extracting sequence diagrams from execution traces using interactive visualization

Hassen Grati, Houari Sahraoui, Pierre Poulin

DIRO, Université de Montréal

Extracting Sequence Diagrams from Execution Traces using Interactive Visualization

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Example of Design Diagram

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Corresponding Automated- RE Diagram

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Presentation Agenda

• Context and motivation

• Overview

• Trace generation and combination

• Sequence diagram extraction

• Evaluation

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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

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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

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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

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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)%>

…

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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

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Trace Generation and Combination

• Combining traces– Example

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Trace Generation and Combination

• Combining traces– Example

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Sequence Diagram Extraction

• Extraction = set of successive interaction cycles

• Each cycle – Automated basic transformations– User interactions using interaction views

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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

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Sequence diagram Extraction

• User interactions using interaction views– Global view

• Messages

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Sequence Diagram Extraction

• User interactions using interaction views– Global view

• Placement

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Sequence Diagram Extraction

• User interactions using interaction views– Global view

• Placement

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Sequence Diagram Extraction

• User interactions using interaction views– Diagram view

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Sequence Diagram Extraction

• User interactions using interaction views– Interactions

• Navigation

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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

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Sequence Diagram Extraction

• User interactions using interaction views• Recommending fragment merges

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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)

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Evaluation• Results

– Participants

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Evaluation• Results

– Messages

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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

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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

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Thank you

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Additional Slides

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Session Scenario

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Session Scenario

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Session Scenario