Hassen Grati, Houari Sahraoui, Pierre Poulin DIRO, Université de Montréal Extracting Sequence Diagrams from Execution Traces using Interactive Visualization

2 Example of Design Diagram

3 Corresponding Automated- RE Diagram

4 Presentation Agenda Context and motivation Overview Trace generation and combination Sequence diagram extraction Evaluation

5 Context and Motivation Reverse engineering of analysis and design models –Comprehension –Migration –Maintenance Mature work on static model extraction –Integrated in commercial tools –Still few challenges Relationship recovery and scope definition

6 Context and Motivation Difficulty to extract behavioral models –Static analysis Dynamic language features –Dynamic analysis Implementation details Specificity to an execution trace Proposal –Semi-automated reverse engineering with interactive visualization

7 Overview Objective and working hypothesis –Extraction of sequence diagrams for the purpose of redocumentation for existing use case scenarios Use−case Scenarios Source Code User Input Combined Trace Generation of Execution Traces T1 T3 T2 Combination of Execution Traces Interactive Visualization Sequence Diagram

8 Trace Generation and Combination Generating traces from a scenario –Determination of execution variants –Code Instrumentation Method body, loop block, conditional block –Example  _, PanelDraw [ ], _, StartDraw [T1M1], _  PanelDraw [ ], Figure [ ], StartDraw [T1M1], Figure [T1M2], _ …  PanelDraw [ ], Circle [ ], StartDraw [T1M1], Circle [T1M9], …

9 Trace Generation and Combination Combining traces –Recursive alignment of call-tree nodes –For each pair of aligned methods, enclosed sequence of method calls are compared –Sequence alignment using the Smith- Waterman algorithm

10 Trace Generation and Combination Combining traces –Example

11 Trace Generation and Combination Combining traces –Example

12 Sequence Diagram Extraction Extraction = set of successive interaction cycles Each cycle –Automated basic transformations –User interactions using interaction views

13 Sequence Diagram Extraction Automated basic transformations –Messages = method calls –Participants = call sender and receiver –opt/alt/loop boxes = conditional/loop stacks –Return messages extracted from the tree structure

14 Sequence diagram Extraction User interactions using interaction views –Global view Messages

15 Sequence Diagram Extraction User interactions using interaction views –Global view Placement

16 Sequence Diagram Extraction User interactions using interaction views –Global view Placement

17 Sequence Diagram Extraction User interactions using interaction views –Diagram view

18 Sequence Diagram Extraction User interactions using interaction views –Interactions Navigation

19 Sequence Diagram Extraction User interactions using interaction views –Interactions Renaming objects and messages Removing objects and messages –Tree pruning –Node removal Recommending fragment merges –Finding recommendations during trace alignments –Based on polymorphism

20 Sequence Diagram Extraction User interactions using interaction views Recommending fragment merges

21 Evaluation Setting –ATM simulation system 24 Java classes –Three use-case scenarios Session, Deposit, and Withdraw –Three sequence diagrams per scenario Design diagram (DD) Diagram extracted automatically (ATD) [Briand et al., 03] Diagram extracted using interactive visualization (IVD)

22 Evaluation Results –Participants

23 Evaluation Results –Messages

24 Conclusions Semi-automated approach –Dynamic analysis –Interactive visualization –Recommendations Evaluation on a benchmark –Concise diagrams with better precision and less implementation details –Acceptable interaction time

25 Limitations & Future Work Improve scalability of the global view Improve the recommendation module –Incremental learning Apply IV to the reverse engineering of other dynamic models –State diagram –Activity diagram

26 Thank you

27 Additional Slides

28 Session Scenario

29 Session Scenario

30 Session Scenario