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Best Sites to Download Free Books Ever thought of creating a library with and to join online book clubs or discussion lists to discuss great works of literature. . to release quality recordings of classic books, all free for anyone to download. Download Metrics & Models in Software Quality lyubimov.info 52 Process Maturity Framework and Quality Standards. Our library includes free download of engineering books, Placement papers, Telecommunication ebooks Earthquake Engineering by Halil Sezen (ed.).

Not in United States? Choose your country's store to see books available for purchase. A concise, engineering-oriented resource that provides practical support to IT professionals and those responsible for the quality of the software or systems they develop. Software quality stems from two distinctive, but associated, topics in software engineering: This book studies the tenets of both of these notions, which focus on the efficiency and value of a design, respectively. It addresses engineering quality on both the application and system levels with attention to information systems IS and embedded systems ES as well as recent developments. Software Quality Engineering introduces the basic concepts of quality engineering like the nature of the engineering process, quality models and measurements, and evaluation quality, and provides a step-by-step overview of the application of software quality engineering in commonly recognized phases of the software development process.

Various specific methods for implementing the TQM philosophy are found in the works of Crosby , Deming , Feigenbaum , , Ishikawa , and Juran and Gryna Since the s, many U. The adoption of ISO as the quality management standard by the European Community and the acceptance of such standards by the U.

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Hewlett-Packard's TQC focuses on key areas such as management commitment, leadership, customer focus, total participation, and systematic analysis. Each area has strategies and plans to drive the improvement of quality, efficiency, and responsiveness, with the final objective being to achieve success through customer satisfaction Shores, Motorola's Six Sigma strategy focuses on achieving stringent quality levels in order to obtain total customer satisfaction.

Cycle time reduction and participative management are among the key initiatives of the strategy Smith, Six Sigma is not just a measure of the quality level; inherent in the concept are product design improvements and reductions in process variations Harry and Lawson, Six Sigma is applied to product quality as well as everything that can be supported by data and measurement. The strategy comprises four initiatives: Despite variations in its implementation, the key elements of a TQM system can be summarized as follows: Customer focus: The objective is to achieve total customer satisfaction.

Customer focus includes studying customers' wants and needs, gathering customers' requirements, and measuring and managing customers' satisfaction.

The objective is to reduce process variations and to achieve continuous process improvement. This element includes both the business process and the product development process. Through process improvement, product quality will be enhanced. Human side of quality: The objective is to create a companywide quality culture. Focus areas include leadership, management commitment, total participation, employee empowerment, and other social, psychological, and human factors.

Measurement and analysis: The objective is to drive continuous improvement in all quality parameters by the goal-oriented measurement system. Clearly, measurement and analysis are the fundamental elements for gauging continuous improvement.

Key Elements of Total Quality Management Various organizational frameworks have been proposed to improve quality that can be used to substantiate the TQM philosophy. Plan-Do-Check-Act is based on a feedback cycle for optimizing a single process or production line.

It uses techniques, such as feedback loops and statistical quality control, to experiment with methods for improvement and to build predictive models of the product. Basic to the assumption is that a process is repeated multiple times, so that data models can be built that allow one to predict results of the process. The six fundamental steps of the Quality Improvement Paradigm are 1 characterize the project and its environment, 2 set the goals, 3 choose the appropriate processes, 4 execute the processes, 5 analyze the data, and 6 package the experience for reuse.

The Experience Factory Organization separates the product development from the experience packaging activities. Basic to this approach is the need to learn across multiple project developments. The SEI Capability Maturity Model is a staged process improvement, based on assessment of key process areas, until you reach level 5, which represents a continuous process improvement. The approach is based on organizational and quality management maturity models developed by Likert and Crosby , respectively.

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The goal of the approach is to achieve continuous process improvement via defect prevention, technology innovation, and process change management.

As part of the approach, a five-level process maturity model is defined based on repeated assessments of an organization's capability in key process areas.

Improvement is achieved by action plans for poor process areas. Basic to this approach is the idea that there are key process areas and attending to them will improve your software development.

Lean Enterprise Management is based on the principle of concentration of production on "value-added" activities and the elimination or reduction of "not-value-added" activities. The goal is to build software with the minimum necessary set of activities and then to tailor the process to the product's requirements.

Basic to this approach is the assumption that the process can be tailored to classes of problems. From the popular view, quality is some type of thing that cannot be quantified: I know it when I see it. Quality and grade or class are often confused. From the professional view, quality must be defined and measured for improvement and is best defined as "conformance to customers' requirements. The TQM philosophy aims at long-term success by linking quality and customer satisfaction.

Despite variations in its implementation, a TQM system comprises four key common elements: It is not surprising that the professional definition of quality fits perfectly in the TQM context. That definition correlates closely with the first two of the TQM elements customer focus and process improvement.

To achieve good quality, all TQM elements must definitely be addressed, with the aid of some organizational frameworks. In this book, our key focus is on metrics, measurements, and quality models as they relate to software engineering. In the next chapter we discuss various software development models and the process maturity framework.

Basili, V. SE, No. Caldiera, F. McGarry, R. Pajersky, G. Page, and S. Waligora, "The Software Engineering Laboratory: Musa, "The Future Engineering of Software: Bowen, T. Crosby, P. McGraw-Hill, Deming, W. Massachusetts Institute of Technology, Feigenbaum, A. Engineering and Management , New York: Guaspari, J. American Management Association, Quality for the Rest of Us , New York: Harry, M. Addison-Wesley, Humphrey, W. Ishikawa, K.

PrenticeHall, Jones, C. Assuring Productivity and Quality , New York: Juran, J. Gryna, Jr. Likert, R. Its Management and Value , New York: Radice, R. Harding, P. Munnis, and R. Shewhart, W. Van Nostrand Company, Shores, D. Smith, W. Womack, J. Jones, and D. Rawson Associates, Zimmer, B. Software Development Process Models Software metrics and models cannot be discussed in a vacuum; they must be referenced to the software development process.

In this chapter we summarize the major process models being used in the software development community. We start with the waterfall process life-cycle model and then cover the prototyping approach, the spiral model, the iterative development process, and several approaches to the object-oriented development process. Processes pertinent to the improvement of the development process, such as the Cleanroom methodology and the defect prevention process, are also described.

In the last part of the chapter we shift our discussion from specific development processes to the evaluation of development processes and quality management standards. The emergence of the waterfall process to help tackle the growing complexity of development projects was a logical event Boehm, As Figure 1. It then breaks the complex mission of development into several logical steps design, code, test, and so forth with intermediate deliverables that lead to the final product.

To ensure proper execution with good-quality deliverables, each step has validation, entry, and exit criteria. The divide-and-conquer approach of the waterfall process has several advantages. It enables more accurate tracking of project progress and early identification of possible slippages. It forces the organization that develops the software system to be more structured and manageable.

This structural approach is very important for large organizations with large, complex development projects. It demands that the process generate a series of documents that can later be used to test and maintain the system Davis et al. The bottom line of this approach is to make large software projects more manageable and delivered on time without cost overrun.

Experiences of the past several decades show that the waterfall process is very valuable. Many major developers, especially those who were established early and are involved with systems development, have adopted this process.

This group includes commercial corporations, government contractors, and governmental entities. Although a variety of names have been given to each stage in the model, the basic methodologies remain more or less the same.

Thus, the system-requirements stages are sometimes called system analysis, customer-requirements gathering and analysis, or user needs analysis; the design stage may be broken down into high-level design and detaillevel design; the implementation stage may be called code and debug; and the testing stage may include component-level test, product-level test, and system-level test.

Figure 2. Note that the requirements stage is followed by a stage for architectural design. When the system architecture and design are in place, design and development work for each function begins. Despite the waterfall concept, parallelism exists because various functions can proceed simultaneously. As shown in the figure, the code development and unit test stages are also implemented iteratively.

Since UT is an integral part of the implementation stage, it makes little sense to separate it into another formal stage.

Before the completion of the HLD, LLD, and code, formal reviews and inspections occur as part of the validation and exit criteria. These inspections are called I0, I1, and I2 inspections, respectively.

When the code is completed and unit tested, the subsequent stages are integration, component test, system test, and early customer programs.

The final stage is release of the software system to customers. High-Level Design High-level design is the process of defining the externals and internals from the perspective of a component.

Its objectives are as follows: Develop the external functions and interfaces, including: Design the internal component structure, including intracomponent interfaces and data structures.

Ensure all functional requirements are satisfied. Ensure the component design is complete. Low-Level Design Low-level design is the process of transforming the HLD into more detailed designs from the perspective of a part modules, macros, includes, and so forth.

Finalize the design of components and parts modules, macros, includes within a system or product. Code Stage The coding portion of the process results in the transformation of a function's LLD to completely coded parts.

The objectives of this stage are as follows: Code parts modules, macros, includes, messages, etc. Code component test cases. Unit Test The unit test is the first test of an executable module. Verify the code against the component's high-level design and low-level design. Execute all new and changed code to ensure all branches are executed in all directions, logic is correct, and data paths are verified. Exercise all error messages, return codes, and response options.

The level of unit test is for verification of limits, internal interfaces, and logic and data paths in a module, macro, or executable include. Unit testing is performed on nonintegrated code and may require scaffold code to construct the proper environment. Component Test Component tests evaluate the combined software parts that make up a component after they have been integrated into the system library.

The objectives of this test are as follows: Test intercomponent interfaces against the component's design documentation. Test application program interfaces against the component's design documentation. Test function against the component's design documentation.

Test intracomponent interfaces module level against the component's design documentation. Test error recovery and messages against the component's design documentation. Verify that component drivers are functionally complete and at the acceptable quality level. Test ported and unchanged functions against the component's design documentation. System-Level Test The system-level test phase comprises the following tests: System test System regression test System performance measurement test Usability tests The system test follows the component tests and precedes system regression tests.

The system performance test usually begins shortly after system testing starts and proceeds throughout the systemlevel test phase. Usability tests occur throughout the development process i. System test objectives Ensure software products function correctly when executed concurrently and in stressful system environments. Verify overall system stability when development activity has been completed for all products. System regression test objective Verify that the final programming package is ready to be shipped to external customers.

Make sure original functions work correctly after functions were added to the system. System performance measurement test objectives Validate the performance of the system.

Verify performance specifications. Provide performance information to marketing. Establish base performance measurements for future releases. Usability tests objective Verify that the system contains the usability characteristics required for the intended user tasks and user environment.

Early Customer Programs The early customer programs ECP include testing of the following support structures to verify their readiness: Collections of such data or user opinion include: Product feedback: It is most appropriate for systems development characterized by a high degree of complexity and interdependency. Although expressed as a cascading waterfall, parallelism and some amount of iteration among process phases often exist in actual implementation.

During this process, the focus should be on the intermediate deliverables e. In other words, it should be entity-based instead of step-by-step based. Otherwise the process could become too rigid to be efficient and effective. When the requirements are defined, the design and development work begins. The model assumes that requirements are known, and that once requirements are defined, they will not change or any change will be insignificant. This may well be the case for system development in which the system's purpose and architecture are thoroughly investigated.

However, if requirements change significantly between the time the system's specifications are finalized and when the product's development is complete, the waterfall may not be the best model to deal with the resulting problems.

Sometimes the requirements are not even known. In the past, various software process models have been proposed to deal with customer feedback on the product to ensure that it satisfied the requirements. Each of these models provides some form of prototyping, of either a part or all of the system. Some of them build prototypes to be thrown away; others evolve the prototype over time, based on customer needs.

A prototype is a partial implementation of the product expressed either logically or physically with all external interfaces presented. The potential customers use the prototype and provide feedback to the development team before full-scale development begins. Seeing is believing , and that is really what prototyping intends to achieve. By using this approach, the customers and the development team can clarify requirements and their interpretation. As Figure 2.

Gather and analyze requirements. Do a quick design. Build a prototype. Customers evaluate the prototype. Refine the design and prototype. If customers are not satisfied with the prototype, loop back to step 5. If customers are satisfied, begin full-scale product development. Several technologies can be used to achieve such an objective. Reusable software parts could make the design and implementation of prototypes easier. Formal specification languages could facilitate the generation of executable code e.

Fourth-generation lan-guages and technologies could be extremely useful for prototyping in the graphical user interface GUI domain. These technologies are still emerging, however, and are used in varying degrees depending on the specific characteristics of the projects.

The prototyping approach is most applicable to small tasks or at the subsystem level. Prototyping a complete system is difficult. Another difficulty with this approach is knowing when to stop iterating. In practice, the method of time boxing is being used. This method involves setting arbitrary time limits e. Rapid Throwaway Prototyping The rapid throwaway prototyping approach of software development, made popular by Gomaa and Scott , is now used widely in the industry, especially in application development.

It is usually used with high-risk items or with parts of the system that the development team does not understand thoroughly. In this approach, "quick and dirty" prototypes are built, verified with customers, and thrown away until a satisfactory prototype is reached, at which time full-scale development begins. Evolutionary Prototyping In the evolutionary prototyping approach, a prototype is built based on some known requirements and understanding.

The prototype is then refined and evolved instead of thrown away. Whereas throwaway prototypes are usually used with the aspects of the system that are poorly understood, evolutionary prototypes are likely to be used with aspects of the system that are well understood and thus build on the development team's strengths.

These prototypes are also based on prioritized requirements, sometimes referred to as "chunking" in application development Hough, For complex applications, it is not reasonable or economical to expect the prototypes to be developed and thrown away rapidly.

Relying heavily on prototyping and risk management, it is much more flexible than the waterfall model. The spiral concept and the risk management focus have gained acceptance in software engineering and project management in recent years. The underlying concept of the model is that each portion of the product and each level of elaboration involves the same sequence of steps cycle. Starting at the center of the spiral, one can see that each development phase concept of operation, software requirements, product design, detailed design, and implementation involves one cycle of the spiral.

The radial dimension in Figure 2. The angular dimension represents the progress made in completing each cycle of the spiral. As indicated by the quadrants in the figure, the first step of each cycle of the spiral is to identify the objectives of the portion of the product being elaborated, the alternative means of implementation of this portion of the product, and the constraints imposed on the application of the alternatives.

The next step is to evaluate the alternatives relative to the objectives and constraints, to identify the associated risks, and to resolve them. Risk analysis and the risk-driven approach, therefore, are key characteristics of the spiral model, in contrast to the document-driven approach of the waterfall model.

Reprinted with permission. In this risk-driven approach, prototyping is an important tool. Usually prototyping is applied to the elements of the system or the alternatives that present the higher risks. Unsatisfactory prototypes can be thrown away; when an operational prototype is in place, implementation can begin. Finally, as indicated in the illustration, an important feature of the spiral model, as with other models, is that each cycle ends with a review involving the key members or organizations concerned with the product.

For software projects with incremental development or with components to be developed by separate organizations or individuals, a series of spiral cycles can be used, one for each increment or component. A third dimension could be added to Figure 2. Boehm provides a candid discussion of the advantages and disadvantages of the spiral model. Its advantages are as follows: Its range of options accommodates the good features of existing software process models, whereas its risk-driven approach avoids many of their difficulties.

This is the primary advantage. Boehm also discusses the primary conditions under which this model becomes equivalent to other process models such as the waterfall model and the evolutionary prototype model. It focuses early attention on options involving the reuse of existing software. These options are encouraged because early identification and evaluation of alternatives is a key step in each spiral cycle.

This model accommodates preparation for life-cycle evolution, growth, and changes of the software product. It provides a mechanism for incorporating software quality objectives into software product development. It focuses on eliminating errors and unattractive alternatives early. It does not involve separate approaches for software development and software enhancement. It provides a viable framework for integrating hardware-software system development.

The riskdriven approach can be applied to both hardware and software. On the other hand, difficulties with the spiral model include the following: Matching to contract software: Contract software relies heavily on control, checkpoint, and intermediate deliverables for which the waterfall model is good. The spiral model has a great deal of flexibility and freedom and is, therefore, more suitable for internal software development. The challenge is how to achieve the flexibility and freedom prescribed by the spiral model without losing accountability and control for contract software.

Relying on risk management expertise: The risk-driven approach is the back-bone of the model. The risk-driven specification addresses high-risk elements in great detail and leaves low-risk elements to be elaborated in later stages. However, an inexperienced team may also produce a specification just the opposite: In such a case, the project may fail and the failure may be discovered only after major resources have been invested. Another concern is that a risk-driven specification is people dependent.

In the case where a design produced by an expert is to be implemented by nonexperts, the expert must furnish additional documentation. Need for further elaboration of spiral steps: The spiral model describes a flexible and dynamic process model that can be used to its fullest advantage by experienced developers.

For nonexperts and especially for large-scale projects, however, the steps in the spiral must be elaborated and more specifically defined so that consistency, tracking, and control can be achieved.

Such elaboration and control are especially important in the area of risk analysis and risk management. Metrics and Models in Software Quality Engineering, 2. Based on the analysis of each intermediate product, the design and the requirements are modified over a series of iterations to provide a system to the users that meets evolving customer needs with improved design based on feedback and learning.

The IDP model combines prototyping with the strength of the classical waterfall model. Other methods such as domain analysis and risk analysis can also be incorporated into the IDP model. The model has much in common with the spiral model, especially with regard to prototyping and risk management. Indeed, the spiral model can be regarded as a specific IDP model, while the term IDP is a general rubric under which various forms of the model can exist.

The model also provides a framework for many modern systems and software engineering methods and techniques such as reuse, object-oriented development, and rapid prototyping.

With the purpose of "building a system by evolving an architectural prototype through a series of executable versions, with each successive iteration incorporating experience and more system functionality," the example implementation contains eight major steps Luckey et al. Luckey, R. Pittman, and A. Requirements definition 3. Software architecture 4. Risk analysis 5. Prototype 6. Test suite and environment development 7. Integration with previous iterations 8.

Release of iteration As illustrated in the figure, the iteration process involves the last five steps; domain analysis, requirements definition, and software architecture are preiteration steps, which are similar to those in the waterfall model.

During the five iteration steps, the following activities occur: Analyze or review the system requirements. Design or revise the solution that best satisfies the requirements. Identify the highest risks for the project and prioritize them. Mitigate the highest priority risk via prototyping, leaving lower risks for subsequent iterations.

Define and schedule or revise the next few iterations. Develop the iteration test suite and supporting test environment. Implement the portion of the design that is minimally required to satisfy the current iteration. Integrate the software in test environments and perform regression testing.

Update documents for release with the iteration. Release the iteration. Note that test suite development along with design and development is extremely important for the verification of the function and quality of each iteration. Yet in practice this activity is not always emphasized appropriately. The iterative part of the process involved the loop of subsystem design subsystem code and test system integration customer feedback subsystem design. Specifically, the waterfall process involved the steps of market requirements, design, code and test, and system certification.

The iterative process went from initial market requirements to the iterative loop, then to system certification. Within the one-year development cycle, there were five iterations, each with increased functionality, before completion of the sys-tem. For each iteration, the customer feedback involved a beta test of the available functions, a formal customer satisfaction survey, and feedback from various vehicles such as electronic messages on Prodigy, IBM internal e-mail conferences, customer visits, technical seminars, and internal and public bulletin boards.

Feedback from various channels was also statistically verified and validated by the formal customer satisfaction surveys. More than 30, customers and , users were involved in the iteration feedback process. Supporting the iterative process was the small team approach in which each team assumed full responsibility for a particular function of the system. Each team owned its project, functionality, quality, and customer satisfaction, and was held completely responsible.

Cross-functional system teams also provided support and services to make the subsystem teams successful and to help resolve cross-subsystem concerns Jenkins, This approach will continue to have a major effect in software for many years. Different from traditional programming, which separates data and control, object-oriented programming is based on objects, each of which is a set of defined data and a set of operations methods that can be performed on that data.

Like the paradigm of structural design and functional decomposition, the object-oriented approach has become a major cornerstone of software engineering. In the early days of OO technology deployment from late s to mid s , much of the OO literature concerned analysis and design methods; there was little information about OO development processes. In recent years the object-oriented technology has been widely accepted and object-oriented development is now so pervasive that there is no longer a question of its viability.

Branson and Herness proposed an OO development process for large-scale projects that centers on an eight-step methodology supported by a mechanism for tracking, a series of inspections, a set of technologies, and rules for prototyping and testing. The eight-step process is divided into three logical phases: The analysis phase focuses on obtaining and representing customers' requirements in a concise manner, to visualize an essential system that represents the users' requirements regardless of which implementation platform hardware or software environment is developed.

The design phase involves modifying the essential system so that it can be implemented on a given set of hardware and software. Essential classes and incarnation classes are combined and refined into the evolving class hierarchy. The objectives of class synthesis are to optimize reuse and to create reusable classes. The implementation phase takes the defined classes to completion. The eight steps of the process are summarized as follows: Model the essential system: The essential system describes those aspects of the system required for it to achieve its purpose, regardless of the target hardware and software environment.

It is composed of essential activities and essential data. This step has five substeps: Create the user view. Model essential activities. Define solution data. Refine the essential model. Construct a detailed analysis. This step focuses on the user requirements. Requirements are analyzed, dissected, refined, combined, and organized into an essential logical model of the system.

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This model is based on the perfect technology premise. Derive candidate-essential classes: This step uses a technique known as "carving" to identify candidate-essential classes and methods from the essential model of the whole system. A complete set of data-flow diagrams, along with supporting process specifications and data dictionary entries, is the basis for class and method selection.

Candidate classes and methods are found in external entities, data stores, input flows, and process specifications. Constrain the essential model: Essential activities and essential data are allocated to the various processors and containers data repositories.

Activities are added to the system as needed, based on limitations in the target implementation environment. The essential model, when augmented with the activities needed to support the target environment, is referred to as the incarnation model.

Derive additional classes: Additional candidate classes and methods specific to the implementation environment are selected based on the activities added while constraining the essential model. These classes supply interfaces to the essential classes at a consistent level.

Synthesize classes: The candidate-essential classes and the candidate-additional classes are refined and organized into a hierarchy.

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Common attributes and operations are extracted to produce superclasses and subclasses. Final classes are selected to maximize reuse through inheritance and importation. Define interfaces: The interfaces, object-type declarations, and class definitions are written based on the documented synthesized classes. Complete the design: The design of the implementation module is completed.

The implementation module comprises several methods, each of which provides a single cohesive function. Logic, system interaction, and method invocations to other classes are used to accomplish the complete design for each method in a class. Referential integrity constraints specified in the essential model using the data model diagrams and data dictionary are now reflected in the class design. Implement the solution: The implementation of the classes is coded and unit tested.

The analysis phase of the process consists of steps 1 and 2, the design phase consists of steps 3 through 6, and the implementation phase consists of steps 7 and 8.

Several iterations are expected during analysis and design. Prototyping may also be used to validate the essential model and to assist in selecting the appropriate incarnation.

Furthermore, the process calls for several reviews and checkpoints to enhance the control of the project. The reviews include the following: Requirements review after the second substep of step 1 model essential system External structure and design review after the fourth substep refined model of step 1 Class analysis verification review after step 5 Class externals review after step 6 Code inspection after step 8 code is complete In addition to methodology, requirements, design, analysis, implementation, prototyping, and verification, Branson and Herness assert that the object-oriented development process architecture must also address elements such as reuse, CASE tools, integration, build and test, and project management.

The Branson and Herness process model, based on their object-oriented experience at IBM Rochester, represents one attempt to deploy the object-oriented technology in large organizations. It is certain that many more variations will emerge before a commonly recognized OOP model is reached. Finally, the element of reuse merits more discussion from the process perspective, even in this brief section. Design and code reuse gives object-oriented development significant advantages in quality and productivity.

However, reuse is not automatically achieved simply by using object-oriented development. Object-oriented development provides a large potential source of reusable components, which must be generalized to become usable in new development environments. In terms of development life cycle, generalization for reuse is typically considered an "add-on" at the end of the project. However, generalization activities take time and resources. Therefore, developing with reuse is what every objectoriented project is aiming for, but developing for reuse is difficult to accomplish.

Therefore, organizations that intend to leverage the reuse advantage of OO development must deal with this issue in their development process. Henderson-Sellers and Pant propose a two-library model for the generalization activities for reusable parts. The model addresses the problem of costing and is quite promising. The first step is to put "on hold" project-specific classes from the current project by placing them in a library of potentially reusable components LPRC.

Thus the only cost to the current project is the identification of these classes.

The second library, the library of generalized components LGC , is the high-quality company resource. At the beginning of each new project, an early phase in the development process is an assessment of classes that reside in the LPRC and LGC libraries in terms of their reuse value for the project.

If of value, additional spending on generalization is made and potential parts in LPRC can undergo the generalization process and quality checks and be placed in LGC.

Because the reusable parts are to benefit the new project, it is reasonable to allocate the cost of generalization to the customer, for whom it will be a savings.

As the preceding discussion illustrates, it may take significant research, experience, and ingenuity to piece together the key elements of an object-oriented development process and for it to mature. It is usecase driven, architecturecentric, iterative, and incremental. Use cases are the key components that drive this process model. A use case can be defined as a piece of functionality that gives a user a result of a value. All the use cases developed can be combined into a use-case model, which describes the complete functionality of the system.

The use-case model is analogous to the functional specification in a traditional software development process model. Use cases are developed with the users and are modeled in UML. These represent the requirements for the software and are used throughout the process model. The Unified Process is also described as architecture-centric. This architecture is a view of the whole design with important characterisitcs made visible by leaving details out.

It works hand in hand with the use cases. Subsystems, classes, and components are expressed in the architecture and are also modeled in UML. Last, the Unified Process is iterative and incremental.

Iterations represent steps in a workflow, and increments show growth in functionality of the product. The core workflows for iterative development are: Each cycle results in a new release of the system, and each release is a deliverable product. Each cycle has four phases: A number of iterations occur in each phase, and the five core workflows take place over the four phases.

During inception, a good idea for a software product is developed and the project is kicked off. A simplified use-case model is created and project risks are prioritized. Next, during the elaboration phase, product use cases are specified in detail and the system architecture is designed. The project manager begins planning for resources and estimating activities.

All views of the system are delivered, including the usecase model, the design model, and the implementation model. These models are developed using UML and held under configuration management.

Once this phase is complete, the construction phase begins. From here the architecture design grows into a full system. Code is developed and the software is tested. Then the software is assessed to determine if the product meets the users' needs so that some customers can take early delivery. Finally, the transition phase begins with beta testing. One very controversial OO process that has gained recognition and generated vigorous debates among software engineers is Extreme Programming XP proposed by Kent Beck This lightweight, iterative and incremental process has four cornerstone values: With this foundation, XP advocates the following practices: The Planning Game: Development teams estimate time, risk, and story order.

The customer defines scope, release dates, and priority. System metaphor: A metaphor describes how the system works. Simple design: Designs are minimal, just enough to pass the tests that bound the scope. Pair programming: All design and coding is done by two people at one workstation. This spreads knowledge better and uses constant peer reviews.

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Unit testing and acceptance testing: Unit tests are written before code to give a clear intent of the code and provide a complete library of tests. Code is refactored before and after implementing a feature to help keep the code clean. Collective code ownership: By switching teams and seeing all pieces of the code, all developers are able to fix broken pieces.

Continuous integration: The more code is integrated, the more likely it is to keep running without big hang-ups. On-site customer: An onsite customer is considered part of the team and is responsible for domain expertise and acceptance testing. Stipulating a hour week ensures that developers are always alert. Small releases: Releases are small but contain useful functionality.

Coding standard: Coding standards are defined by the team and are adhered to. According to Beck, because these practices balance and reinforce one another, implementing all of them in concert is what makes XP extreme. With these practices, a software engineering team can "embrace changes. It appears that the XP philosophy and practices may be more applicable to small projects.

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For large and complex software development, some XP principles become harder to implement and may even run against traditional wisdom that is built upon successful projects.

Beck stipulates that to date XP efforts have worked best with teams of ten or fewer members. The Cleanroom process employs theory-based technologies such as box structure specification of user function and system object architecture, function-theoretic design and correctness verification, and statistical usage testing for quality certification.

Cleanroom management is based on incremental development and certification of a pipeline of user-function increments that accumulate into the final product. Cleanroom operations are carried out by small, independent development and certification test teams, with teams of teams for large projects Linger, The Cleanroom process emphasizes the importance of the development team having intellectual control over the project. The bases of the process are proof of correctness of design and code and formal quality certification via statistical testing.

Perhaps the most controversial aspect of Cleanroom is that team verification of correctness takes the place of individual unit testing. Once the code is developed, it is subject to statistical testing for quality assessment. Proponents argue that the intellectual control of a project afforded by team verification of correctness is the basis for prohibition of unit testing.

This elimination also motivates tremendous determination by developers that the code they deliver for independent testing be error-free on first execution Hausler and Trammell, The Cleanroom process proclaims that statistical testing can replace coverage and path testing.

In Cleanroom, all testing is based on anticipated customer usage. Test cases are designed to rehearse the more frequently used functions. In terms of measurement, software quality is certified in terms of mean time to failure MTTF.

The Cleanroom process represents one of the formal approaches in software development that have begun to see application in industry. Since the pilot projects in and , a number of projects have been completed using the Cleanroom process.

As reported by Linger , the average defect rate in first-time execution was 2. The adoption of Cleanroom thus far is mostly confined to small projects. Like other formal methods, the questions about its ability to be scaled up to large projects and the mathematical training required have been asked by many developers and project managers.

Also, as discussed previously, the prohibition of unit testing is perhaps the most controversial concern. This is especially true when the software system is complex or when the system is a common-purpose system where a typical customer usage profile is itself in question. Not surprisingly, some Cleanroom projects do not preclude the traditional methods such as unit test and limit test while adopting Cleanroom's formal approaches.

Hausler and Trammell even proposed a phased implementation approach in order to facilitate the acceptance of Cleanroom. The phased implementation framework includes three stages: Introductory implementation involves the implementation of Cleanroom principles without the full formality of the methodology e. Full implementation involves the complete use of Cleanroom's formal methods as illustrated in Figure 2.

Advanced implementation optimizes the process for the local environment e. In their recent work, the Cleanroom experts elaborate in detail the development and certification process Prowell et al.

They also show that the Cleanroom software process is compatible with the Software Engineering Institute's capability maturity model CMM. Rather, it is a process to continually improve the development process. It originated in the software development environment and thus far has been implemented mostly in software development organizations.

Because we would be remiss if we did not discuss this process while discussing software development processes, this chapter includes a brief discussion of DPP. The DPP was modeled on techniques used in Japan for decades and is in agreement with Deming's principles. It is based on three simple steps: Analyze defects or errors to trace the root causes. Suggest preventive actions to eliminate the defect root causes.

Implement the preventive actions. Causal analysis meetings: These are usually two-hour brainstorming sessions conducted by technical teams at the end of each stage of the development process. Developers analyze defects that occurred in the stage, trace the root causes of errors, and suggest possible actions to prevent similar errors from recurring. Methods for removing similar defects in a current product are also discussed.

Team members discuss overall defect trends that may emerge from their analysis of this stage, particularly what went wrong and what went right, and examine suggestions for improvement. After the meeting, the causal analysis leader records the data defects, causes, and suggested actions in an action database for subsequent reporting and tracking. To allow participants at this meeting to express their thoughts and feelings on why defects occurred without fear of jeopardizing their careers, managers do not attend this meeting.

Action team: The action team is responsible for screening, prioritizing, and implementing suggested actions from causal analysis meetings.

Each member has a percentage of time allotted for this task. Each action team has a coordinator and a management representative the action team manager. The team uses reports from the action database to guide its meetings.

The action team is the engine of the process. Other than action implementation, the team is involved in feedback to the organization, reports to management on the status of its activities, publishing success stories, and taking the lead in various aspects of the process. The action team relieves the programmers of having to implement their own suggestions, especially actions that have a broad scope of influence and require substantial resources.

Of course, existence of the action team does not preclude action implemented by others. In fact, technical teams are encouraged to take improvement actions, especially those that pertain to their specific areas. Stage kickoff meetings: The technical teams conduct these meetings at the beginning of each development stage. The emphasis is on the technical aspect of the development process and on quality: What is the right process?

How do we do things more effectively? What are the tools and methods that can help? What are the common errors to avoid? What improvements and actions had been implemented? The meetings thus serve two main purposes: Action tracking and data collection: To prevent suggestions from being lost over time, to aid action implementation, and to enhance communications among groups, an action database tool is needed to track action status.

Defect Prevention Process Different from postmortem analysis, the DPP is a real-time process, integrated into every stage of the development process.

Rather than wait for a postmortem on the project, which has frequently been the case, DPP is incorporated into every sub-process and phase of that project. This approach ensures that meaningful discussion takes place when it is fresh in everyone's mind. It focuses on defect-related actions and process-oriented preventive actions, which is very important. Through the action teams and action tracking tools and methodology, DPP provides a systematic, objective, data-based mechanism for action implementation.

It is a bottoms-up approach; causal analysis meetings are conducted by developers without management interference. However, the process requires management support and direct participation via the action teams. Causal analysis of defects along with actions aimed at eliminating the cause of defects are credited as the key factors in these successes Mays et al.

Indeed, the element of defect prevention has been incorporated as one of the "imperatives" of the software development process at IBM. Other companies, especially those in the software industry, have also begun to implement the process. As long as the defects are recorded, causal analysis can be performed and preventive actions mapped and implemented. A study in the application of statistics, probability and distribution to engineering.

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