Analysis Modeling (Chapter 12)

Analysis Model

• First technical representation of a system
• Combination of text and diagrams to represent software requirements (data, function, and behavior)
• Analysis models make it easier to uncover requirement inconsistencies and omissions.
• Two types of analysis modeling:
• structured analysis
• object-oriented analysis
• Data modeling: entity-relationship diagrams define data objects, attributes, and relationships.
• Functional modeling:  data flow diagrams show how data are transformed inside the system.
• Behavioral modeling:  state transition diagrams show the impact of events.

Structured Analysis (DeMarco)

• Analysis products must be highly maintainable, especially the software requirements specification.
• Problems of size must be dealt with using an effective method of partitioning.
• Graphics should be used whenever possible.
• Differentiate between the logical (essential) and physical (implementation) considerations.
• Find something to help with requirements partitioning and document the partitioning before specification.
• Devise a way to track and evaluate user interfaces.
• Devise tools that describe logic and policy better than narrative text.

Analysis Model Objectives

• Describe what the customer requires.
• Establish a basis for the creation of a software design.
• Devise a set of requirements that can be validated once the software is built.

Analysis Model Elements

• Data dictionary - contains the descriptions of all data objects consumed or produced by the software
• Entity relationship diagram (ERD) - depicts relationships between data objects
• Data flow diagram (DFD) - provides an indication of how data are transformed as they move through the system; also depicts functions that transform the data flow (a function is represented in a DFD using a process specification or PSPEC)
• State transition diagram (STD) - indicates how the system behaves as a consequence of external events, states are used to represent behavior modes. Arcs are labeled with the events triggering the transitions from one state to another (control information is contained in control specification or CSPEC)

• A statement of scope can be acquired from:
• the FAST working document
• A set of use-cases
• the statement of scope must be “parsed” to extract data, function and behavioral domain information
• Statement of Scope
• Relatively brief description of the system to be built
• indicates data that are input and output and basic functionality
• indicates conditional processing (at a high level)
• implies certain constraints and limitations
• Identifying Objectsand Operations
• define “objects” by underlining all nouns in the written statement of scope
• producers/consumers of data
• places where data are stored
• “composite” data items
• define “operations” by double underlining all active verbs
• processes relevant to the application
• data transformations
• consider other “services” that will be required by the objects

Data Modeling Elements (ERD)

• Questions Answered
• What are the primary data objects to be processed by the system?
• What is the composition of each data object and what attributes describe the object?
• Where do the the objects currently reside?
• What are the relationships between each object and other objects?
• What are the relationships between the objects and the processes that transform them?
• Components
• Data object - any person, organization, device, or software product that produces or consumes information, e.g.
• report
• event
• place
• structure
• Attributes - name a data object instance, describe its characteristics, or make reference to another data object

• Relationships - indicate the manner in which data objects are connected to one another

Cardinality and Modality (ERD)

• Cardinality - in data modeling, cardinality specifies how the number of occurrences of one object are related to the number of occurrences of another object (1:1, 1:N, M:N)
• Modality - zero (0) for an optional object relationship and one (1) for a mandatory relationship

Entity/Relationship Diagrams

• Primary components identified for the ERD:
• data objects
• attributes
• relationships
• type indicators
• Primary purpose:  represent data objects and their relationships
• Iconography:
• Data objects are represented by a labeled rectangle
• Relationships are indicated with a labeled line connecting objects (Some variations: the connecting line contains a diamond that is labeled with the relationship)
• Connections between data objects and relationships are established using a variety of special symbols that indicate cardinality and modality

Expanded ERD

ERD representation of data object type hierarchies

Associative data object - represents the associativity between objects

 

Creating Entity Relationship Diagrams

1. During requirements elicitation, customers are asked to list the "things" that the application or business process addresses. These "things" evolve into a list of input and output data objects as well as external entities that produce or consume information.
2. Taking the objects one at a time, the analyst and customer define whether or not a connection (unnamed at this stage) exists between the data object and other objects.
3. Wherever a connection exists, the analyst and the customer create one or more object/relationship pairs.
4. For each object/relationship pair, cardinality and modality are explored.
5. Steps 2 through 4 are continued iteratively until all object/relationships have been defined. It is common to discover omissions as this process continues. New objects and relationships will invariably be added as the number of iterations grows.
6. The attributes of each entity are defined.
7. An entity relationship diagram is formalized and reviewed.
8. Steps 1 through 7 are repeated until data modeling is complete.

Functional Modeling and Information Flow (DFD)

• Shows the relationships of external entities, process or transforms, data items, and data stores
• DFD's cannot show procedural detail (e.g. conditionals or loops) only the flow of data through the software
• Refinement from one DFD level to the next should follow approximately a 1:5 ratio (this ratio will reduce as the refinement proceeds)
• To model real-time systems, structured analysis notation must be available for time continuous data and event processing

Data Flow Diagrams (DFDs)

• Graphical representation that depicts information flow and the transforms that are applied as data move from input to output
• Represents a system or software at any level of abstraction
• Partitioned into levels that represent increasing information flow and functional detail - satisfies the second operational analysis principle (i.e., creating a functional model)
• Iconography
• Circle (aka bubble) : a process or transform  applied to data and changes it in some way
• Arrow : one or more data items (data objects)
• Double line: data store — stored information that is used by the software
• Shadowed Rectangle : data source or sink - where data begins or ends

• Creating Data Flow Diagram
• Level 0 data flow diagram should depict the system as a single bubble
• Primary input and output should be carefully noted
• Refinement should begin by consolidating candidate processes, data objects, and data stores to be represented at the next level
• Label all arrows with meaningful names
• Information flow must be maintained from one level to level
• Refine one bubble at a time
• Write a PSPEC (a "mini-spec" written using English or another natural language or a program design language) for each bubble in the final DFD
• Extensions for Real-Time Systems
• Conventional data flow notation does not make a distinction between discrete data and time-continuous data
• Ward and Mellor Extensions - mechanism for representing time-continuous data flow
• Information flow is gathered or produced on a time-continuous basis
• Control information is passed throughout the system and associated control processing
• Multiple instances of the same transformation are sometimes encountered in multitasking situations
• Systems have states and a mechanism causes transition between states
• Initial Iconography
• double headed arrow is used to represent time-continuous flow
• single headed arrow is used to indicate discrete data flow

• Revised Iconography
• Data flow is represented using a solid arrow
• Control flow is represented using a dashed or shaded arrow
• Control process - handles only control flows - represented as a dashed bubble

• Hatley and Pirbhai Extensions
• Focus on the representation and specification of the control-oriented aspects of the software
• Dashed arrow used to represent control or event flow
• Dashed and solid notation be represented separately - control flow diagram
• Control flow diagram CFD - shows control flow, rather than data flow
• Notational reference (a solid bar) to a control specification (CSPEC) is used
• CSPEC used to indicate:
• how the software behaves when an event or control signal is sensed
• which processes are invoked as a consequence of the occurrence of the event
• A process specification is used to describe the inner workings of a process represented in a flow diagram
• Hatley and Pirbhai's model of a real-time system
• Data flow diagrams used to represent data and the processes that manipulate it.
• Control flow diagrams show how events flow among processes and illustrate those external events that cause various processes to be activated

• Creating Control Flow Diagrams
• Begin by stripping all the data flow arrows form the DFD
• Events (solid arrows) and control items (dashed arrows) are added to the diagram
• Add a window to the CSPEC (contains an STD that is a sequential specification of the behavior) for each bubble in the final CFD

Behavioral Modeling (STD)

• State transition diagrams represent the system states and events that trigger state transitions
• state—a set of observable circum-stances that characterizes the behavior of a system at a given time
• state transition—the movement from one state to another
• event—an occurrence that causes the system to exhibit some predictable form of behavior
• action—process that occurs as a consequence of making a transition
• STD's indicate actions (e.g. process activation) taken as a consequence of a particular event
• A state is any observable mode of behavior
• Hatley and Pirbhai control flow diagrams (CFD) can also be used for behavioral modeling
• Iconography
• Rectangles represent system states
• Arrows represent transitions between states
• Each arrow is labeled with a ruled expression
• Top value - the event(s) that cause the transition to occur
• Bottom value - the action that occurs as a consequence of the event

State transition diagram for photocopier software

• Building a Behavioral Model
• make a list of the different states of a system (How does the system behave?)
• indicate how the system makes a transition from one state to another (How does the system change state?)
• indicate event
• indicate action
• draw a state transition diagram

Data Dictionary Contents

• Name - primary name for each data or control item, data store, or external entity
• Alias - alternate names for each data object
• Where-used/how-used - a listing of processes that use the data or control item and how it is used (e.g. input to process, output from process, as a store, as an external entity)
• Content description - notation for representing content
• Supplementary information - other data type information, preset values, restrictions, limitations, etc.

Notation enables representation of composite data in one of the three fundamental ways that it can be constructed:

1. As a sequence of data items.
2. As a selection from among a set of data items.
3. As a repeated grouping of data items. Each data item entry that is represented as part of a sequence, selection, or repetition may itself be another composite data item that needs further refinement within the dictionary.

Design Concepts and Principles (Chapter 12)

• Software requirements model is transformed into design models that describe the details of the data structures, system architecture, interface, and components
• Each design product is reviewed for quality before moving to the next phase of software development

Design Specification Models

• Data design - created by transforming the analysis information model (data dictionary and ERD) into data structures required to implement the software
• Architectural design - defines the relationships among the major structural elements of the software, it is derived from the system specification, the analysis model, and the subsystem interactions defined in the analysis model (DFD)
• Interface design - describes how the software elements communicate with each other, with other systems, and with human users; the data flow and control flow diagrams provide much the necessary information
• Component-level design - created by transforming the structural elements defined by the software architecture into procedural descriptions of software components using information obtained from the PSPEC, CSPEC, and STD

The Design Process

• Good Design Characteristics
• The design must implement all of the explicit requirements contained in the analysis model, and it must accommodate all of the implicit requirements desired by the customer.
• The design must be a readable, understandable guide for those who generate code and for those who test and subsequently support the software.
• The design should provide a complete picture of the software, addressing the data, functional, and behavioral domains from an implementation perspective.
• Design Guidelines
1. A design should exhibit an architectural structure that it:

(1) has been created using recognizable design patterns
(2) is composed of components that exhibit good design characteristics
(3) can be implemented in an evolutionary fashion, thereby facilitating implementation and testing.
2. A design should be modular; that is, the software should be logically partitioned into elements that perform specific functions and subfunctions.
3. A design should contain distinct representations of data, architecture, interfaces, and components (modules).
4. A design should lead to data structures that are appropriate for the objects to be implemented and are drawn from recognizable data patterns.
5. A design should lead to components that exhibit independent functional characteristics.
6. A design should lead to interfaces that reduce the complexity of connections between modules and with the external environment.
7. A design should be derived using a repeatable method that is driven by information obtained during software requirements analysis.

Design Principles

• The design process should not suffer from "tunnel vision."
• The design should be traceable to the analysis model.
• The design should not reinvent the wheel.
• The structure of the software design should  mimic the structure of the problem domain.
• The design should exhibit uniformity and integration.
• The design should be structured to accommodate change.
• The design should be structured to degrade gently, even when aberrant data, events, or operating conditions are encountered.
• Design is not coding, coding is not design.
• The design should be assessed for quality as it is being created, not after the fact.
• The design should be reviewed to minimize conceptual (semantic) errors.

Software Design Concepts

• Abstraction - allows designers to focus on solving a problem without being concerned about irrelevant lower level details (procedural abstraction - named sequence of events, data abstraction - named collection of data objects)

• Refinement - process of elaboration where the designer provides successively more detail for each design component

• Modularity - the degree to which software can be understood by examining its components independently of one another

• Modular Design Method Evaluation Criteria
• Modular decomposability - provides systematic means for breaking problem into subproblems
• Modular composability - supports reuse of existing modules in new systems
• Modular understandability - module can be understood as a stand-alone unit
• Modular continuity - side-effects due to module changes minimized
• Modular protection - side-effects due to processing errors minimized

• Software architecture - overall structure of the software components and the ways in which that structure provides conceptual integrity for a system
• Structural properties - Defines the components of a system (e.g., modules, objects, filters) and the manner in which those components are packaged and interact with one another.
• Extra-functional properties - The architectural design description should address how the design architecture achieves requirements for performance, capacity, reliability, security, adaptability, and other system characteristics.
• Families of related systems - The architectural design should draw upon repeatable patterns that are commonly encountered in the design of families of similar systems. In essence, the design should have the ability to reuse architectural building blocks.

• Control hierarchy or program structure - represents the module organization and implies a control hierarchy, but does not represent the procedural aspects of the software (e.g. event sequences)

• Structural partitioning
• horizontal partitioning - defines three partitions (input, data transformations, and output)
• Benefits:
• software that is easier to test
• software that is easier to maintain
• propagation of fewer side effects
• software that is easier to extend
• vertical partitioning (factoring) - distributes control in a top-down manner (control decisions in top level modules and processing work in the lower level modules)

• Data structure - representation of the logical relationship among individual data elements (requires at least as much attention as algorithm design)

• Software procedure - precise specification of processing (event sequences, decision points, repetitive operations, data organization/structure)

• Information hiding - information (data and procedure) contained within a module is inaccessible to modules that have no need for such information

Effective Modular Design

• Design software so that each module addresses a specific subfunction of requirements and has a simple interface when viewed from other parts of the program structure
• Measured using two qualitative criteria:
• Cohesion is a measure of the relative functional strength of a module
• Natural extension of the information hiding
• Cohesive module performs a single task within a software procedure, requiring little interaction with procedures being performed in other parts of a program
• Range of Cohesion - low (worse) to high (better)

• Coupling is a measure of the relative interdependence among modules
• Best - lowest possible coupling

Design Heuristics for effective Modularity

1. Evaluate the "first iteration" of the program structure to reduce coupling and improve cohesion
2. Attempt to minimize structures with high fan-out; strive for fan-in as depth increases
3. Keep the scope of effect of a module within the scope of control of that module
4. Evaluate module interfaces to reduce complexity and redundancy and improve consistency
5. Define modules whose function is predictable, but avoid modules that are overly restrictive
6. Strive for "controlled entry" modules by avoiding "pathological connections."

Design Documentation

• System Specification
• Software Requirements Specification