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Once a solution space is identi ed, the challenge for SEs is being able to accurately and precisely bound and specify it via the System Performance Speci cation (SPS) or entity development speci cation. Our discussion on speci cation development practices provided an approach for identifying types of speci cation requirements. This chapter focuses on the formulation and development of those requirements statements. Our discussions introduce and explore various methods for preparing requirements statements. We identify a syntactic structure to facilitate de nition of a requirement. The discussions emphasize the need to de ne the substantive content of a requirement before focusing on the grammar. To facilitate preparation of requirements, we provide requirements development guidelines and discuss how to test a requirement. We conclude the chapter with a discussion of one of the challenges of speci cation requirements development: knowing WHEN a set of requirements is necessary and suf cient. We explore the need to minimize the quantity of requirements and avoid overspeci cation and underspeci cation.

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1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. What are the attributes of a good requirement When is a requirement of cially recognized as a requirement What are some suggestions for preparing good requirements What is a common pitfall in preparing requirements statements What methodology should one use to create a requirements statement What criteria do you use to test a requirement How do you identify a requirement s veri cation method(s) What is a Requirements Veri cation Matrix (RVM) How do you develop an RVM What is requirements minimization How do you minimize requirements

Table 18.1 Characterization of Alternative Server Architectures MULTITHREADED SERVERS DIALOGDATA-SPECIFIC ORIENTED SERVERS SERVERS

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Investigate what advanced management features are included in or offered by the various virtualization environments you are considering. Examples include the ability to move running virtual machines to other host servers, automate load balancing, set policies for dynamic resource management, and automate intelligent use of resource pools. As virtualization software products mature, these advanced features are becoming the key differentiators between virtual environments.

System Analysis, Design, and Development, by Charles S. Wasson Copyright 2006 by John Wiley & Sons, Inc.

Speci cation Language A language, often a machine-processible combination of natural and formal language, used to express the requirements, design, behavior, or other characteristics of a system or component. For example, a design language or requirements speci cation language. (Source: IEEE 610.12-1990)

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People often say that a speci cation has a good set of requirements. The subjective usage of the term good makes SEs cringe. Good for WHOM relative to WHAT tness-for-use standard(s) The User The System Developer If good requirements are relative to the User, WHAT makes a bad requirement bad Does bad mean poorly stated, open to interpretation, unachievable, immeasurable, unveri able, and untestable What these people are attempting to convey is: GOOD requirement statements are well de ned, explicit, and can be implemented with low risk of misinterpretation. They are well de ned and explicitly stated in a clear and concise manner that results in the same interpretation by two or more independent readers with comparable disciplinary skills.

A well-de ned requirement should consist of several key characteristics, depending on application. It must explicitly express the following, as applicable: 1. 2. 3. 4. 5. 6. 7. 8. 9. The use case based operational capability to the performed. The source of the action. WHAT scenario or conditions for performing the action. WHAT is expected as a performance-based outcome (i.e., WHAT products or services are to be produced). WHAT by-products are to be AVOIDED. WHEN the capability or action is to be initiated. WHO is the expected recipient(s) of the action. WHAT are the expected result(s) and outcome(s). HOW is the outcome to be measured and veri ed.

Resource pools and clustering are often used interchangeably but, in fact, are quite different. Resource pools are created so the resources from within the pool can be allocated to virtual machines or applications by policy-driven software rather than by hand. Clustering, on the other hand, is when multiple physical or virtual entities are used to address a single task. Specific tasks include clustering for high availability or to solve a computational complex problem, as with high performance computing. Often, clustering implementations will draw their resources from resource pools.

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