Data Design at the Component Level
14.2.2 Data Design at the Component Level
Data design at the component level focuses on the representation of data structures that are directly accessed by one or more software components. Wasserman [WAS80] has proposed a set of principles that may be used to specify and design such data structures. In actuality, the design of data begins during the creation of the analysis model. Recalling that requirements analysis and design often overlap, we consider the following set of principles [WAS80] for data specification:
? 1. The systematic analysis principles applied to function and behavior should also
What
principles are
be applied to data. We spend much time and effort deriving, reviewing, and
applicable to data
specifying functional requirements and preliminary design. Representations
design?
of data flow and content should also be developed and reviewed, data
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
objects should be identified, alternative data organizations should be consid- ered, and the impact of data modeling on software design should be evalu- ated. For example, specification of a multiringed linked list may nicely satisfy data requirements but lead to an unwieldy software design. An alternative data organization may lead to better results.
2. All data structures and the operations to be performed on each should be identi- fied. The design of an efficient data structure must take the operations to be performed on the data structure into account (e.g., see [AHO83]). For exam- ple, consider a data structure made up of a set of diverse data elements. The data structure is to be manipulated in a number of major software functions. Upon evaluation of the operations performed on the data structure, an abstract data type is defined for use in subsequent software design. Specifica- tion of the abstract data type may simplify software design considerably.
3. A data dictionary should be established and used to define both data and pro- gram design. The concept of a data dictionary has been introduced in Chap- ter 12. A data dictionary explicitly represents the relationships among data objects and the constraints on the elements of a data structure. Algorithms that must take advantage of specific relationships can be more easily defined if a dictionarylike data specification exists.
4. Low-level data design decisions should be deferred until late in the design process. A process of stepwise refinement may be used for the design of data. That is, overall data organization may be defined during requirements analy- sis, refined during data design work, and specified in detail during component- level design. The top-down approach to data design provides benefits that are analogous to a top-down approach to software design—major structural attributes are designed and evaluated first so that the architecture of the data may be established.
5. The representation of data structure should be known only to those modules that must make direct use of the data contained within the structure. The concept of information hiding and the related concept of coupling (Chapter 13) provide important insight into the quality of a software design. This principle alludes to the importance of these concepts as well as "the importance of separating the logical view of a data object from its physical view" [WAS80].
6. A library of useful data structures and the operations that may be applied to them should be developed. Data structures and operations should be viewed as a resource for software design. Data structures can be designed for reusability. A library of data structure templates (abstract data types) can reduce both specification and design effort for data.
7. A software design and programming language should support the specification and realization of abstract data types. The implementation of a sophisticated
CHAPTER 14
ARCHITECTURAL DESIGN
data structure can be made exceedingly difficult if no means for direct specifi- cation of the structure exists in the programming language chosen for imple- mentation.
These principles form a basis for a component-level data design approach that can
be integrated into both the analysis and design activities.
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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