SDLC Models

Link for cocomo model: http://nptel.iitm.ac.in/courses/Webcourse-contents/IIT%20Kharagpur/Soft%20Engg/pdf/m11L28.pdf

SDLC Models

A Software Development Life Cycle Model is a set of activities together with an ordering relationship between activities which if performed in a manner that satisfies the ordering relationship that will produce desired product. Software Development Life Cycle Model is an abstract representation of a development process.

In a software development effort the goal is to produce high quality software. The development process is, therefore, the sequence of activities that will produce such software. A software development life cycle model is broken down into distinct activities. A software development life cycle model specifies how these activities are organized in the entire software development effort. We discuss each software development life cycle model in detail.

1. Waterfall Software Development Life Cycle Model 2. Prototyping Software Development Life Cycle Model 3. Iterative Enhacement Model 4. The Spiral Model 5. Object Oriented Methodology 6. Dynamic System Development Method

Waterfall Software Development Life Cycle Model

The simplest software development life cycle model is the waterfall model, which states that the phases are organized in a linear order. A project begins with feasibility analysis. On the successful demonstration of the feasibility analysis, the requirements analysis and project planning begins.

The design starts after the requirements analysis is done. And coding begins after the design is done. Once the programming is completed, the code is integrated and testing is done. On succeeful completion of testing, the system is installed. After this the regular operation and maintenance of the system takes place. The following figure demonstrates the steps involved in waterfall life cycle model.

The Waterfall Software Life Cycle Model

With the waterfall model, the activities performed in a software development project are requirements analysis, project planning, system design, detailed design, coding and unit testing, system integration and testing. Linear ordering of activities has some important consequences. First, to clearly identify the end of a phase and beginning of the others. Some certification mechanism has to be employed at the end of each phase. This is usually done by some verification and validation. Validation means confirming the output of a phase is consistent with its input (which is the output of the previous phase) and that the output of the phase is consistent with overall requirements of the system.

The consequences of the need of certification is that each phase must have some defined output that can be evaluated and certified. Therefore, when the activities of a phase are completed, there should be an output product of that phase and the goal of a phase is to produce this product. The outputs of the earlier phases are often called intermediate products or design document. For the coding phase, the output is the code. From this point of view, the output of a software project is to justify the final program along with the use of documentation with the requirements document, design document, project plan, test plan and test results.

Another implication of the linear ordering of phases is that after each phase is completed and its outputs are certified, these outputs become the inputs to the next phase and should not be changed or modified. However, changing requirements cannot be avoided and must be faced. Since changes performed in the output of one phase affect the later phases, that might have been performed. These changes have to made in a controlled manner after evaluating the effect of each change on the project.This brings us to the need for configuration control or configuration management.

The certified output of a phase that is released for the best phase is called baseline. The configuration management ensures that any changes to a baseline are made after careful review, keeping in mind the interests of all parties that are affected by it. There are two basic assumptions for justifying the linear ordering of phase in the manner proposed by the waterfall model.

For a successful project resulting in a successful product, all phases listed in the waterfall model must be performed anyway.

Any different ordering of the phases will result in a less successful software product.

• Requirements – defines needed information, function, behavior, performance and interfaces.• Design – data structures, software architecture, interface representations, algorithmic details.• Implementation – source code, database, user documentation, testing.

Project Output in a Waterfall Model

As we have seen, the output of a project employing the waterfall model is not just the final program along with documentation to use it. There are a number of intermediate outputs, which must be produced in order to produce a successful product.

The set of documents that forms the minimum that should be produced in each project are:

Requirement document Project plan System design document Detailed design document Test plan and test report Final code Software manuals (user manual, installation manual etc.)

Review reports

Except for the last one, these are all the outputs of the phases. In order to certify an output product of a phase before the next phase begins, reviews are often held. Reviews are necessary especially for the requirements and design phases, since other certification means are frequently not available. Reviews are formal meeting to uncover deficiencies in a product. The review reports are the outcome of these reviews.

Advantages of Waterfall Life Cycle Models

1. Easy to explain to the user2. Stages and activities are well defined3. Helps to plan and schedule the project4. Verification at each stage ensures early detection of errors / misunderstanding

Limitations of the Waterfall Life Cycle Model

The waterfall model assumes that the requirements of a system can be frozen (i.e. basedline) before the design begins. This is possible for systems designed to automate an existing manual system. But for absolutely new system, determining the requirements is difficult, as the user himself does not know the requirements. Therefore, having unchanging (or changing only a few) requirements is unrealistic for such project.

Freezing the requirements usually requires choosing the hardware (since it forms a part of the requirement specification). A large project might take a few years to complete. If the hardware is selected early, then due to the speed at which hardware technology is changing, it is quite likely that the final software will employ a hardware technology that is on the verge of becoming obsolete. This is clearly not desirable for such expensive software.

The waterfall model stipulates that the requirements should be completely specified before the rest of the development can proceed. In some situations it might be desirable to first develop a part of the system completely, an then later enhance the system in phase. This is often done for software products that are developed not necessarily for a client (where the client plays an important role in requirement specification), but for general marketing, in which the requirements are likely to be determined largely by developers.

The goal of prototyping based development is to counter the first two limitations of the waterfall model discussed earlier. The basic idea here is that instead of freezing the requirements before a design or coding can proceed, a throwaway prototype is built to understand the requirements. This prototype is developed based on the currently known requirements. Development of the prototype obviously undergoes design, coding and testing. But each of these phases is not done very formally or thoroughly. By using this prototype, the client can get an "actual feel" of the system, since the interactions with prototype can enable the client to better understand the requirements of the desired system.

• All requirements must be known upfront• Deliverables created for each phase are considered frozen – inhibits flexibility• Can give a false impression of progress• Does not reflect problem-solving nature of software development – iterations of phases• Integration is one big bang at the end• Little opportunity for customer to preview the system (until it may be too late)

Advantages

Simple goal. Simple to understand and use.

Clearly defined stages. Well understood milestones. Easy to arrange tasks. Process and results are Well documented. Easy to manage. Each phase has specific deliverable and a review. Works well for projects where requirements are well understood. Works well when quality is more important then cost/schedule. Customers/End users already know about it.

Disadvantages

It is difficult to measure progress within stages. Cannot accommodate changing requirements. No working software is produced until late in the life cycle. Risk and uncertainty is high with this process model. Adjusting scope during the life cycle can end a project Not suitable for complex projects Not suitable for projects of long duration because in long running projects

requirements are likely to change. Integration is done as a "big-bang” at the very end, which doesn't allow to identify

any technological or business bottleneck or challenges early. Users can only judge quality at the end. Attempt to go back 2 or more phases is very costly. Percentage completion of functionality can not be determined in mid of the project

because every functionality is undergoing some phase. Very risky, since one process can not start before finishing the other.

Prototyping Software Development Life Cycle Model

Prototyping is an attractive idea for complicated and large systems for which there is no manual process or existing system to help determining the requirements. In such situations letting the client "plan" with the prototype provides invaluable and intangible inputs which helps in determining the requirements for the system. It is also an effective method to demonstrate the feasibility of a certain approach. This might be needed for novel systems where it is not clear that constraints can be met or that algorithms can be developed to implement the requirements. The process model of the prototyping approach is shown in the figure below.

Prototyping Model

The basic reason for little common use of prototyping is the cost involved in this built-it-twice approach. However, some argue that prototyping need not be very costly and can actually reduce the overall development cost. The prototype are usually not complete systems and many of the details are not built in the prototype. The goal is to provide a system with overall functionality. In addition, the cost of testing and writing detailed documents are reduced. These factors helps to reduce the cost of developing the prototype. On the other hand, the experience of developing the prototype will very useful for developers when developing the final system. This experience helps to reduce the cost of development of the final system and results in a more reliable and better designed system.

• A preliminary project plan is developed• An partial high-level paper model is created• The model is source for a partial requirements specification• A prototype is built with basic and critical attributes • The designer builds

– the database – user interface – algorithmic functions

• The designer demonstrates the prototype, the user evaluates for problems and suggests improvements.

• This loop continues until the user is satisfied

When to use

• Requirements are unstable or have to be clarified • As the requirements clarification stage of a waterfall model• Develop user interfaces• Short-lived demonstrations • New, original development• With the analysis and design portions of object-oriented development.

Advantages of Prototyping

1. Users are actively involved in the development2. It provides a better system to users, as users have natural tendency to change their mind in specifying requirements and this method of developing systems supports this user tendency.3. Since in this methodology a working model of the system is provided, the users get a better understanding of the system being developed.4. Errors can be detected much earlier as the system is mode side by side.5. Quicker user feedback is available leading to better solutions.

Disadvantages

1.Leads to implementing and then repairing way of building systems.

2.Practically, this methodology may increase the complexity of the system as scope of the system may expand beyond original plans.

Advantages

Risk analysis is better.

It supports changing requirements. Initial Operating time is less. Better suited for large and mission-critical projects. During life cycle software is produced early which facilitates customer evaluation

and feedback.

Disadvantages

Not suitable for smaller projects. Management complexity is more. End of project may not be know which is a risk. Can be costly to use. Highly skilled resources are required for risk analysis. Project’s progress is highly dependent upon the risk analysis phase.

Iterative Enhacement Model

The iterative enhancement life cycle model counters the third limitation of the waterfall model and tries to combine the benefits of both prototyping and the waterfall model. The basic idea is that the software should be developed in increments, where each increment adds some functional capability to the system until the full system is implemented. At each step extensions and design modifications can be made. An advantage of this approach is that it can result in better testing, since testing each increment is likely to be easier than testing entire system like in the waterfall model. Furthermore, as in prototyping, the increments provides feedback to the client which is useful for determining the final requirements of the system.

In the first step of iterative enhancement model, a simple initial implementation is done for a subset of the overall problem. This subset is the one that contains some of the key aspects of the problem which are easy to understand and implement, and which forms a useful and usable system. A project control list is created which contains, in an order, all the tasks that must be performed to obtain the final implementation. This project control list gives an idea of how far the project is at any given step from the final system.Each step consists of removing the next step from the list. Designing the implementation for the selected task, coding and testing the implementation, and performing an analysis of the partial system obtained after this step and updating the list as a result of the analysis. These three phases are called the design phase, implementation phase and analysis phase. The process is iterated until the project control list is empty, at the time the final implementation of the system will be available. The process involved in iterative enhancement model is shown in the figure below.

The Iterative Enhancement Model

The project control list guides the iteration steps and keeps track of all tasks that must be done. The tasks in the list can be include redesign of defective components found during analysis. Each entry in that list is a task that should be performed in one step of the iterative enhancement process, and should be simple enough to be completely understood. Selecting tasks in this manner will minimize the chances of errors and reduce the redesign work.

Advantages

Some working functionality can be developed quickly and early in the life cycle. Results are obtained early and periodically. Parallel development can be planned. Progress can be measured. Less costly to change the scope/requirements. Testing and debugging during smaller iteration is easy. Risks are identified and resolved during an iteration; and each iteration is an easily

managed milestone. Easier to manage risk - High risk part is done first. With every increment operational product is delivered. Issues, challenges & risks identified from each increment can be utilized/applied to

the next increment.

Disadvantages

More resources may be required. Although cost of change is lesser but it is not very suitable for changing

requirements. More management attention is required. Each phase of an iteration is rigid with no overlaps. System architecture or design issues may arise because not all requirements are

gathered. up front for the entire life cycle. Does not allow iterations within an increment. Defining increments may require definition of the complete system.

Spiral model

This is a recent model that has been proposed by Boehm. As the name suggests, the activities in this model can be organized like a spiral. The spiral has many cycles. The radial dimension represents the cumulative cost incurred in accomplishing the steps dome so far and the angular dimension represents the progress made in completing each cycle of the spiral. The structure of the spiral model is shown in the figure given below. Each cycle in the spiral begins with the identification of objectives for that cycle and the different alternatives are possible for achieving the objectives and the imposed constraints.

The next step in the spiral life cycle model is to evaluate these different alternatives based on the objectives and constraints. This will also involve identifying uncertainties and risks involved. The next step is to develop strategies that resolve the uncertainties and risks. This step may involve activities such as benchmarking, simulation and prototyping. Next, the software is developed by keeping in mind the risks. Finally the next stage is planned.

The next step is determined by remaining risks. For example, its performance or user-interface risks are considered more important than the program development risks. The next step may be evolutionary development that involves developing a more detailed prototype for resolving the risks. On the other hand, if the program development risks dominate and previous prototypes have resolved all the user-interface and performance risks; the next step will follow the basic waterfall approach.

The risk driven nature of the spiral model allows it to accommodate any mixture of specification-oriented, prototype-oriented, simulation-oriented or some other approach. An important feature of the model is that each cycle of the spiral is completed by a review, which covers all the products developed during that cycle, including plans for the next cycle. The spiral model works for developed as well as enhancement projects.

Spiral Model Description

The development spiral consists of four quadrants as shown in the figure above

Quadrant 1: Determine objectives, alternatives, and constraints.

Quadrant 2: Evaluate alternatives, identify, resolve risks.

Quadrant 3: Develop, verify, next-level product.

Quadrant 4: Plan next phases.

Although the spiral, as depicted, is oriented toward software development, the concept is equally applicable to systems, hardware, and training, for example. To better understand the scope of each spiral development quadrant, let’s briefly address each one.

Quadrant 1: Determine Objectives, Alternatives, and Constraints

Activities performed in this quadrant include:

1. Establish an understanding of the system or product objectives—namely performance, functionality, and ability to accommodate change.2. Investigate implementation alternatives—namely design, reuse, procure, and procure/ modify3. Investigate constraints imposed on the alternatives—namely technology, cost, schedule, support, and risk. Once the system or product’s objectives, alternatives, and constraints are understood, Quadrant 2 (Evaluate alternatives, identify, and resolve risks) is performed.

Quadrant 2: Evaluate Alternatives, Identify, Resolve Risks

Engineering activities performed in this quadrant select an alternative approach that best satisfies technical, technology, cost, schedule, support, and risk constraints. The focus here is on risk mitigation. Each alternative is investigated and prototyped to reduce the risk associated with the development decisions. Boehm describes these activities as follows:

. . . This may involve prototyping, simulation, benchmarking, reference checking, administering userquestionnaires, analytic modeling, or combinations of these and other risk resolution techniques.

The outcome of the evaluation determines the next course of action. If critical operational and/or technical issues (COIs/CTIs) such as performance and interoperability (i.e., external and internal) risks remain, more detailed prototyping may need to be added before progressing to the next quadrant. Dr. Boehm notes that if the alternative chosen is “operationally useful and robust enough to serve as a low-risk base for future product evolution, the subsequent risk-driven steps would be the evolving series of evolutionary prototypes going toward the right (hand side of the graphic) . . . the option of writing specifications would be addressed but not exercised.” This brings us to Quadrant 3.

Quadrant 3: Develop, Verify, Next-Level Product

If a determination is made that the previous prototyping efforts have resolved the COIs/CTIs, activities to develop, verify, next-level product are performed. As a result, the basic “waterfall” approach may be employed—meaning concept of operations, design, development, integration, and test of the next system or product iteration. If appropriate, incremental development approaches may also be applicable.

Quadrant 4: Plan Next Phases

The spiral development model has one characteristic that is common to all models—the need for advanced technical planning and multidisciplinary reviews at critical staging or control points. Each cycle of the model culminates with a technical review that assesses the status, progress, maturity, merits, risk, of development efforts to date; resolves critical operational and/or technical issues (COIs/CTIs); and reviews plans and identifies COIs/CTIs to be resolved for the next iteration of the spiral.

Subsequent implementations of the spiral may involve lower level spirals that follow the same quadrant paths and decision considerations.

Advantages

Changing requirements can be accommodated. Allows for extensive use of prototypes Requirements can be captured more accurately. Users see the system early. Development can be divided in to smaller parts and more risky parts can be

developed earlier which helps better risk management.

Disadvantages

Management is more complex. End of project may not be known early. Not suitable for small or low risk projects (expensive for small projects). Process is complex Spiral may go indefinitely. Large number of intermediate stages require excessive documentation.

Object Oriented Methodology

We live in a world of objects. These objects exist in nature, in man-made entities, in business, and in the products that we use. They can be categorized, described, organized, combined, manipulated and created. Therefore, an object-oriented view has come into picture for creation of computer software. An object-oriented approach to the development of software was proposed in late 1960s.

Object-Oriented development requires that object-oriented techniques be used during the analysis, and implementation of the system. This methodology asks the analyst to determine what the objects of the system are, how they behave over time or in response to events, and what responsibilities and relationships an object has to other objects. Object-oriented analysis has the analyst look at all the objects in a system, their commonalties, difference, and how the system needs to manipulate the objects.

Object Oriented Process

The Object Oriented Methodology of Building Systems takes the objects as the basis. For this, first the system to be developed is observed and analyzed and the requirements are defined as in any other method of system development. Once this is done, the objects in the required system are identified. For example in case of a Banking System, a customer is an object, a chequebook is an object, and even an account is an object.

In simple terms, Object Modeling is based on identifying the objects in a system and their interrelationships. Once this is done, the coding of the system is done. Object Modeling is somewhat similar to the traditional approach of system designing, in that it also follows a sequential process of system designing but with a different approach. The basic steps of system designing using Object Modeling may be listed as:

System Analysis

System Design Object Design Implementation

System Analysis

As in any other system development model, system analysis is the first phase of development in case of Object Modeling too. In this phase, the developer interacts with the user of the system to find out the user requirements and analyses the system to understand the functioning.

Based on this system study, the analyst prepares a model of the desired system. This model is purely based on what the system is required to do. At this stage the implementation details are not taken care of. Only the model of the system is prepared based on the idea that the system is made up of a set of interacting objects. The important elements of the system are emphasized.

System Design

System Design is the next development stage where the overall architecture of the desired system is decided. The system is organized as a set of sub systems interacting with each other. While designing the system as a set of interacting subsystems, the analyst takes care of specifications as observed in system analysis as well as what is required out of the new system by the end user.

As the basic philosophy of Object-Oriented method of system analysis is to perceive the system as a set of interacting objects, a bigger system may also be seen as a set of interacting smaller subsystems that in turn are composed of a set of interacting objects. While designing the system, the stress lies on the objects comprising the system and not on the processes being carried out in the system as in the case of traditional Waterfall Model where the processes form the important part of the system.

Object Design

In this phase, the details of the system analysis and system design are implemented. The Objects identified in the system design phase are designed. Here the implementation of these objects is decided as the data structures get defined and also the interrelationships between the objects are defined.

Let us here deviate slightly from the design process and understand first a few important terms used in the Object-Oriented Modeling.

As already discussed, Object Oriented Philosophy is very much similar to real world and hence is gaining popularity as the systems here are seen as a set of interacting objects as in the real world. To implement this concept, the process-based structural programming is not used; instead objects are created using data structures. Just as every programming language provides various data types and various variables of that type can be created, similarly, in case of objects certain data types are predefined.

For example, we can define a data type called pen and then create and use several objects of this data type. This concept is known as creating a class.

Class: A class is a collection of similar objects. It is a template where certain basic characteristics of a set of objects are defined. The class defines the basic attributes and the operations of the objects of that type. Defining a class does not define any object, but it only creates a template. For objects to be actually created instances of the class are created as per the requirement of the case.

Abstraction: Classes are built on the basis of abstraction, where a set of similar objects are observed and their common characteristics are listed. Of all these, the characteristics of concern to the system under observation are picked up and the class definition is made. The attributes of no concern to the system are left out. This is known as abstraction.

The abstraction of an object varies according to its application. For instance, while defining a pen class for a stationery shop, the attributes of concern might be the pen color, ink color, pen type etc., whereas a pen class for a manufacturing firm would be containing the other dimensions of the pen like its diameter, its shape and size etc.

Inheritance: Inheritance is another important concept in this regard. This concept is used to apply the idea of reusability of the objects. A new type of class can be defined using a similar existing class with a few new features. For instance, a class vehicle can be defined with the basic functionality of any vehicle and a new class called car can be derived out of it with a few modifications. This would save the developers time and effort as the classes already existing are reused without much change.

Coming back to our development process, in the Object Designing phase of the Development process, the designer decides onto the classes in the system based on these concepts. The designer also decides on whether the classes need to be created from scratch or any existing classes can be used as it is or new classes can be inherited from them.

Implementation

During this phase, the class objects and the interrelationships of these classes are translated and actually coded using the programming language decided upon. The databases are made and the complete system is given a functional shape.

The complete OO methodology revolves around the objects identified in the system. When observed closely, every object exhibits some characteristics and behavior. The objects recognize and respond to certain events. For example, considering a Window on the screen as an object, the size of the window gets changed when resize button of the window is clicked.

Here the clicking of the button is an event to which the window responds by changing its state from the old size to the new size. While developing systems based on this approach, the analyst makes use of certain models to analyze and depict these objects. The methodology supports and uses three basic Models:

Object Model - This model describes the objects in a system and their interrelationships. This model observes all the objects as static and does not pay any attention to their dynamic nature. Dynamic Model - This model depicts the dynamic aspects of the system. It portrays the changes occurring in the states of various objects with the events that might occur in the system. Functional Model - This model basically describes the data transformations of the system. This describes the flow of data and the changes that occur to the data throughout the system.

While the Object Model is most important of all as it describes the basic element of the system, the objects, all the three models together describe the complete functional system.

As compared to the conventional system development techniques, OO modeling provides many benefits. Among other benefits, there are all the benefits of using the Object Orientation. Some of these are:

Reusability - The classes once defined can easily be used by other applications. This is achieved by defining classes and putting them into a library of classes where all the classes are maintained for

future use. Whenever a new class is needed the programmer looks into the library of classes and if it is available, it can be picked up directly from there. Inheritance - The concept of inheritance helps the programmer use the existing code in another way, where making small additions to the existing classes can quickly create new classes. Programmer has to spend less time and effort and can concentrate on other aspects of the system due to the reusability feature of the methodology. Data Hiding - Encapsulation is a technique that allows the programmer to hide the internal functioning of the objects from the users of the objects. Encapsulation separates the internal functioning of the object from the external functioning thus providing the user flexibility to change the external behaviour of the object making the programmer code safe against the changes made by the user. The systems designed using this approach are closer to the real world as the real world functioning of the system is directly mapped into the system designed using this approach.

Advantages of Object Oriented Methodology

Object Oriented Methodology closely represents the problem domain. Because of this, it is easier to produce and understand designs. The objects in the system are immune to requirement changes. Therefore, allows changes more easily. Object Oriented Methodology designs encourage more re-use. New applications can use the existing modules, thereby reduces the development cost and cycle time. Object Oriented Methodology approach is more natural. It provides nice structures for thinking and abstracting and leads to modular design.

V-shaped model

The V-Model is a systems development model designed to simplify the understanding of the complexity associated with developing systems.[2][3][4] In systems engineering it is used to define a uniform procedure for product or project development.

Overview

The V-model is a graphical representation of the systems development lifecycle. It summarizes the main

steps to be taken in conjunction with the corresponding deliverables within computerized system

validation framework.

The VEE represents the sequence of steps in a project life cycle development. It describes the activities

and results that have to be produced during product development. The left side of the "V" represents the

decomposition of requirements, and creation of system specifications. The right side of

the VEE represents integration of parts and their verification.[3][4][5][6][7] V stands for "Verification and

Validation".

[edit]Objectives

The V-Model provides guidance for the planning and realization of projects. The following objectives are

intended to be achieved by a project execution:

Minimization of Project Risks: The V-Model improves project transparency and project control by

specifying standardized approaches and describing the corresponding results and responsible roles.

It permits an early recognition of planning deviations and risks and improves process management,

thus reducing the project risk.

Improvement and Guarantee of Quality: As a standardized process model, the V-Model ensures

that the results to be provided are complete and have the desired quality. Defined interim results can

be checked at an early stage. Uniform product contents will improve readability, understandability

and verifiability.

Reduction of Total Cost over the Entire Project and System Life Cycle: The effort for the

development, production, operation and maintenance of a system can be calculated, estimated and

controlled in a transparent manner by applying a standardized process model. The results obtained

are uniform and easily retraced. This reduces the acquirers dependency on the supplier and the effort

for subsequent activities and projects.

Improvement of Communication between all Stakeholders: The standardized and uniform

description of all relevant elements and terms is the basis for the mutual understanding between all

stakeholders. Thus, the frictional loss between user, acquirer, supplier and developer is reduced.

[edit]V Model topics

Systems engineering and verification.[8]

[edit]Systems Engineering and verification

The Systems Engineering Process (SEP) provides a path for improving the cost effectiveness of complex

systems as experienced by the system owner over the entire life of the system, from conception to

retirement.[1]

It involved early and comprehensive identification of goals, a concept of operations that describes user

needs and the operating environment, thorough and testable system requirements, detailed design,

implementation, rigorous acceptance testing of the implemented system to ensure it meets the stated

requirements (system verification), measuring its effectiveness in addressing goals (system validation),

on-going operation and maintenance, system upgrades over time, and eventual retirement.[1][3][4][7]

The process emphasizes requirements-driven design and testing. All design elements and acceptance

tests must be traceable to one or more system requirements and every requirement must be addressed

by at least one design element and acceptance test. Such rigor ensures nothing is done unnecessarily

and everything that is necessary is accomplished.[1][3]

[edit]The specification stream

The specification stream mainly consists of:

User Requirement Specifications

Functional Requirement Specifications

Design Specifications

The testing stream generally consists of:

Installation Qualification (IQ)

Operational Qualification (OQ)

Performance Qualification (PQ)

The development stream can consist (depending on the system type and the development scope) of

customization, configuration or coding.

[edit]Applications

Off-Core alternatives (illustrating upward and downward iterations and Time and Maturity dimension). Source - K. Forsberg

and H. Mooz 2004[3][7]

The V-model is used to regulate the software development process within the German federal

administration. Nowadays it is still the standard for German federal administration and defense projects,

as well as software developers within the region.

The concept of the V-Model was developed simultaneously, but independently, in Germany and in the

United States in the late 1980s:

The German V-Model was originally developed by IABG in Ottobrunn, near Munich, in cooperation

with the Federal Office for Defense Technology and Procurement in Koblenz, for the Federal Ministry

of Defense. It was taken over by the Federal Ministry of the Interior for the civilian public authorities

domain in summer 1992.[9]

The US V-Model, as documented in the 1991 proceedings for the National Council on Systems

Engineering (NCOSE; now INCOSE as of 1995),[7] was developed for satellite systems involving

hardware, software, and human interaction.

The V-Model first appeared at Hughes Aircraft circa 1982 as part of the pre-proposal effort for the

FAA Advanced Automation System (AAS) program. It eventually formed the test strategy for the

Hughes AAS Design Competition Phase (DCP) proposal. It was created to show the test and

integration approach which was driven by new challenges to surface latent defects in the software.

The need for this new level of latent defect detection was driven by the goal to start automating the

thinking and planning processes of the air traffic controller as envisioned by the Automated Enroute

Air Traffic Control (AERA) program. The reason the V is so powerful comes from the Hughes culture

of coupling all text and analysis to multi dimensional images. It was the foundation of Sequential

Thematic Organization of Publications (STOP) [10]created by Hughes in 1963 and used until Hughes

was divested by the Howard Hughes Medical Institute in 1985.[11]

It has now found widespread application in commercial as well as defense programs. Its primary use is in

Project Management[3][4] and throughout the project lifecycle.

One fundamental characteristic of the US V-Model is that time and maturity move from left to right and

one cannot move back in time. All iteration is along a vertical line to higher or lower levels in the system

hierarchy, as shown in the figure.[3][4][7] This has proven to be an important aspect of the model. The

expansion of the model to a dual-Vee concept is treated in reference.[3]

As the V-model is publicly available many companies also use it. In project management it is a method

comparable to PRINCE2 and describes methods for project management as well as methods for system

development. The V-Model while rigid in process, can be very flexible in application, especially as it

pertains to the scope outside of the realm of the System Development Lifecycle normal parameters.

[edit]Advantages

These are the advantages V-Model offers in front of other systems development models:

The users of The V-Model participate in the development and maintenance of The V-Model. A

change control board publicly maintains the V-Model. The change control board meets once a year

and processes all received change requests on The V-Model.[12]

At each project start, the V-Model can be tailored into a specific project V-Model, this being possible

because the V-Model is organization and project independent.[13]

The V-Model provides concrete assistance on how to implement an activity and its work steps,

defining explicitly the events needed to complete a work step: each activity schema contains

instructions, recommendations and detailed explanations of the activity.[14]

[edit]Limits

The following aspects are not covered by the V-Model, they must be regulated in addition, or the V-Model

must be adapted accordingly [15][16]:

The placing of contracts for services is not regulated.

The organization and execution of operation, maintenance, repair and disposal of the system are not

covered by the V-Model. However, planning and preparation of a concept for these tasks are

regulated in the V-Model.

The V-Model addresses software development within a project rather than a whole organization.

Advantages

Simple and easy to use. Each phase has specific deliverables.

Higher chance of success over the waterfall model due to the development of test plans early on during the life cycle.

Works well for small projects where requirements are easily understood.

Disadvantages

Very rigid, like the waterfall model. Little flexibility and adjusting scope is difficult and expensive.

Software is developed during the implementation phase, so no early prototypes of the software are produced.

Model doesn’t provide a clear path for problems found during testing phases.

. RAD Model

RAD is a linear sequential software development process model that emphasis an extremely short development cycle using a component based construction approach. If the requirements are well understood and defines, and the project scope is constraint, the RAD process enables a development team to create a fully functional system with in very short time period.RAD (rapid application development) is a concept that products can be developed faster and of higher quality through:

Gathering requirements using workshops or focus groups Prototyping and early, reiterative user testing of designs The re-use of software components A rigidly paced schedule that defers design improvements to the next product version Less formality in reviews and other team communication

Some companies offer products that provide some or all of the tools for RAD software development. (The concept can be applied to hardware development as well.) These products include requirements gathering tools, prototyping tools, computer-aided software engineering tools, language development environments such as those for the Java platform, groupware for communication among development members, and testing tools. RAD usually embraces object-oriented programming methodology, which inherently fosters software re-use. The most popular object-oriented programming languages, C++ and Java, are offered in visual programming packages often described as providing rapid application development. Development MethodologyThe traditional software development cycle follows a rigid sequence of steps with a formal sign-off at the completion of each.  A complete, detailed requirements analysis is done that attempts to capture the system requirements in a Requirements Specification. Users are forced to “sign-off” on the

specification before development proceeds to the next step. This is followed by a complete system design and then development and testing.But, what if the design phase uncovers requirements that are technically unfeasible, or extremely expensive to implement? What if errors in the design are encountered during the build phase? The elapsed time between the initial analysis and testing is usually a period of several months. What if business requirements or priorities change or the users realize they overlooked critical needs during the analysis phase? These are many of the reasons why software development projects either fail or don’t meet the user’s expectations when delivered.RAD is a methodology for compressing the analysis, design, build, and test phases into a series of short, iterative development cycles. This has a number of distinct advantages over the traditional sequential development model.RAD projects are typically staffed with small integrated teams comprised of developers, end users, and IT technical resources. Small teams, combined with short, iterative development cycles, optimizes speed, unity of vision and purpose, effective informal communication and simple project management.

 RAD Model PhasesRAD model has the following phases:

1. Business Modeling: The information flow among business functions is defined by answering questions like what information drives the business process, what information is generated, who generates it, where does the information go, who process it and so on.

2. Data Modeling: The information collected from business modeling is refined into a set of data objects (entities) that are needed to support the business. The attributes (character of each entity) are identified and the relation between these data objects (entities) is defined.

3. Process Modeling: The data object defined in the data modeling phase are transformed to achieve the information flow necessary to implement a business function. Processing descriptions are created for adding, modifying, deleting or retrieving a data object.

4. Application Generation: Automated tools are used to facilitate construction of the software; even they use the 4th GL techniques.

5. Testing and Turn over: Many of the programming components have already been tested since RAD emphasis reuse. This reduces overall testing time. But new components must be tested and all interfaces must be fully exercised.

 Advantage and DisadvantagesRAD reduces the development time and reusability of components help to speed up development. All functions are modularized so it is easy to work with.For large projects RAD require highly skilled engineers in the team. Both end customer and developer should be committed to complete the system in a much abbreviated time frame. If commitment is lacking RAD will fail. RAD is based on Object Oriented approach and if it is difficult to modularize the project the RAD may not work well.

Advantages

Time to deliver is less. Changing requirements can be accommodated. Progress can be measured. Cycle time can be short with use of powerful RAD tools. Productivity with fewer people in short time. Use of tools and frameworks.

Disadvantages

Management complexity is more. Resource requirements may be more. Suitable for systems that are component based and scalable. Suitable only when requirements are well known. Requires user involvement throughout the life cycle. Suitable for project requiring shorter development times.

Extreme/Agile Development

Advantages

Promotes teamwork and cross training. Functionality can be developed rapidly and demonstrated. Resource requirements are minimum. Suitable for fixed or changing requirements Delivers early partial working solutions. Good model for environments that change steadily. Minimal rules, documentation easily employed. Enables concurrent development and delivery within an overall planned context.

Disadvantages

Not suitable for handling complex dependencies. More risk of sustainability, maintainability and extensibility. An overall plan, an agile leader and agile PM practice is a must without which it will

not work. Strict delivery management dictates the scope, functionality to be delivered, and

adjustments to meet the deadlines.