Quantitative Guidance for Architectural Design
14.4.2 Quantitative Guidance for Architectural Design
One of the many problems faced by software engineers during the design process is
a general lack of quantitative methods for assessing the quality of proposed designs. The ATAM approach discussed in Section 14.4.1 is representative of a useful but unde- niably qualitative approach to design analysis.
Work in the area of quantitative analysis of architectural design is still in its formative stages. Asada and his colleagues [ASA96] suggest a number of pseudo- quantitative techniques that can be used to complement the ATAM approach as a method for the analysis of architectural design quality.
Asada proposes a number of simple models that assist a designer in determining the degree to which a particular architecture meets predefined “goodness” criteria.
CHAPTER 14
ARCHITECTURAL DESIGN
These criteria, sometimes called design dimensions, often encompass the quality attri- butes defined in the last section: reliability, performance, security, maintainability, flexibility, testability, portability, reusability, and interoperability, among others.
The first model, called spectrum analysis, assesses an architectural design on a “goodness” spectrum from the best to worst possible designs. Once the software architecture has been proposed, it is assessed by assigning a “score” to each of its design dimensions. These dimension scores are summed to determine the total score,
S, of the design as a whole. Worst-case scores 4 are then assigned to a hypothetical design, and a total score, S w , for the worst case architecture is computed. A best-case score, S b , is computed for an optimal design. 5 We then calculate a spectrum index, I s , using the equation
w “A doctor can bury his )/(S b w
mistakes, but an The spectrum index indicates the degree to which a proposed architecture approaches architect can only
an optimal system within the spectrum of reasonable choices for a design. advise his clients to
plant vines.” If modifications are made to the proposed design or if an entirely new design is
Frank Lloyd Wright
proposed, the spectrum indices for both may be compared and an improvement index,
I mp , may be computed:
I mp =I s1
s2
This provides a designer with a relative indication of the improvement associated with architectural changes or a new proposed architecture. If I mp is positive, then we can conclude that system 1 has been improved relative to system 2.
Design selection analysis is another model that requires a set of design dimensions to be defined. The proposed architecture is then assessed to determine the number of design dimensions that it achieves when compared to an ideal (best-case) system. For example, if a proposed architecture would achieve excellent component reuse, and this dimension is required for an idea system, the reusability dimension has been achieved. If the proposed architecture has weak security and strong security is required, that design dimension has not been achieved.
We calculate a design selection index, d, as
d = (N s /N a where N s is the number of design dimensions achieved by a proposed architecture and
N a is the total number of dimensions in the design space. The higher the design selec- tion index, the more closely the proposed architecture approaches an ideal system. Contribution analysis “identifies the reasons that one set of design choices gets
a lower score than another” [ASA96]. Recalling our discussion of quality function deployment (QFD) in Chapter 11, value analysis is conducted to determine the
4 The design must still be applicable to the problem at hand, even if it is not a particularly good solution. 5 The design might be optimal, but constraints, costs, or other factors will not allow it to be built.
PA R T T H R E E C O N V E N T I O N A L M E T H O D S F O R S O F T WA R E E N G I N E E R I N G
relative priority of requirements determined during function deployment, infor- mation deployment, and task deployment. A set of “realization mechanisms” (fea- tures of the architecture) are identified. All customer requirements (determined using QFD) are listed and a cross-reference matrix is created. The cells of the matrix indicate the relative strength of the relationship (on a numeric scale of 1 to 10) between a realization mechanism and a requirement for each alternative architecture. This is sometimes called a quantified design space (QDS). The QDS is relatively easy to implement as a spreadsheet model and can be used to iso- late why one set of design choices gets a lower score than another.
Parts
» The Concurrent Development Model
» SUMMARY Software engineering is a discipline that integrates process, methods, and tools for
» PEOPLE In a study published by the IEEE [CUR88], the engineering vice presidents of three
» THE PROCESS The generic phases that characterize the software process—definition, development,
» THE PROJECT In order to manage a successful software project, we must understand what can go
» METRICS IN THE PROCESS AND PROJECT DOMAINS
» Extended Function Point Metrics
» METRICS FOR SOFTWARE QUALITY
» INTEGRATING METRICS WITHIN THE SOFTWARE PROCESS
» METRICS FOR SMALL ORGANIZATIONS
» ESTABLISHING A SOFTWARE METRICS PROGRAM
» Obtaining Information Necessary for Scope
» An Example of LOC-Based Estimation
» QUALITY CONCEPTS 1 It has been said that no two snowflakes are alike. Certainly when we watch snow
» SUMMARY Software quality assurance is an umbrella activity that is applied at each step in the
» R diagram 1.4 <part-of> data model; data model <part-of> design specification;
» SYSTEM MODELING Every computer-based system can be modeled as an information transform using an
» Facilitated Application Specification Techniques
» Data Objects, Attributes, and Relationships
» Entity/Relationship Diagrams
» Hatley and Pirbhai Extensions
» Creating an Entity/Relationship Diagram
» SUMMARY Design is the technical kernel of software engineering. During design, progressive
» Data Modeling, Data Structures, Databases, and the Data Warehouse
» Data Design at the Component Level
» A Brief Taxonomy of Styles and Patterns
» Quantitative Guidance for Architectural Design
» Isolate the transform center by specifying incoming and outgoing
» SUMMARY Software architecture provides a holistic view of the system to be built. It depicts the
» The User Interface Design Process
» Defining Interface Objects and Actions
» D E S I G N E VA L U AT I O N
» Testing for Real-Time Systems
» Organizing for Software Testing
» Criteria for Completion of Testing
» The Transition to a Quantitative View
» The Attributes of Effective Software Metrics
» Architectural Design Metrics
» Component-Level Design Metrics
» SUMMARY Software metrics provide a quantitative way to assess the quality of internal product
» Encapsulation, Inheritance, and Polymorphism
» Identifying Classes and Objects
» The Common Process Framework for OO
» OO Project Metrics and Estimation
» Event Identification with Use-Cases
» SUMMARY Object-oriented analysis methods enable a software engineer to model a problem by
» Partitioning the Analysis Model
» Designing Algorithms and Data Structures
» Program Components and Interfaces
» SUMMARY Object-oriented design translates the OOA model of the real world into an
» Testing Surface Structure and Deep Structure
» Deficiencies of Less Formal Approaches 1
» What Makes Cleanroom Different?
» Design Refinement and Verification
» SUMMARY Cleanroom software engineering is a formal approach to software development that
» Structural Modeling and Structure Points
» Describing Reusable Components
» SUMMARY Component-based software engineering offers inherent benefits in software quality,
» Guidelines for Distributing Application Subsystems
» Middleware and Object Request Broker Architectures
» An Overview of a Design Approach
» Consider expert Web developer will create a complete design, but time and cost can be appropriate
» A Software Reengineering Process Model
» Reverse Engineering to Understand Data
» Forward Engineering for Client/Server Architectures
» SUMMARY Reengineering occurs at two different levels of abstraction. At the business level,
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