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−caseScenarios

SourceCode

UserInput

Combined Trace

Generation of Execution Traces

T1

T3T2

Combination of Execution Traces

Interactive Visualization

SequenceDiagram

8

Trace Generation and Combination

• Generating traces from a scenario– Determination of execution variants – Code Instrumentation

• Method body, loop block, conditional block

– Example1 _, PanelDraw [21668571], _, StartDraw [T1M1], _

2 PanelDraw [21668571], Figure [3916193], StartDraw [T1M1], Figure [T1M2], _

…

9 PanelDraw [21668571], Circle [17282414], StartDraw [T1M1], Circle [T1M9], <%(State.getFiguretype()==MODE_CERCLE)%>

…

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• www.math-cs.gordon.edu/local/courses/cs211/ATMExample/

– 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