ICPC08b.ppt
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The document discusses techniques for locating concerns in source code. It introduces the concept of a concern as anything that affects program implementation, like features or requirements. Locating concerns is difficult because the relationship between concerns and code elements is usually undocumented. The document proposes an approach called Cerberus that combines three concern location techniques - information retrieval, execution tracing, and prune dependency analysis - to more effectively determine this relationship. Future work is discussed to improve the techniques, especially prune dependency analysis and Cerberus' accuracy.
![Prune dependency rule [ACOM’07]
□ Code is prune dependent on concern if
□ Pruning the concern requires removing or
altering the code
□ Must alter code that depends on removed
code
□ Prevent compile errors
□ Eliminate “dead code”
□ Easy to determine/approximate
Marc Eaddy ICPC 2008 11](https://image.slidesharecdn.com/icpc08b-ppt-130410194843-phpapp01/85/ICPC08b-ppt-11-320.jpg)
![Vector space model [Salton]
□ Parse code and reqs doc to extract term vectors
□ NativeArray.js_join() method “native,” “array,” “join”
□ “Array.join” requirement “array,” “join”
□ Our contributions
□ Expand abbreviations
□ numconns number, connections, numberconnections
□ Index fields
□ Weigh terms (tf · idf)
□ Term frequency (tf)
□ Inverse document frequency (idf)
□ Similarity = cosine distance between document and
query vectors
Marc Eaddy ICPC 2008 14](https://image.slidesharecdn.com/icpc08b-ppt-130410194843-phpapp01/85/ICPC08b-ppt-14-320.jpg)
ICPC08b.ppt
- 2. Motivation □ >50% of maintenance time spent trying to understand the program Marc Eaddy ICPC 2008 2
- 3. Motivation □ >50% of maintenance time spent trying to understand the program □ Where are the features, reqs, etc. in the code? Marc Eaddy ICPC 2008 3
- 4. Motivation □ >50% of maintenance time spent trying to understand the program □ Where are the features, reqs, etc. in the code? □ What is this code for? Marc Eaddy ICPC 2008 4
- 5. Motivation □ >50% of maintenance time spent trying to understand the program □ Where are the features, reqs, etc. in the code? □ What is this code for? □ Why is it hard to understand and change the program? Marc Eaddy ICPC 2008 5
- 6. What is a “concern?” Anything that affects the implementation of a program □ Feature, requirement, design pattern, coding idiom, etc. □ Raison d'être for code □ Every line of code exists to satisfy some concern Marc Eaddy ICPC 2008 6
- 7. Concern location problem Concern–code relationship hard to obtain Program Concerns Elements Marc Eaddy ICPC 2008 7
- 8. Concern location problem Concern–code relationship hard to obtain Program Concerns Elements □ Concern–code relationship undocumented Marc Eaddy ICPC 2008 8
- 9. Concern location problem Concern–code relationship hard to obtain Program Concerns Elements □ Concern–code relationship undocumented □ Reverse engineer the relationship □ (but, which one?) Marc Eaddy ICPC 2008 9
- 10. Software pruning □ Remove code that supports certain features, reqs, etc. □ Reduce program’s footprint □ Support different platforms □ Simplify program Marc Eaddy ICPC 2008 10
- 11. Prune dependency rule [ACOM’07] □ Code is prune dependent on concern if □ Pruning the concern requires removing or altering the code □ Must alter code that depends on removed code □ Prevent compile errors □ Eliminate “dead code” □ Easy to determine/approximate Marc Eaddy ICPC 2008 11
- 12. Automated concern location Concern–code relationship predicted by an “expert” □ Experts mine clues in code, docs, etc. □ Existing techniques use 1 or 2 experts only □ Our solution: Cerberus 1. Information retrieval 2. Execution tracing 3. Prune dependency analysis Marc Eaddy ICPC 2008 12
- 13. IR-based concern location □ i.e., Google for code □ Program entities are documents □ Requirements are queries Requirement Source “Array.join” Code Id_joi join n js_join( ) Marc Eaddy ICPC 2008 13
- 14. Vector space model [Salton] □ Parse code and reqs doc to extract term vectors □ NativeArray.js_join() method “native,” “array,” “join” □ “Array.join” requirement “array,” “join” □ Our contributions □ Expand abbreviations □ numconns number, connections, numberconnections □ Index fields □ Weigh terms (tf · idf) □ Term frequency (tf) □ Inverse document frequency (idf) □ Similarity = cosine distance between document and query vectors Marc Eaddy ICPC 2008 14
- 15. Tracing-based concern location □ Observe elements activated when concern is exercised □ Unit tests for each concern □ e.g., find elements uniquely activated by a concern Marc Eaddy ICPC 2008 15
- 16. Tracing-based concern location □ Observe elements activated when concern is exercised □ Unit tests for each concern □ e.g., find elements uniquely activated by a concern Unit Test Call for “Array.join” Graph var a = new Array(1, 2); if (a.join(',') == "1,2") { print "Test passed"; } Marc Eaddy else { 16 print "Test js_construct js_joi failed"; n
- 17. Tracing-based concern location □ Observe elements activated when concern is exercised □ Unit tests for each concern □ e.g., find elements uniquely activated by a concern Unit Test Call for “Array.join” Graph var a = new Array(1, 2); if (a.join(',') == "1,2") { print "Test passed"; } Marc Eaddy else { 17 print "Test js_construct js_joi failed"; n
- 18. Prune dependency analysis □ Infer relevant elements based on structural relationship to relevant element e (seed) □ Assumes we already have some seeds □ Prune dependency analysis □ Determines prune dependency rule using program analysis □ Find references to e □ Find superclasses and subclasses of e Marc Eaddy ICPC 2008 18
- 19. PDA example Source Code Program Dependency Graph interface A { inherits public void foo(); A } C B public class B implements A { public void foo() { ... } refs public void bar() { ... } contains contains contains } public class C { contains public static void main() { B b = new B(); b.bar(); calls } main bar foo foo Marc Eaddy ICPC 2008 19
- 20. PDA example Source Code Program Dependency Graph interface A { inherits public void foo(); A } C B public class B implements A { public void foo() { ... } refs public void bar() { ... } contains contains contains } public class C { contains public static void main() { B b = new B(); b.bar(); calls } main bar foo foo Marc Eaddy ICPC 2008 20
- 21. PDA example Source Code Program Dependency Graph interface A { inherits public void foo(); A } C B public class B implements A { public void foo() { ... } refs public void bar() { ... } contains contains contains } public class C { contains public static void main() { B b = new B(); b.bar(); calls } main bar foo foo Marc Eaddy ICPC 2008 21
- 22. PDA example Source Code Program Dependency Graph interface A { public void foo(); inherits C B A } public class B implements A { public void foo() { ... } refs public void bar() { ... } contains contains contains } public class C { contains public static void main() { B b = new B(); b.bar(); calls } main bar foo foo Marc Eaddy ICPC 2008 22
- 23. PDA example Source Code Program Dependency Graph interface A { inherits public void foo(); A } C B public class B implements A { public void foo() { ... } refs public void bar() { ... } contains contains contains } public class C { contains public static void main() { B b = new B(); b.bar(); calls } main bar foo foo Marc Eaddy ICPC 2008 23
- 24. Cerberus Marc Eaddy ICPC 2008 24
- 25. Cerberus ≈ PROMESIR + SNIAFL Marc Eaddy ICPC 2008 25
- 26. Cerberus effectiveness Cerberus Marc Eaddy 26
- 27. Ignoring “No results found” Cerberus Marc Eaddy 27
- 28. Future work □ Improve PDA □ Reimplemented using Soot and Polyglot □ Generalize using prune dependency predicates □ Improve precision using points-to analysis □ Improve accuracy using □ Dominator heuristic □ Variable liveness analysis □ Improve accuracy of Cerberus □ Combine experts using matrix linear regression Marc Eaddy ICPC 2008 28
- 29. Cerberus contributions □ Effectively combined 3 concern location techniques □ PDA boosts performance of Source Code interface A { public void foo(); Program Dependency Graph C B A other techniques } public class B implements A { public void foo() { ... } refs public void bar() { ... } contains contains contains } public class C { contains public static void main() { B b = new B(); b.bar(); calls } main bar foo foo Marc Eaddy ICPC 2008 29
- 30. Questions? Marc Eaddy Columbia University eaddy@cs.columbia.edu Marc Eaddy ICPC 2008 30