Transcript Method Size Metrics

OORPT
Object-Oriented Reengineering Patterns
and Techniques
7. Problem Detection
Prof. O. Nierstrasz
OORPT — Problem Detection
Roadmap
Metrics
> Object-Oriented Metrics in Practice
> Duplicated Code
>
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.2
OORPT — Problem Detection
Roadmap
>
Metrics
— Software quality
— Analyzing trends
Object-Oriented Metrics in Practice
> Duplicated Code
>
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.3
OORPT — Problem Detection
Why Metrics in OO Reengineering (ii)?
> Assessing Software Quality
— Which components have poor quality?
(Hence could be reengineered)
— Which components have good quality?
(Hence should be reverse engineered)
 Metrics as a reengineering tool!
> Controlling the Reengineering Process
— Trend analysis: which components changed?
— Which refactorings have been applied?
 Metrics as a reverse engineering tool!
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.4
OORPT — Problem Detection
Selecting Metrics
>
Fast
— Scalable: you can’t afford log(n2) when n  1 million LOC
>
Precise
— (e.g. #methods — do you count all methods, only public ones,
also inherited ones?)
— Reliable: you want to compare apples with apples
>
Code-based
— Scalable: you want to collect metrics several times
— Reliable: you want to avoid human interpretation
>
Simple
— Complex metrics are hard to interpret
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.5
OORPT — Problem Detection
Assessing Maintainability
>
Size of the system, system entities
— Class size, method size, inheritance
— The intuition: large entities impede maintainability
>
Cohesion of the entities
— Class internals
— The intuition: changes should be local
>
Coupling between entities
— Within inheritance: coupling between class-subclass
— Outside of inheritance
— The intuition: strong coupling impedes locality of changes
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.6
OORPT — Problem Detection
Sample Size and Inheritance Metrics
Class Size Metrics
# methods (NOM)
# instance attributes (NIA, NCA)
# Sum of method size (WMC)
Inheritance Metrics
hierarchy nesting level (HNL)
# immediate children (NOC)
# inherited methods, unmodified (NMI)
# overridden methods (NMO)
Inherit
Class
BelongTo
Method Size Metrics
# invocations (NOI)
# statements (NOS)
# lines of code (LOC)
Invoke
Attribute
Method
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
Access
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OORPT — Problem Detection
Method Size
(MSG) Number of Message Sends
> (LOC) Lines of Code
> (MCX) Method complexity
>
— Total Number of Complexity / Total number of methods
— API calls= 5, Assignment = 0.5, arithmetics op = 2, messages
with params = 3....
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.8
OORPT — Problem Detection
Sample Metrics: Class Cohesion
>
(LCOM) Lack of Cohesion in Methods
— [Chidamber 94] for definition
— [Hitz 95] for critique
Ii = set of instance variables used by method Mi
let
P = { (Ii, Ij ) | Ii  Ij =  }
Q = { (Ii, Ij ) | Ii  Ij   }
if all the sets are empty, P is empty
LCOM =
|P| - |Q|
if |P|>|Q|
0
otherwise
>
>
Tight Class Cohesion (TCC)
Loose Class Cohesion (LCC)
— [Bieman 95] for definition
— Measure method cohesion across invocations
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.9
OORPT — Problem Detection
The Trouble with Coupling and
Cohesion
>
Coupling and Cohesion are intuitive notions
— Cf. “computability”
— E.g., is a library of mathematical functions “cohesive”
— E.g., is a package of classes that subclass framework classes
cohesive? Is it strongly coupled to the framework package?
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.10
OORPT — Problem Detection
Roadmap
Metrics
> Object-Oriented Metrics in Practice
>
— Detection strategies, filters and composition
— Sample detection strategies: God Class …
>
Duplicated Code
Michele Lanza and Radu Marinescu,
Object-Oriented Metrics in Practice,
Springer-Verlag, 2006
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.11
OORPT — Problem Detection
Pattern: Study the Exceptional Entities
Problem
— How can you quickly gain insight into complex software?
Solution
— Measure software entities and study the anomalous ones
Steps
— Use simple metrics
— Visualize metrics to get an overview
— Browse the code to get insight into the anomalies
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.12
OORPT — Problem Detection
System Complexity View
System Complexity View
Nodes = Classes
Edges = Inheritance Relationships
Width = Number of Attributes
Height = Number of Methods
Color = Number of Lines of Code
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
Width Metric
Height
Metric
Position
Metrics
Color
Metric
7.13
OORPT — Problem Detection
Detection strategy
>
A detection strategy is a metrics-based predicate to
identify candidate software artifacts that conform to (or
violate) a particular design rule
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.14
OORPT — Problem Detection
Filters and composition
>
A data filter is a predicate used to focus attention on a
subset of interest of a larger data set
— Statistical filters
–
I.e., top and bottom 25% are considered outliers
— Other relative thresholds
–
I.e., other percentages to identify outliers (e.g., top 10%)
— Absolute thresholds
–
>
I.e., fixed criteria, independent of the data set
A useful detection strategy can often be expressed as a
composition of data filters
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.15
OORPT — Problem Detection
God Class
>
A God Class centralizes intelligence in the system
— Impacts understandibility
— Increases system fragility
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.16
OORPT — Problem Detection
ModelFacade (ArgoUML)
453 methods
> 114 attributes
> over 3500 LOC
> all methods and all
attributes are static
>
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.17
OORPT — Problem Detection
Feature Envy
>
Methods that are more interested in data of other classes
than their own [Fowler et al. 99]
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
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OORPT — Problem Detection
ClassDiagramLayouter
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.19
OORPT — Problem Detection
Data Class
>
A Data Class provides data to other classes but little or
no functionality of its own
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.20
OORPT — Problem Detection
Data Class (2)
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
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OORPT — Problem Detection
Property
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.22
OORPT — Problem Detection
Shotgun Surgery
>
A change in an operation implies many (small) changes
to a lot of different operations and classes
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
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OORPT — Problem Detection
Project
© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.24
OORPT — Problem Detection
License
>
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© Stéphane Ducasse, Serge Demeyer, Oscar Nierstrasz
7.25