Rsse12.ppt
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This document presents a recommendation system for design patterns in software development. The system uses a knowledge base of design patterns and a Goal, Question, Metric methodology to ask users a series of weighted questions to determine the most suitable design pattern for their needs. An experiment was conducted with 8 users to evaluate the system. The system was able to correctly recommend a design pattern 50% of the time and was found to require fewer questions than similar existing systems. Future work will focus on expanding the knowledge base and further evaluating the system.
![Recommendation
System for Design
Patterns in
Software
Development
Outline
Introduction
Introduction
Design Patterns and Recommendation Systems
Design Patterns?
◮
Motivating Scenario
Design Patterns and
Recommendation Systems
“Descriptions of communicating objects and classes that
are customized to solve a general design problem in a
particular context.” [Gamma et al.]
◮
Related Work
Methodology
Ingredient: Knowledge Base
◮
Ingredient: GQM
◮
Process Summary
Increased reusability, improved maintainability and
comprehensibility
Increasing number of DPs → Better quality
Inappropriate use → Complexity
Primary Level
Experiment
User Session
Recommendation Systems
Summary
Comparison
◮
Conclusion
◮
5 / 21
Recommendation systems → Information filtering
systems
Collaborative, content-based filtering (primary level)
and Hybrid (secondary level)](https://image.slidesharecdn.com/rsse12-131014234916-phpapp01/85/Rsse12-ppt-6-320.jpg)
![Recommendation
System for Design
Patterns in
Software
Development
Related Work
ReBuilder [1]
Outline
◮
Introduction
Motivating Scenario
Design Patterns and
Recommendation Systems
◮
◮
Related Work
Methodology
Ingredient: Knowledge Base
Case-based reasoning approach, cases described with
class diagrams
Such diagrams are not always available
Human and machine readable pattern format
ESSDP [2]
Ingredient: GQM
Process Summary
◮
Primary Level
◮
Experiment
User Session
◮
Summary
Uses an interactive session with the designer
Uses a knowledge base
Requires too many questions to choose a pattern
Comparison
Conclusion
Recommender System [3]
◮
◮
◮
8 / 21
Uses textual descriptions of patterns
No user feedback
Suitable for small systems](https://image.slidesharecdn.com/rsse12-131014234916-phpapp01/85/Rsse12-ppt-9-320.jpg)
![Recommendation
System for Design
Patterns in
Software
Development
Outline
Introduction
[1] P. Gomes, F. C. Pereira, P. Paiva, N. Seco, P. Carreiro, Jos´ Luis
e
Ferreira and Carlos Bento 2002. Using CBR for Automation of Software
Design Patterns. In Proceedings of the 6th European Conference on
Advances in Case-Based Reasoning, pp:534-548.
[2] R. S. David C. Kung, H. Bhambhani and G. Pancholi. An expert
system for suggesting design patterns - a methodology and a prototype.
In Software Engineering with Computational Intelligence, 2003.
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
21 / 21
[3] Y. G. Gu´h´neuc, and M. Rabih. A Simple Recommender System for
e e
Design Patterns, Proceedings of the 1st EuroPLoP Focus Group on
Pattern Repositories (2007)](https://image.slidesharecdn.com/rsse12-131014234916-phpapp01/85/Rsse12-ppt-23-320.jpg)
Rsse12.ppt
- 1. Recommendation System for Design Patterns in Software Development Outline Introduction Recommendation System for Design Patterns in Software Development Motivating Scenario Design Patterns and Recommendation Systems Related Work Methodology Ingredient: Knowledge Base e e e Francis Palma1,2 , Hadi Farzin1, Yann-Ga¨l Gu´h´neuc1 , Naouel Moha2 Ingredient: GQM Process Summary Primary Level Experiment User Session 1 2 ´ Ecole Polytechnique de Montr´al, Canada e Universit´ du Qu´bec ` Montr´al, Canada e e a e Summary Comparison Conclusion 4 June 2012 Pattern Trace Identification, Detection, and Enhancement in Java SOftware Cost-effective Change and Evolution Research Lab
- 2. Recommendation System for Design Patterns in Software Development Outline Table of Contents Introduction Introduction Motivating Scenario Design Patterns and Recommendation Systems Related Work Related Work Methodology Ingredient: Knowledge Base Ingredient: GQM Methodology Process Summary Primary Level Experiment User Session Experiment Summary Comparison Conclusion 2 / 21 Conclusion
- 3. Recommendation System for Design Patterns in Software Development Outline Table of Contents Introduction Introduction Motivating Scenario Design Patterns and Recommendation Systems Related Work Related Work Methodology Ingredient: Knowledge Base Ingredient: GQM Methodology Process Summary Primary Level Experiment User Session Experiment Summary Comparison Conclusion 3 / 21 Conclusion
- 4. Recommendation System for Design Patterns in Software Development Introduction Motivating Scenario First Scenario (Assumption 1) Outline Not reusable Introduction Motivating Scenario Expensive maintenance life Design Patterns and Recommendation Systems Poor performance/antipatterns Related Work Methodology Ingredient: Knowledge Base Ingredient: GQM Process Summary Primary Level Experiment User Session Summary Comparison Conclusion 4 / 21 Designer Developer Produced System Hard for comprehension Low maintainability Hard for evolution
- 5. Recommendation System for Design Patterns in Software Development Introduction Motivating Scenario First Scenario (Assumption 1) Outline Not reusable Introduction Motivating Scenario Expensive maintenance life Design Patterns and Recommendation Systems Poor performance/antipatterns Related Work Designer Developer Produced System Methodology Ingredient: Knowledge Base Hard for comprehension Low maintainability Hard for evolution Ingredient: GQM Process Summary Primary Level Experiment User Session Second Scenario (Assumption 2) Recommended Design Pattern Summary Comparison Reusable in a new problem Low cost maintenance Conclusion Good performance, no/less antipatterns Designer 4 / 21 Developer Produced System Easy for comprehension High maintainability Easy for evolution
- 6. Recommendation System for Design Patterns in Software Development Outline Introduction Introduction Design Patterns and Recommendation Systems Design Patterns? ◮ Motivating Scenario Design Patterns and Recommendation Systems “Descriptions of communicating objects and classes that are customized to solve a general design problem in a particular context.” [Gamma et al.] ◮ Related Work Methodology Ingredient: Knowledge Base ◮ Ingredient: GQM ◮ Process Summary Increased reusability, improved maintainability and comprehensibility Increasing number of DPs → Better quality Inappropriate use → Complexity Primary Level Experiment User Session Recommendation Systems Summary Comparison ◮ Conclusion ◮ 5 / 21 Recommendation systems → Information filtering systems Collaborative, content-based filtering (primary level) and Hybrid (secondary level)
- 7. Recommendation System for Design Patterns in Software Development Introduction Outline Introduction Our Goal Motivating Scenario Design Patterns and Recommendation Systems Related Work ◮ ◮ Methodology Ingredient: Knowledge Base The purpose of our work is to propose a Design Pattern Recommender (DPR) system Help designers by minimizing their effort to choose design patterns Ingredient: GQM Process Summary Primary Level Experiment ◮ Our solution is two-fold ◮ User Session Summary Comparison Conclusion 6 / 21 ◮ 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)
- 8. Recommendation System for Design Patterns in Software Development Outline Table of Contents Introduction Introduction Motivating Scenario Design Patterns and Recommendation Systems Related Work Related Work Methodology Ingredient: Knowledge Base Ingredient: GQM Methodology Process Summary Primary Level Experiment User Session Experiment Summary Comparison Conclusion 7 / 21 Conclusion
- 9. Recommendation System for Design Patterns in Software Development Related Work ReBuilder [1] Outline ◮ Introduction Motivating Scenario Design Patterns and Recommendation Systems ◮ ◮ Related Work Methodology Ingredient: Knowledge Base Case-based reasoning approach, cases described with class diagrams Such diagrams are not always available Human and machine readable pattern format ESSDP [2] Ingredient: GQM Process Summary ◮ Primary Level ◮ Experiment User Session ◮ Summary Uses an interactive session with the designer Uses a knowledge base Requires too many questions to choose a pattern Comparison Conclusion Recommender System [3] ◮ ◮ ◮ 8 / 21 Uses textual descriptions of patterns No user feedback Suitable for small systems
- 10. Recommendation System for Design Patterns in Software Development Outline Table of Contents Introduction Introduction Motivating Scenario Design Patterns and Recommendation Systems Related Work Related Work Methodology Ingredient: Knowledge Base Ingredient: GQM Methodology Process Summary Primary Level Experiment User Session Experiment Summary Comparison Conclusion 9 / 21 Conclusion
- 11. Recommendation System for Design Patterns in Software Development Outline Methodology Ingredient: Knowledge Base ◮ 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 10 / 21 ◮ Root of XML is a design pattern category (e.g., Creational) Child nodes are design patterns (e.g., Adapter)
- 12. Recommendation System for Design Patterns in Software Development Methodology Ingredient: GQM ◮ Outline ◮ Introduction Motivating Scenario Design Patterns and Recommendation Systems Related Work ◮ 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 Methodology Ingredient: Knowledge Base Ingredient: GQM Process Summary Primary Level Experiment User Session Summary Comparison Conclusion n Pattern Name Tot Weight =∀Applicability i =1 where, i = j & i ≥ 1, j ≥ 1 11 / 21 n Weight Pattern Name i Yes Score + Weight Pattern Name j No Score j =1
- 13. Recommendation System for Design Patterns in Software Development Methodology Process Summary Introduction Motivating Scenario Process Output Pattern Knowledge Base Questionnaire using GQM model Recommended design pattern User Knowledge (Experience) Application of weighting scheme Input Outline Level 1 (Primary) Design Patterns and Recommendation Systems Related Work Scoring and ranking Methodology Ingredient: Knowledge Base Ingredient: GQM Process Summary Primary Level Experiment User Session Level 2* (Secondary) Level 1 Inputs Refactoring package design Refactored system * packages + Initial designs Summary Comparison Conclusion 12 / 21 Secondary Level Recommendation: Detail methodological overview and implementation as future works.
- 14. Recommendation System for Design Patterns in Software Development Methodology Primary Level 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 ◮ 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 13 / 21
- 15. Recommendation System for Design Patterns in Software Development Outline Table of Contents Introduction Introduction Motivating Scenario Design Patterns and Recommendation Systems Related Work Related Work Methodology Ingredient: Knowledge Base Ingredient: GQM Methodology Process Summary Primary Level Experiment User Session Experiment Summary Comparison Conclusion 14 / 21 Conclusion
- 16. Recommendation System for Design Patterns in Software Development Outline Introduction Experiment Context ◮ Motivating Scenario Design Patterns and Recommendation Systems ◮ Related Work ◮ Methodology Ingredient: Knowledge Base Ingredient: GQM ◮ Process Summary 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 Primary Level Experiment User Session Summary Comparison Conclusion 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) 15 / 21
- 17. 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 16 / 21 Experiment User Session Questions Response 1. Do you need to use several yes existing subclasses? 2. Do you want to create a reusable yes class? 3. Do you want to use existing class? yes 4. Do you want to perform no operations on objects? 5. Do you want to avoid polluting yes classes with new operations? 6. Do you want to define new no operations over the structure? 7. Do you want to add no responsibilities to individual objects dynamically without affecting other? 8. Do you want to use class for no responsibilities that can be withdrawn? 9. Is the extension by subclassing is no impractical for your problem? 10. Do you want your clients to be able to ignore different compositions of objects and individual objects? 11. Do you want to represent yes part-whole hierarchies of objects? Total weight given by the designer Weight 8 Adapter 8 Visitor - Decorator - 8 8 - - 9 4 9 4 9 - 9 4 7 - 7 - 6 6 - - 7 7 7 - 9 9 9 - 8 8 8 - 0 0 0 0 7 - - - 71 59 40 13
- 18. Recommendation System for Design Patterns in Software Development Experiment Summary Outline Introduction Summary of eight users’ response on DPR: Motivating Scenario Design Patterns and Recommendation Systems Related Work Methodology Ingredient: Knowledge Base Ingredient: GQM Process Summary Primary Level Experiment Subject 1 2 3 4 5 6 7 8 User Session Summary Comparison Conclusion 17 / 21 Summary OO-Level medium beginner advanced medium advanced advanced medium advanced DP-Level beginner beginner medium beginner medium medium low beginner Questions 11 11 10 11 11 11 11 11 Tot.Weight ≥51 ≥51 ≤50 ≥51 ≤50 ≤50 ≤50 ≤50 Pattern Adapter Visitor Adapter both Adapter Visitor Visitor Visitor beginner 12.5% medium 37.5% advanced 50% low 12.5% beginner 50% medium 37.5% Questions≤5 0% Questions≥6 100% ≤50 62.5% ≥51 37.5% succeed 50 failed 50
- 19. Recommendation System for Design Patterns in Software Development Outline Experiment Comparison - DPR has less number of questions than ESSDP Approach Use of Textual Desc. Use of Ranking Weighting Scheme Knowledge Base User Session Relevance Score Certainity≥50% Pattern Details Shown Readable Pattern Format Runtime Reasoning Introduction DPR # # ESSDP # # ReBuilder - # # - # Recommerder System # # # - - # 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 18 / 21
- 20. Recommendation System for Design Patterns in Software Development Outline Table of Contents Introduction Introduction Motivating Scenario Design Patterns and Recommendation Systems Related Work Related Work Methodology Ingredient: Knowledge Base Ingredient: GQM Methodology Process Summary Primary Level Experiment User Session Experiment Summary Comparison Conclusion 19 / 21 Conclusion
- 21. Recommendation System for Design Patterns in Software Development Conclusion Conclusion Outline ◮ Introduction Motivating Scenario An interactive DPR prototype for suggesting design patterns ◮ Design Patterns and Recommendation Systems ◮ Related Work ◮ Methodology ◮ Ingredient: Knowledge Base Ingredient: GQM Process Summary Primary Level 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 less number of questions Experiment User Session Summary Future Work Comparison ◮ Conclusion ◮ ◮ 20 / 21 All 23 design patterns identified by Gamma et al., and more A complete interactive tool for both primary and secondary level More empirical studies
- 22. Recommendation System for Design Patterns in Software Development Thank You... 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 21 / 21 ◮ Questions...?
- 23. Recommendation System for Design Patterns in Software Development Outline Introduction [1] P. Gomes, F. C. Pereira, P. Paiva, N. Seco, P. Carreiro, Jos´ Luis e Ferreira and Carlos Bento 2002. Using CBR for Automation of Software Design Patterns. In Proceedings of the 6th European Conference on Advances in Case-Based Reasoning, pp:534-548. [2] R. S. David C. Kung, H. Bhambhani and G. Pancholi. An expert system for suggesting design patterns - a methodology and a prototype. In Software Engineering with Computational Intelligence, 2003. 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 21 / 21 [3] Y. G. Gu´h´neuc, and M. Rabih. A Simple Recommender System for e e Design Patterns, Proceedings of the 1st EuroPLoP Focus Group on Pattern Repositories (2007)