Copyright 2003 National ICT Australia Limited 1 Mining Patterns to Support Software Architecture...

Copyright 2003 National ICT Australia Limited1

Mining Patterns to Support Software Architecture Evaluation

4th Working IEEE/IFIP Conference on Software ArchitectureOslo, Norway 12-15th June

Liming Zhu, Muhammad Ali Babar, Ross Jeffery

School of Computer Science, University of New South WalesEmpirical Software Engineering Group, National ICT Australia


Presentation Outline

Background: Architecture Evaluation and Architecture

Patterns

Current Problems and Research Goals

Extracting Scenarios and Tactics from Patterns

A Case Study – Architectural-level Performance

Evaluation on “Stock-Online” system

Conclusion


Background

Scenario-based architecture evaluation (ALMA, ATAM, PASA etc.)

Architecture patterns More and more large and complex software systems have

been developed using architectural patterns

Concrete Scenarios for Quality Attribute

Quality Attribute Reasoning Framework

Independent Parameters

Dependant Parameters

Evaluation results

Evaluation Method


Research Goals

Problems: Useful information in patterns is not used effectively and efficiently in

architecture evaluation• Scenario generation• Reasoning framework selection and calibrating

Patterns as “best practices” are not validated

Research Goals: Useful information in pattern can be extracted and re-organized to

improve architecture evaluation• To improve scenario quality • To help to select and calibrate quality reasoning framework

By following the above method, an architecture evaluation result on a pattern-based architecture can qualify as one of the many pieces of evidence for validating the pattern. (Evidence-based Software Engineering)


Architecture Pattern

Problem Solution Claimed

Qualitative Quality

Consequences

General Scenarios

Architectural Tactics

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Concrete Scenarios for Quality Attribute

Quality Attribute Reasoning Framework

Independent Parameters

Dependant Parameters

Evaluation results

Evaluation Method


Extracting Scenarios

A six elements framework [Bass, Clements and Kazman 03] Stimulus, Response, Source of stimulus,

Environment, Stimulated Artifact, Response measure

A general scenario extracted from J2EE Data Mapper or DTO (Data Transfer Object) pattern

A periodic data structure change request (stimulus) from stakeholders (source of the stimulus) arrives when data use case changes after the system is deployed (environment). The system (stimulated artifact) has to be modifiable (response) according to the data structure change request within certain scope under certain time and maintenance cost (response measure).


Extracting Tactics

Extracting Architectural Tactics: Providing information on independent parameters and reasoning framework

Existing preliminary tactic framework: [Bass, Bachmann and Klein 03] [Bosch 04]

Example: Tactics from DTOFactory J2EE pattern Tactic 1: Managing demands by managing event rate

• Independent parameters: number of requests Tactic 2: Localizing expected modification by limiting change

options, isolating expected changes and maintaining semantic coherence

• Independent parameters: number of primary components affected


A Case Study

System: Stock-Online System [Gorton 00]Typical online stock trading systemAlternative design decisions

Architecture-level Performance prediction (QNM-based) [Liu, Fekete and Gorton 04]

Pattern: Read Mostly (RM) Pattern Platform: J2EE


A Case Study

General performance

model

Architecture specific model

Calibrating

Performance profile (for

architecture tactics)

Behaviour Description

Target application

Application specific model

Calibrating

Populating

Benchmark suite

Benchmarking

Architecture Pattern

Problem (General

Scenarios)

Solution(Architecture

Tactics)

Qualitative quality

consequencesPopulating

Validating


Mining the RM Pattern

Extracting scenarios from RM pattern General Scenario: A large number of client (stimulus source) requests,

mostly read-only requests (stimulus) arrive at the server at normal condition (environment), the server (artifact) needs to process the requests (response) within certain response time (response measure)

• Concrete Scenario: A large number of stock transaction related requests (get/set/create accout/stockholders/stockitems/stockTx, 83.7% of them, read-only requests) arrive at the server at normal condition, the server needs to process the request within certain response time.

Extracting tactics from RM Pattern Managing demands by reducing event rate

• Independent parameter: number of requests on resource intensive activities This will shorten the total response time for a large number of read-only

requests


Selecting and Calibrating Reasoning Framework

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R1: number of requests related to T1: service time to synchronize with database

R2: number of requests related to T2: service time to access entity bean

p: read only requests ratio hr: cache hit ratio [Yan et. al 04]

• Introducing p as one of the independent parameters in reasoning framework

• helping to make design decisions

• validating “claimed” pattern benefits


Architecture Evaluation

A benchmark application is built with the RM pattern Concrete scenarios used in the measurement are instances of

general scenarios extracted from the RM pattern The independent parameter manipulated by the tactic is

modelled in the reasoning framework Reasoning framework parameters are solved and populated

through experimental measurements on the benchmark application

Evaluation results (prediction) for the target application are in favour of RM pattern and can be explained by the read requests ratio - p

Evaluation results are validated against target application


Conclusion

Extracting information from pattern to improve architecture evaluation

Accumulating evidence to validate pattern Deriving concrete scenario from extracted general scenario Modelling pattern tactics (independent parameters a

pattern is trying to manipulate) in reasoning framework

General scenariosArchitecture tactics

Concrete scenariosQuality reasoning framework

Architectural Patterns

Copyright 2003 National ICT Australia Limited 1 Mining Patterns to Support Software Architecture...

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