialized object, … Problem: Find a smaller subset of the input that still cause the failure 9

  10. A generic algorithm How do people handle this problem? Binary search Cut the input to halves Try to reproduce the bug Iterate 10

  11. Delta Debugging Version 1 The set of elements in the bug-revealing input is I Assumptions Each subset of I is a valid input: Each Subset of I -> success / fail A single input element E causes the failure E will cause the failure in any cases (combined with any other elements) (Monotonic) 11

  12. Solution is simple Go with the binary search process Throw away half of the input elements, if the rest input elements still cause the failure 12

  13. Solution is simple Go with the binary search process Throw away half of the input elements, if the rest input elements still cause the failure A single element: we are done! 13

  14. Example 14

  15. Delta Debugging Version 1 This is just binary search: easy to automate The assumptions do not always hold Let’s look at the assumptions: (I1 U I2) = -> I1 = and I2 = or I1 = and I2 = It is interesting to see if this is not the case 15

  16. Case I: multiple failing branches What happened if I1 = and I2 = ? A subset of I1 fails and also a subset of I2 fails We can simply continue to search I1 and I2 And we find two fail-causing elements They may be due to the same bug or not 16

  17. Case II: Interference What happened if I1 = and I2 = ? This means that a subset of I1 and a subset of I2 cause the failure when they combined This is called interference 17

  18. Handling Interference The cute trick Consider I1 = and I2 = But I1 UI2 = An element D1 in I1 and an element D2 in I2 cause the failure We do binary search in I2 with I1 Split I2 to P1 and P2, try I1 U P1 and I1 UP2 Continue until you find D2, so that I1 UD2 cause the failure Then we do binary search in I1 with D2 until find D1 Return D1 U D2 18

  19. Example I: Handle interference Consider 8 input elements, of which 3 and 7 cause the failure when they applied together Configuration Result 1 2 3 4 Interference! 5 6 7 8 1 2 3 4 5 6 1 2 3 4 7 8 1 2 3 4 7 1 2 7 3 4 7 37 19

  20. Example II: Handle multiple interference Consider 8 input elements, of which 3, 5 and 7 cause the failure when they applied together Configuration Result 1 2 3 4 Interference! 5 6 7 8 1 2 3 4 5 6 1 2 3 4 7 8 Second Interference! What to do? Go on with I1 U P1! 1 2 3 4 5 6 7 1 2 3 4 57 1 2 57 3 4 57 3 57 20

  21. Delta Debugging Version 2 The set of elements in the bug-revealing input is I New Assumptions Each subset of I is a valid input A subset of input elements E causes the failure E will cause the failure in any cases (combined with any other elements) 21

  22. Delta Debugging Version 2 Algorithm Split I to I1 and I2 Case I: I1 = and I2 = Try I1 Case I: I1 = and I2 = Try I2 Case I: I1 = and I2 = try both I1 and I2 Case II: I1 = and I2 = Handle interference for I1 and I2 22

  23. Real example: GNU Compiler This input program (bug.c) causes Gcc 2.59.2 to crash when all optimitization are enabled Minimize it to debug gcc Consider each character as an element 23

  24. Real example: GNU Compiler Our delta debugging process Create the appropriate subset of bug.c Feed it to gcc Continue according to whether Gcc crashes 77 24

  25. GCC compiler example The minimized code: The test case is 1-minimal No single character can be removed Even every space is removed The function name has been changed from mult to a signle t Gcc is executed for 700+ times Input reduce to 10% of the initial input t(double z[],int n){int i,j;for(;;){i=i+j+1;z[i]=z[i]*(z[0]+0);}return z[n];} 25

  26. Another example: GDB GDB is the debugger from GNU It updates from 4.16 to 4.17 The version 4.17 no longer compatible with DDD (a GUI for GNU software development tools) 178, 000 lines of code change from 4.16 How to know which code change(s) cause the failure 26

  27. Results After a lot of work (by machine) 178KLOC change grouped to 8700 groups (commits) Use delta debugging Work it out in 470 tests It took 48 hours Doing this by hand would be a nightmare! 27

  28. Importance of input elements It is important to have good input element definition So that subset of input elements are valid for input The size of input is small Consider the examples GCC example: we use characters as elements, which is simple but not so good, if the bug happens after parser, the bug is not monotonic due to syntax errors GDB example: we group LOC to groups to reduce input size to 5% of the original size. 2 days are acceptable, what about 40 days? 28

  29. Limitations of Delta debugging Rely on the assumptions Monotonicity does not always hold Rely on good input elements, always providing valid inputs will enhance efficiency Require automatic test oracles Good for regression testing No good for development-time testing 29

  30. Statistical Debugging Delta Debugging Narrow down the input to be considered Statistical Debugging Narrow down the code to be considered 30

  31. Statistical Debugging Basic Idea Consider a number of test cases, some of which pass and some of which fail If a statement is covered mostly by failed test cases, it is highly likely to be the buggy part of the code 31

  32. Tarantula A classical tool for statistical debugging Use the following formulas Color = red + pass/(fail + pass) * (green ) Brightness = max (pass, fail) 32

  33. Tarantula: Illustration 33

  34. Context based statistical debugging Not just consider a statement Runtime Control Flow Graph Also consider connections Outcomes of branches Connections on a runtime-CFG 34

  35. Runtime Control Flow Graph 1: void replaceFirst (sx, sy) { 2: for (int i=0;i<len;i++) { 3: if (arr[i]==sx){ 4: arr[i] = sz; 5: //should break; 6: } 7: if (arr[i]==sy)){ 8: arr[i] = sz; 9: //should break; 10: } 11: } 12:} pass pass Fail 35

  36. Limitations Questions: If a statement is covered only by passed test cases, can it be the root cause of the bug found? If a statement is covered only by failed test cases, it must be the root cause of the bug found? 36

  37. Example void f(int a, int b){ if (a > 0){ //error: should be >= do something; } if (b < 0){ do something } } Test Cases: 3, 2 2, 1, 0, -1 2, 0 37

  38. Dynamic Slicing Another way to narrow down code to be considered in debugging 38

  39. Data Dependencies Data dependencies are the dependency from the usage of a variable to the definition of the variable Example: s1: x = 3; s2: if(y > 5){ s3: y = y + x; //data depend on x in s1 s4: } 39

  40. Control Dependencies Control dependencies are the dependency from the branch basic blocks to the predicate Example: s1: x = 3; s2: if(y > 5){ s3: y = y + x; //control depend on y in s2 s4: } 40

  41. Dynamic Slicing Describe dependencies among code elements If a variable has incorrect value, the bug should be in its backward dynamic slice Like runtime control flow graph A map from static slicing to the executed code 41

  42. Algorithm • A dependence edge is introduced from a load to a store if during execution, at least once, the value stored by the store is indeed read by the load (mark dependence edge) • No static analysis is needed.

  43. 11 21 31 41 51 71 81 Algorithm II Example 1: b=0 For input N=1, the trace is: 2: a=2 3: 1 <=i <=N T 4: if ((i++)%2= =1) F T F 5: a=a+1 6: b=a*2 7: z=a+b 8: print(z)

  44. Efficiency: Summary • For an execution of 130M instructions: • space requirement: reduced from 1.5GB to 94MB (I further reduced the size by a factor of 5 by designing a generic compression technique [MICRO’05]). • time requirement: reduced from >10 Mins to <30 seconds. • http://jslice.sourceforge.net/

  45. Summary of debugging Debugging is a follow-up step of testing Bug localization, and bug fixing are tasks highly depend on human intelligence Tools can help us to narrow the scope to consider Bug localization Reduce the code to be considered Delta debugging Reduce the inputs to be considered 45

  46. Tool Demos for Next Week • Turki Aljarbooa, Iram Lee, Robert McCammon, Avid Narimani, Shelly Klinzing • Himadri Sekhar Debnath, Hemanth Lokesha, Amartya Roy, Anudeep Reddy Donthiri, Deepti, Marimadaiah • Zhemou Li, Shen Chang,Alamin Hossain;, Wei wei;, Chih-Wei Yu • Pranitha Madduri, Shravya Gaddam, Sai Gandham, Anandsai ChinthamReddy • Dharunumakr Matheswaran, Kumara Sri Sai Ravi Teja Kosaraju, Kavya Putumbaka, Navya Somepalli

  47. Tool Demos for Next Week • Hemankita Perabathini, Moulika Omtri, Safwa Amir, Williams Vega • Bharadwaj Prabhala, Anjan Pradhan, Venkat Rahul Dantuluri, Narender Sorrineeda • Umadevi Samudrala, Manju Priya Hari Krishnan, Rajiv Shanmugam Madeswaran, Deepa Raveendran, Karthika Jayagopan • Alex Torres, Deepti Gupta, Joe Ybarra, Smriti Bhatt

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