1 Towards an Automated Approach for Quality Improvement in OO Design Dr. Radu Marinescu Timişoara,...

Timişoara, 12.02.2003 1

Towards an Automated Approach for Quality Improvement in OO Design

Dr. Radu Marinescu

Towards an Automatic Approach for Quality

Improvement in Object-Oriented Design

Dr. Radu Marinescu

Timişoara, 12.02.2003 2


Dr. Radu Marinescu

Problem Statement

Numerous large-scale OO systems with signs of "rotting design" monolithic, inflexible, fragile, etc.

Discarding these systems is not an option ! high business value and large scale reuse and maintenance necessary

Design Flaws – an invariant issue in software time pressure during development permanent change of requirements

How to correlate external signs of poor quality andthe occurrence of concrete structural design flaws?

Timişoara, 12.02.2003 3


Dr. Radu Marinescu

Research Goal

Develop methods, techniques and tools that provide

a proper mapping between external quality attributes and the internal, structural characteristics of

object-oriented design.

Central focus is to support the process of quality assessment and improvement

for existing object-oriented systems

Timişoara, 12.02.2003 4


Dr. Radu Marinescu

Design Flaws ...

Exclusive Focus on Structural Flaws Design Fragments

i.e. methods, classes, modules (subsystems)

Need criteria for high-quality design design rules, principles and heuristics etc. also negative rules (e.g. "bad-smells")

… are structural characteristics of design

fragments

that express deviations from a given set

of criteria

typifying a high-quality design.

Timişoara, 12.02.2003 5


Dr. Radu Marinescu

Detection of Design Problems

Problem DetectionThe process of identifying the parts of a software system affected by a particular design flaw

It‘s not easy! manual and empirical

time-expensive and non-scalable

hard to quantify design rules and principles....

"Measuring" the Designmap source-code entities to numerical values

used as quality indicators

Idea: Use metrics to detect design problems!

Timişoara, 12.02.2003 6


Dr. Radu Marinescu

Problems with Software Measurement

Definitions of MetricsMapping attributes of a software product to numeric values [Fent97]

Imprecise, confusing, or conflicting definitions

Interpretation ModelsInterpretation level is too fine-grained to lead to design decisions

metrics values are like symptomsindicate an abnormality, but can’t indicate the causereduces the relevance of measurement results

There is a large gap between what we do measure and what we should measure!

Define mechanism for higher-level interpretation of metrics!

Timişoara, 12.02.2003 7


Dr. Radu Marinescu

The measurable expression of a rule, by which

design fragments that are conformant to the rule

can be identified in the source-code

Detection Strategy

Generic mean for defining metrics-based design rules use metrics together! Based on mechanisms of filtering and composition

Timişoara, 12.02.2003 8


Dr. Radu Marinescu

Metricsmeasure internal characteristics

entity value pairs

Composition Operatorsarticulate the composition of a detection rule

i.e. compose metrics in a rule

Three operators used: and , or , butnotin

Filtering Mechanism

statistical functions that return a subset of a data-set

Semantical Filters (e.g. HigherThan or BottomValues)

Statistical Filters (e.g. BoxPlots)

Anatomy of a Detection Strategy

Timişoara, 12.02.2003 9


Dr. Radu Marinescu

Quantified Design Flaws

Around 20 design flaws quantified as DS

Different abstraction levels method to omission of

patterns

Different literature sources

Relevant design flaws

Timişoara, 12.02.2003 10


Dr. Radu Marinescu

Sources(Java, C++) Meta-Model

parsing

usingMetrics

Detection Strategy (*.sod)

Definitions ofStatistical

Outliers

1 .. n

1 .. m

executing with PRODEOOS

List of Candidates

manual inspection

Process of Design Inspection

Timişoara, 12.02.2003 11


Dr. Radu Marinescu

The Unified Meta-Model

Design information needed in the DS i.e used by the metrics

Declarations classes, variables and methods

Inheritance relations Cross-referencing information

Variable accesses Method invocations

Contains information about packages for C++ the directory structure neccessary for the strategies at the

subsystem level

For Java and C++ TableGen and MeMoJ-Tables

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Dr. Radu Marinescu

What did we gain so far …

Detection Strategy proper mechanism for higher-level interpretation of measurements

Methodology for quantifying design-related rules

Quantified violations of design principles, rules and heuristics around 20 strategies for design flaws

from several literature sources

different abstraction levels from method to subsystem level

Build bridge between quality attributes and design problems Prove that the approach is scalable and accurate

… and what is left?

Timişoara, 12.02.2003 13


Dr. Radu Marinescu

Design principles and rules are implicit Hard to construct

A Classical Quality Model

Metrics are too fine-grained Hard to interpret

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Dr. Radu Marinescu

Factor-Strategy Quality Model

Lack ofBridge

Data Classes

God Classes

Int.Seg Principle

WMC

TCC

CIW

NOAM

AUF

NOPA

COC

AOFD

NOD

LR

Principles, rules, heuristicsquantified in Detection Strategies

Qualitydecomposed in Factors

communicates with

Timişoara, 12.02.2003 15


Dr. Radu Marinescu

The Case-Study

A Re-engineered Case-Study two versions of the an industrial business application second version re-engineered for maintainability purposes

Relevance of the Case-Study Size (~100KLOC) proper to evaluate scalability of approach Before-After reengineering scenario evaluate accuracy of DS Clear reengineering goal evaluate relevance of FS models

Size Characteristics

Timişoara, 12.02.2003 16


Dr. Radu Marinescu

Automatic Evaluation Method

Assumption 1 All major design problems in SV1 were eliminated during the

reengineering process not present in SV2

Assumption 2 Maintainability level in SV2 is higher (better) than in SV1

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Dr. Radu Marinescu

Automatic Evaluation of Strategies — Results

Accuracy Rate: between 50% and 81% Average Accuracy Rate: 64.5 % Average Number of Suspects: ~ 15% of entities reported suspect

Timişoara, 12.02.2003 18


Dr. Radu Marinescu

Evaluation of FS Quality Model

Defined a Factor-Strategy quality model for maintainability

Evaluation mechanisms Score = nr. of suspects Qualifier = “grade”

1-10 scale based on Score

Compared results between the two versions based on Assumption 2

expected improvement in SV2

Timişoara, 12.02.2003 19


Dr. Radu Marinescu

Why is the FS Model Better ?

See the problems not the numbers! problems expressed in terms of design rules that are violated interpretation is much easier

Easier to improve the quality of the design understand the causes of problems easier to correlate with “correction strategies”

Timişoara, 12.02.2003 20


Dr. Radu Marinescu

Summary A mechanism for quantifying design-related rules

the “Detection Strategy” concept

Suite of detection strategies for finding design flaws quantification of well-known design flaws and…”smells”

Described a novel concept of quality model based on detection strategies the bridge between qualitative and quantitative statements

Strong tool support for the entire approach high degree of automatization and scalability

Concrete evaluation of the concepts, methods, techniques

Timişoara, 12.02.2003 21


Dr. Radu Marinescu

Refinement The issue of threshold values [Diploma Thesis in progress]

define a tuning-machine

Unify means of expression [Master Thesis in progress] SAIL language

Applicability Bridge the gap between automated problem detection and

problem correction [PhD in progress] Integrate techniques in the development process

Migration Adapt the approach to emerging technologies (e.g. EJB) …and programming paradigms (e.g. AOP)

Refinement

Applicability

Migration

Perspectives

Timişoara, 12.02.2003 22


Dr. Radu Marinescu

Thank you!

1 Towards an Automated Approach for Quality Improvement in OO Design Dr. Radu Marinescu Timişoara,...

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