1. Dynamic Analysis and Visualizing of Data Structures in Java Programs Presented by Sokhom Pheng (Supervisor: Clark Verbrugge) McGill University February 9 th 2005

2. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 2 Outline Motivation Brief overview of *J Requirements for data structure (DS) analysis Some algorithms for analysis Issues Future works

3. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 3 Motivation Visual understanding of data structure in java programs Help understand code without looking at source code Dynamic analysis

4. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 4 Brief Overview of *J Developed by Bruno Dufour in the sable lab Java Application *J Analyzer Data Structure Analyzer *J Agent (JVMPI) trace file

5. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 5 Why isn’t *J enough for DS Analysis? JVMPI doesn’t provide all info  Missing references of objects  Missing info on actual values for primitive Important for accessing arrays  Does not track objects

6. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 6 Requirements for Data Structures Analysis Need to simulate the whole program execution  Keep track of the JVM stacks Follow JVM design (VM Spec)  Invocation stack for each thread  Stack frame for each method  Execution stack to contain operand objects  Keep track of actual values (even of primitives) for array indices

7. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 7 Represent Data Structures in Memory Object, method and class has unique ID and entity (originally implemented in *J)  ObjectEntity: ID, name, type, size, …  MethodEntity: signature, name, class entity, …  ClassEntity: name, number of methods/interfaces, … Recreate objects and their references to each other by executing bytecodes found in the trace  Eg. putfield obj1 obj2

8. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 8 Algorithm for DS Analysis Goal: identifying data structures Started with identifying “tree”, “dag” and “cycle” detected by DFS treedag cycle

9. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 9 Algorithm for DS Analysis (con’d) Other way to identify DS  Combinatorial topology Shape represented by set of equations  Reference Shape Graph (RSG) 1 Node represent memory location having similar reference patterns 1 A new Dependence Test Based on Shape Analysis for Pointer-Based Codes, Navarro, Corbera, Asenjo, Tineo, Plata, Zapata, LCPC 2004

10. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 10 RSG Example

11. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 11 Advantage over Static Analysis public class BinaryTree {... public static void main(String[] args) {... tree.left = tree.right; tree.right = new Node(...);... }... } class Node {... } Static Analysis tree dag

12. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 12 Advantage over Static Analysis (con’d) From JOlden benchmark: BiSort After 62 modifications

13. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 13 Advantage over Static Analysis (con’d) From JOlden benchmark: BiSort After 63 modifications

14. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 14 Data Gathering Issues Start up code  JVMPI doesn’t start with JVM Lack of array indices  Primitive values from I/O Native methods

15. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 15 Potential Solutions Look only at application code Ignore arrays for now

16. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 16 Analysis Problems Multiple entry points treedag cycle obj1obj2 obj3 obj5 obj4 obj6 Sol’n: Look at all entry points individually obj7 obj8

17. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 17 Analysis Problems (con’d) Garbage objects  Induce multiple entry points  Dead nodes not trivially distinguished from live ones obj1 obj2 obj3 obj4 Garbage Node

18. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 18 Sol’n for Garbage Problem Root set  Exclude garbage objects not yet deleted by garbage collector  Static fields, live variables and live methods parameters obj2 obj1 obj2 obj1

19. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 19 Example of Entry Points public class Foo { static bar = new Bar(); public static void main(String[] args) { Foo foo = new Foo(); foo.foo1(new Bar());... } public void foo1(Bar b) { Foo f = new Foo();... } } class Bar {... } Root set {bar} {bar, foo} {bar, foo, b, f} {bar}

20. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 20 DS Configuration Options Self loop  Why do they exist?  Effect: makes everything cyclic

21. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 21 DS Configuration Options (con’d) Doubly-connected DS  Effect: makes everything cyclic  Not every edge is doubly-connected

22. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 22 Gathering Other Useful Info Encode “age” of modification  How a DS evolves over time Amount of garbage being carried  “Drag” effect

23. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 23 Drag Effect From JOlden benchmark: Barnes-Hut After 58 modifications

24. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 24 Legend / Encoding ≤ 1000 byte codes ≤ 100 byte codes ≤ 10 byte codes ≤ 10000 byte codes ≤ 100000 byte codes ≤ 1000000 byte codes > 1000000 byte codes Age of node New node Cycle DAG Tree obj1 Garbage

25. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 25 Example From JOlden benchmark: Barnes-Hut After 13 modifications

26. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 26 Garbage Option Option to show garbage objects or not

27. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 27 Representing Entry Points Different shapes and colours for entry point depending on type of DS

28. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 28 Drawing Tool Dot / Graphviz  Generates snapshots

29. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 29 Drawing Issue Drawing of one graph has no relation to drawing of the next  Dot try to be optimal  Jumps all over the place

30. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 30 Drawing Issue Example

31. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 31 Possible Solutions Tom Sawyer Software (currently investigating)  Incremental drawing Hack into Dot’s source code Add “inter-frames” between snapshots

32. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 32 Small Complete Example

33. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 33 Future Works Deal with arrays and unknown info  Draw approximate graph Handle start up code / native methods Investigate other drawing tools Add other analyses  RSG from LCPC paper  Topological approach (set of equations) Calculate “drags” for garbage objects Analyze more and more complex programs

34. February 9th 2005 Dynamic Analysis and Visualizing of Data Structures in Java Programs 34 Thank You!