SAS Data Analytic Development: Dimensions of Software Quality (Wiley and SAS Business Series)

SAS Data Analytic Development: Dimensions of Software Quality (Wiley and SAS Business Series)

By: Troy Martin Hughes (author)Hardback

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Design quality SAS software and evaluate SAS software quality SAS Data Analytic Development is the developer s compendium for writing better-performing software and the manager s guide to building comprehensive software performance requirements. The text introduces and parallels the International Organization for Standardization (ISO) software product quality model, demonstrating 15 performance requirements that represent dimensions of software quality, including: reliability, recoverability, robustness, execution efficiency (i.e., speed), efficiency, scalability, portability, security, automation, maintainability, modularity, readability, testability, stability, and reusability. The text is intended to be read cover-to-cover or used as a reference tool to instruct, inspire, deliver, and evaluate software quality. A common fault in many software development environments is a focus on functional requirements the what and how to the detriment of performance requirements, which specify instead how well software should function (assessed through software execution) or how easily software should be maintained (assessed through code inspection). Without the definition and communication of performance requirements, developers risk either building software that lacks intended quality or wasting time delivering software that exceeds performance objectives thus, either underperforming or gold-plating, both of which are undesirable. Managers, customers, and other decision makers should also understand the dimensions of software quality both to define performance requirements at project outset as well as to evaluate whether those objectives were met at software completion. As data analytic software, SAS transforms data into information and ultimately knowledge and data-driven decisions. Not surprisingly, data quality is a central focus and theme of SAS literature; however, code quality is far less commonly described and too often references only the speed or efficiency with which software should execute, omitting other critical dimensions of software quality. SAS(R) software project definitions and technical requirements often fall victim to this paradox, in which rigorous quality requirements exist for data and data products yet not for the software that undergirds them. By demonstrating the cost and benefits of software quality inclusion and the risk of software quality exclusion, stakeholders learn to value, prioritize, implement, and evaluate dimensions of software quality within risk management and project management frameworks of the software development life cycle (SDLC). Thus, SAS Data Analytic Development recalibrates business value, placing code quality on par with data quality, and performance requirements on par with functional requirements.

About Author

TROY MARTIN HUGHES has been a SAS practitioner for more than 15 years, has managed SAS projects in support of federal, state, and local government initiatives, and is a SAS Certified Advanced Programmer, SAS Certified Base Programmer, SAS Certified Clinical Trials Programmer, and SAS Professional V8. He has an MBA in information systems management and additional credentials, including: PMP, PMI-ACP, PMI-PBA, PMI-RMP, CISSP, CSSLP, CSM, CSD, CSPO, CSP, and ITIL v3 Foundation. He has been a frequent presenter and invited speaker at SAS user conferences, including SAS Global Forum, WUSS, MWSUG, SCSUG, SESUG, and PharmaSUG. Troy is a U.S. Navy veteran with two tours of duty in Afghanistan, and in his spare time, a volunteer firefighter and EMT.


Preface xi Acknowledgments xvi About the Author xvii Chapter 1 Introduction 1 Distinguishing Data Analytic Development 3 Software Development Life Cycle (SDLC) 7 Risk 14 Chapter 2 Quality 21 Defining Quality 24 Software Product Quality Model 30 Quality in the SDLC 40 Chapter 3 Communication 49 Return Codes 51 System Numeric Return Codes 53 System Alphanumeric Return Codes 70 User-Generated Return Codes 74 Parallel Processing Communication 79 PART I DYNAMIC PERFORMANCE 85 Chapter 4 Reliability 87 Defining Reliability 90 Paths to Failure 91 ACL: The Reliability Triad 102 Reliability in the SDLC 108 Chapter 5 Recoverability 123 Defining Recoverability 125 Recoverability toward Reliability 127 Recoverability Matrix 131 TEACH Recoverability Principles 132 SPICIER Recoverability Steps 136 Recovering with Checkpoints 148 Recoverability in the SDLC 151 Chapter 6 Robustness 159 Defining Robustness 162 Robustness toward Reliability 163 Defensive Programming 164 Exception Handling 172 Robustness in the SDLC 203 Chapter 7 Execution Efficiency 207 Defining Execution Efficiency 209 Factors Affecting Execution Efficiency 210 False Dependencies 211 Parallel Processing 220 Execution Efficiency in the SDLC 232 Chapter 8 Efficiency 243 Defining Efficiency 246 Disambiguating Efficiency 246 Defining Resources 249 Efficiency in the SDLC 259 Chapter 9 Scalability 273 Defining Scalability 276 The Scalability Triad 276 Resource Scalability 278 Demand Scalability 279 Load Scalability 290 Scalability in the SDLC 309 Chapter 10 Portability 313 Defining Portability 316 Disambiguating Portability 317 3GL versus 4GL Portability 318 Facets of Portability 319 Portability in the SDLC 338 Chapter 11 Security 341 Defining Security 344 Confidentiality 344 Integrity 345 Availability 365 Security in the SDLC 379 Chapter 12 Automation 383 Defining Automation 386 Automation in SAS Software 387 SAS Processing Modes 388 Starting in Interactive Mode 393 Starting in Batch Mode 410 Automation in the SDLC 415 PART II STATIC PERFORMANCE 419 Chapter 13 Maintainability 421 Defining Maintainability 424 Maintenance 425 Maintenance in the SDLC 429 Failure to Maintain 436 Maintainability 440 Chapter 14 Modularity 447 Defining Modularity 449 From Monolithic to Modular 450 Modularity Principles 454 Benefits of Modularity 474 Chapter 15 Readability 477 Defining Readability 479 Plan to Get Hit by a Bus 480 Software Readability 481 External Readability 503 Chapter 16 Testability 507 Defining Testability 510 Software Testing 510 Testability 538 Chapter 17 Stability 541 Defining Stability 543 Achieving Stability 544 Stable Requirements 545 Defect-Free Code 546 Dynamic Flexibility 546 Stability and Beyond 549 Modularizing More Than Macros 559 Chapter 18 Reusability 577 Defining Reusability 579 Reuse 580 Reusability 588 From Reusability to Extensibility 597 Index 603

Product Details

  • ISBN13: 9781119240761
  • Format: Hardback
  • Number Of Pages: 624
  • ID: 9781119240761
  • weight: 1022
  • ISBN10: 111924076X

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