detection strategies metrics-based rules for detecting design flaws
TRANSCRIPT
Introduction Problem Demand Solution Implementation Evaluation Summary
Detection StrategiesMetrics-Based Rules forDetecting Design Flaws
M.... N.....1
1Universita della Svizzera Italiana, Switzerland
Software Design and Evolution, WS 2009
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Author
Dr. Radu Marinescu
Associate Professor -Department of Computer Science and Engineering"Politechnica" University at TimisoaraAuthor of "Object-Oriented Metrics in Practice"
Ph.D defense
Mircea Lungu, Today, 17.30, A21, Red Building
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Author
Dr. Radu Marinescu
Associate Professor -Department of Computer Science and Engineering"Politechnica" University at TimisoaraAuthor of "Object-Oriented Metrics in Practice"
Ph.D defense
Mircea Lungu, Today, 17.30, A21, Red Building
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Outline
1 Introduction
2 Problem
3 Demand
4 Solution
5 Implementation
6 Evaluation
7 Summary
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Metrics
Metrics
ambiguous definitionsnoiserelevance
Interpretation
experience basedno modelshowing symptoms not a disease
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Metrics
Metrics
ambiguous definitionsnoiserelevance
Interpretation
experience basedno modelshowing symptoms not a disease
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Metrics
Metrics
ambiguous definitionsnoiserelevance
Interpretation
experience basedno modelshowing symptoms not a disease
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Strategy
Strategy
"A detection strategy is the quantifiable expression of a rule bywhich design fragments that are conforming to that rule can bedetected in the source code"
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Filters
Semantical
threshold valuedirection
For example:Absolute: HigherThan, LowerThanRelative: TopValues, BottomValues
Statistical
direction
For example: UpperQuantile, BelowMedian
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Strategy
Choosing an appropriate filter1 Absolute semantical filter2 Relative semantical filter3 Semantical filter with percentile values4 Statistical filter
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Composition
Logical Operators
and, or, butnot
Metric1
Metric2
Metric3
Filtered
Set1
Filtered
Set2
Filtered
Set3
filter
filter
filter
Composition Rules Final
Results
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Metrics
"God Class" syndrome.Weighted Method Count (WMC)Tight Class Cohesion (TCC)Access to Foreign Data (ATFD)
(WMC(C), TopValues(25%))∧ (1)
(ATFD(C), HigherThan(1))∧ (2)
(TCC(C), BottomValues(25%)) (3)
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Process
Sources
(Java, C++)
Meta-Modelparsing
Metrics
Detection
Detection
Strategy Flaw List
Manual inspection
using
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Filter tuning
1 Experience and Literature2 Reference Samples (Tuning Machine)3 Evolution Analysis
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Case-study
Version 193 KLOC, 18 Packages, 152 Classes, 1284 MethodsVersion 2116 KLOC, 29 Packages, 387 Classes, 3446 Methods
Evaluation methods
Automatic Classification (differential between the versions)Manual Investigation (of the Version 1)
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Summary
Results
Automatic Classification accuracy over 50% with averageover 67%.Manual Inspection method resulted in Accuracy of 87%.
Conclusion
Method is very promising !
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Summary
Results
Automatic Classification accuracy over 50% with averageover 67%.Manual Inspection method resulted in Accuracy of 87%.
Conclusion
Method is very promising !
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Related Work
Quantification of Design Principles and RulesUsing Correlations of Metrics for Design Inspections
Nowak Faculty of Informatics
Detection Strategies
Introduction Problem Demand Solution Implementation Evaluation Summary
Discussion
Questions and Discussion.
Nowak Faculty of Informatics
Detection Strategies