Recommendation System for Design Patterns in Software Development
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Recommendation System for Design Patterns in Software Development Outline Introduction Motivating Scenario Design Patterns and Recommendation Systems Related Work Methodology Ingredient: Knowledge Base Ingredient: GQM Process Summary Primary Level Experiment User Session Summary Comparison Conclusion Recommendation System for Design Patterns in Software Development Francis Palma 1,2 , Hadi Farzin 1 , Yann-Ga¨ el Gu´ eh´ eneuc 1 , Naouel Moha 2 1 ´ Ecole Polytechnique de Montr´ eal, Canada 2 Universit´ e du Qu´ ebec ` a Montr´ eal, Canada 4 June 2012 Pattern Trace Identification, Detection, and Enhancement in Java SOftware Cost-effective Change and Evolution Research Lab
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Transcript of Recommendation System for Design Patterns in Software Development
RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
Recommendation System for Design Patternsin Software Development
Francis Palma1,2, Hadi Farzin1, Yann-Gael Gueheneuc1,Naouel Moha2
1 Ecole Polytechnique de Montreal, Canada2 Universite du Quebec a Montreal, Canada
4 June 2012
Pattern Trace Identification, Detection, and Enhancement in JavaSOftware Cost-effective Change and Evolution Research Lab
RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
Table of Contents
2 / 21
RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
Table of Contents
3 / 21
RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
IntroductionMotivating Scenario
First Scenario (Assumption 1)
Designer Developer Produced System
Not reusable
Expensive maintenance life
Poor performance/antipatterns
Hard for comprehension
Low maintainability
Hard for evolution
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RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
IntroductionMotivating Scenario
First Scenario (Assumption 1)
Designer Developer Produced System
Not reusable
Expensive maintenance life
Poor performance/antipatterns
Hard for comprehension
Low maintainability
Hard for evolution
Second Scenario (Assumption 2)
Recommended Design Pattern
Reusable in a new problem
Low cost maintenance
Designer Developer Produced System
Good performance, no/less antipatterns
Easy for comprehension
High maintainability
Easy for evolution
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RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
IntroductionDesign Patterns and Recommendation Systems
Design Patterns?
◮ “Descriptions of communicating objects and classes thatare customized to solve a general design problem in aparticular context.” [Gamma et al.]
◮ Increased reusability, improved maintainability andcomprehensibility
◮ Increasing number of DPs → Better quality◮ Inappropriate use → Complexity
Recommendation Systems
◮ Recommendation systems → Information filteringsystems
◮ Collaborative, content-based filtering (primary level)and Hybrid (secondary level)
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RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
Introduction
Our Goal◮ The purpose of our work is to propose a Design
Pattern Recommender (DPR) system◮ Help designers by minimizing their effort to choose
design patterns
◮ Our solution is two-fold◮ Recommend a design pattern for a context
(primary-level)◮ Recommend one(more) design pattern(s) for a system
given its initial design (secondary-level, future work)
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RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
Table of Contents
7 / 21
RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
Related Work
ReBuilder [1]
◮ Case-based reasoning approach, cases described withclass diagrams
◮ Such diagrams are not always available◮ Human and machine readable pattern format
ESSDP [2]
◮ Uses an interactive session with the designer◮ Uses a knowledge base◮ Requires too many questions to choose a pattern
Recommender System [3]
◮ Uses textual descriptions of patterns◮ No user feedback◮ Suitable for small systems
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RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
Table of Contents
9 / 21
RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
MethodologyIngredient: Knowledge Base
◮ Root of XML is a design pattern category (e.g.,Creational)
◮ Child nodes are design patterns (e.g., Adapter)
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RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
MethodologyIngredient: GQM
◮ Goal: Pattern names◮ Questions: 2-layered questions, i.e., conditions &
sub-conditions◮ Metric: Apply a weighting scheme
◮ Answer ∈ {‘yes’, ‘no’ or ‘do not know’}, with a weight◮ 1 ≤ weights ≤ 9
Pattern NameTot Weight=∀Applicability
(
n∑
i=1
Weight(
Pattern Name i Yes Score
)
+
n∑
j=1
Weight(
Pattern Namej No Score
)
)
where, i 6= j & i ≥ 1, j ≥ 1
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RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
MethodologyProcess Summary
Input
Level 1
(Primary)
Level 2
(Secondary)
Pattern Knowledge
Base
User Knowledge
(Experience)
Initial designs
Process Output
Questionnaire using
GQM model
Application of
weighting scheme
Scoring and ranking
Refactoring package
design
Recommended design
pattern
Refactored system
packagesLevel 1 Inputs
+
* *
Secondary Level Recommendation: Detail methodologicaloverview and implementation as future works.
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RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
MethodologyPrimary Level
◮ DPR is a selection type of expert system◮ We use a ranking based selection approach◮ Suggestion segment includes interactive session, calculate weights,
and assign ranks
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RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
Table of Contents
14 / 21
RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
Experiment
Context◮ A develops a program to display details about its
product in the Console using an Iterator◮ A outsource Product back-end system to B◮ B gives back a system that return products as an
Enumeration◮ Enumeration is a problem for A’s system
Characteristics◮ 8 users as Subjects (6 Grad. Students, 1 Professional
Developer, 1 IT Analyst)◮ 3 design patterns (Adapter, Visitor, Decorator)◮ 3 other approaches for comparison (ESSDP, ReBuilder, Recommender
System)
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RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
ExperimentUser Session
Questions Response Weight Adapter Visitor Decorator
1. Do you need to use severalexisting subclasses?
yes 8 8 - -
2. Do you want to create a reusableclass?
yes 8 8 - -
3. Do you want to use existing class? yes 9 9 9 94. Do you want to performoperations on objects?
no 4 4 - 4
5. Do you want to avoid pollutingclasses with new operations?
yes 7 - 7 -
6. Do you want to define newoperations over the structure?
no 6 6 - -
7. Do you want to addresponsibilities to individual objectsdynamically without affecting other?
no 7 7 7 -
8. Do you want to use class forresponsibilities that can bewithdrawn?
no 9 9 9 -
9. Is the extension by subclassing isimpractical for your problem?
no 8 8 8 -
10. Do you want your clients to beable to ignore different compositionsof objects and individual objects?
- 0 0 0 0
11. Do you want to representpart-whole hierarchies of objects?
yes 7 - - -
Total weight given by the designer 71 59 40 13
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RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
ExperimentSummary
Summary of eight users’ response on DPR:
Subject OO-Level DP-Level Questions Tot.Weight Pattern1 medium beginner 11 ≥51 Adapter2 beginner beginner 11 ≥51 Visitor3 advanced medium 10 ≤50 Adapter4 medium beginner 11 ≥51 both5 advanced medium 11 ≤50 Adapter6 advanced medium 11 ≤50 Visitor7 medium low 11 ≤50 Visitor8 advanced beginner 11 ≤50 Visitor
beginner low Questions≤5 ≤50 succeed12.5% 12.5% 0% 62.5% 50
Summary medium beginner Questions≥6 ≥51 failed37.5% 50% 100% 37.5% 50
advanced medium50% 37.5%
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RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
ExperimentComparison
- DPR has less number of questions than ESSDP
Approach
Use
ofTextualDesc.
Use
ofRanking
WeightingSch
eme
Know
ledgeBase
UserSession
Relevance
Score
Certainity≥
50%
PatternDetailsShow
n
Readable
PatternFormat
RuntimeReasoning
DPR ✓ ✓ ✓ ✓ ✓ ✗ ✓ ✓ ✓ ✗
ESSDP ✗ ✓ ✗ ✓ ✓ ✓ ✓ ✓ ✓ ✓
ReBuilder - ✓ ✗ ✓ ✓ ✗ - ✗ ✓ ✓
Recommerder ✓ ✓ ✗ ✗ ✗ ✓ - ✓ - ✗System
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RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
Table of Contents
19 / 21
RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
Conclusion
Conclusion◮ An interactive DPR prototype for suggesting design
patterns◮ GQM approach◮ KB for pattern details and relative information
◮ A sample interactive session with the designer◮ Preliminary evaluation of DPR by 8 subjects shows that
DPR is relatively effective than ESSDP in terms of lessnumber of questions
Future Work◮ All 23 design patterns identified by Gamma et al., and
more◮ A complete interactive tool for both primary and
secondary level◮ More empirical studies
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RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
Thank You...◮ Questions...?
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RecommendationSystem for Design
Patterns inSoftware
Development
Outline
Introduction
Motivating Scenario
Design Patterns andRecommendation Systems
Related Work
Methodology
Ingredient: Knowledge Base
Ingredient: GQM
Process Summary
Primary Level
Experiment
User Session
Summary
Comparison
Conclusion
[1] P. Gomes, F. C. Pereira, P. Paiva, N. Seco, P. Carreiro, Jose LuisFerreira and Carlos Bento 2002. Using CBR for Automation of SoftwareDesign Patterns. In Proceedings of the 6th European Conference onAdvances in Case-Based Reasoning, pp:534-548.
[2] R. S. David C. Kung, H. Bhambhani and G. Pancholi. An expertsystem for suggesting design patterns - a methodology and a prototype.In Software Engineering with Computational Intelligence, 2003.
[3] Y. G. Gueheneuc, and M. Rabih. A Simple Recommender System forDesign Patterns, Proceedings of the 1st EuroPLoP Focus Group onPattern Repositories (2007)
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