1. Combining Static and Dynamic Data in Code Visualization David Eng Sable Research Group, McGill University PASTE 2002 Charleston, South Carolina November 18-19, 2002

2. Presentation outline Introduction Framework overview JIL SOOT STEP JIMPLEX Future work

3. Introduction Code visualization: why and where? Program understanding. Compiler development. Visualization of an optimizable IR. Motivation: Expose both static & dynamic program attributes which are hidden in the raw IR. Design goals: Intuitive, portable, & modular.

4. Framework overview Java class files MyClass.java JVM/JVMPI (execution profile) Tools with JIL support Visualizers with JIL support JIL documents SOOT STEP static data (JIL) dynamic data (JIL) JIMPLEX (XSL/HTML) MyVisualizer (my language) DTD (d)(c)(b)(a)

5. Java Intermediate Language (JIL) XML-based representation of code. A metalanguage used to describe other languages and their characteristics. Encapsulates IRs as code objects which can be extended with both static and dynamic data.

6. JIL document structure contributing toolsruntime accessesruntime invokes name, returns, access invoke targets definitions uses name, type, accessversion, created myclass historyfields name, type parameters name, type locals statement count name labels live variables in/out flow information jimple declaration line number, label statements type, handler exceptions methods myclass extension base element legend required

7. Benefits of using XML Extensible: add or remove elements without breaking existing structure. Supported by existing parsers, APIs, software, databases, servers, etc. Portable across platforms and networks. Human readable, editable.

8. JIL Let’s take a look at an example JIL document…

9. Static vs. dynamic data Static data: Collected at compile-time Program attributes Flow information Analysis results Basis for program understanding We chose SOOT as a source of static data…

10. SOOT Java optimization framework and API. Uses intermediate languages (IRs) to perform analyses and transformations. Provides several output formats, including JIL. Jimple source (.jimple) SOOT Java source (.java) Java class (.class) JIL document (.xml) Baf, Grimp, and Jimple analysis & optimization Grimp source (.grimp) Baf source (.baf) javac

11. SOOT as a source of JIL SOOT was modified to generate Jimple as XML. The resulting XML contains general program characteristics and flow information. Static analysis results can be linked to applicable code elements.

12. SOOT elements in JIL As a source of static data: Flow information Live variable analysis Variable uses and definitions Class hierarchy analysis Variable type analysis

13. Static vs. dynamic data Dynamic data: Collected at runtime Profiling results Variable access and use counts Temporal data Basis for evaluation Especially important for OOP languages

14. STEP Toolkit for extensible profiling. Encodes and compresses trace data in a trace definition language. JIL document (.xml) STEP Java class (.class) EVolve trace format Profiling agent (JVMPI, Kaffe, SOOT) event pipe

15. STEP as a source of JIL STEP as a source of profiling data. Visualizers becomes consumers at the backend of the event pipe. STEP traces are read and converted to JIL. JIMPLEX has full control over what elements are included and in what format.

16. STEP elements in JIL As a source of runtime dynamic data: field accesses method invocations object allocations

17. Separation of data from data Static and dynamic data are generated as independent XML sources. Trace results from different profiling runs can be swapped in and out. Data sources can live on separate servers.

18. Merging XML data sources To visualize both static and dynamic elements simultaneously, the data is merged into a single source. XML can be merged on the fly using XSL.

19. Separation of data and interface Interfaces are independent of data. Can be implemented using any combination of languages or technologies. One possible interface will be presented here…

20. JIMPLEX Web-based visualization interface implemented using HTML and XSL. Uses JIL documents as data sources, allowing them to exist remotely. Runs on any machine equipped with a web browser. Portable across platforms and networks. Modular and extensible.

21. JIMPLEX interface myclass.xml (JIL document) (c) (b) (a) Server A: JIL document storage web server jimplex.xsl (XSL stylesheet) Server B: JIMPLEX server web server JIMPLEX (web page) Client 1: JIMPLEX web client JIMPLEX (web page) Client n: JIMPLEX web client … XML data HTML data XML/XSL transformation

22. Example Interface

23. JIMPLEX interface Let’s take a look at the interface…

25. Contributions JIL document format DTD specifications SOOT extensions JIL document output format STEP extensions JIL document generating backend JIMPLEX visualizer XSL stylesheets

26. Future Work: JIL Extract more runtime attributes from STEP, such as temporal data. Use XML merging to support multiple STEP streams, allowing multi-dimensional profiling. Use XML differentiation to support program and trace comparison, allowing better evaluation of optimizations.

27. Future Work: UI Any updates to JIL should be reflected in the UI (ie. multi-dimensional profiling). With the inclusion of more and more data, an application-based interface would provide better performance. Profiling and other dynamic data are more suited towards a graphical representation.

28. Links Java Intermediate Language (JIL): http://www.sable.mcgill.ca/jil/ JIL papers, resources, and the JIMPLEX visualizer. SOOT: http://www.sable.mcgill.ca/soot/ SOOT papers, documentation, and downloads. STEP: http://www.sable.mcgill.ca/step/ STEP papers, more to come.