Automated Software Performance

Overview

Automated Software Performance is written for information data center management, quality assurance professionals, and both systems and applications technical staff. It provides a comprehensive guide to automating the measurement of software quality and reliability, as well as programmer productivity using conventional system log technology as the means to monitor and track software quality improvement. It can be used to assist in implementing a cost-effective Total Quality Management (TQM) program for any host ...
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Overview

Automated Software Performance is written for information data center management, quality assurance professionals, and both systems and applications technical staff. It provides a comprehensive guide to automating the measurement of software quality and reliability, as well as programmer productivity using conventional system log technology as the means to monitor and track software quality improvement. It can be used to assist in implementing a cost-effective Total Quality Management (TQM) program for any host data center, which is based upon proven capacity planning and performance analysis methods using SMF, RMF, SAS, MXG, MICS and other system performance analysis tools approved and recommended by the Computer Measurement Group (CMG) and IBM Guide user groups. Vendor ASQM products are demonstrated, along with methods and tips that can be used to develop your own ASQM software using SAS (Statistical Analysis Systems) language. It answers many questions that are commonly asked by information data center management, and provides a handy back-up reference for seasoned professional mainframe network capacity planning and computer performance evaluation analysts, as well as novice performance specialists.
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Product Details

  • ISBN-13: 9781583484609
  • Publisher: iUniverse, Incorporated
  • Publication date: 1/21/2000
  • Edition number: 2
  • Pages: 340
  • Product dimensions: 8.25 (w) x 11.00 (h) x 0.71 (d)

Table of Contents

Preface vii
Acknowledgments ix
1. Measuring All the Things That Computers Manage 1
Things Computers Must Measure in Order to Manage Themselves 1
Basic Functions Common to All Computer Operating Systems 2
Metrics Associated with Basic Computer Operating System Functions 3
Operating Systems as the Silent Supervisors of Computer Systems 3
How Operating Systems Log Their Data Processing Activities 4
How Business Operations Use Computer Operating System Log Data 6
Linking Operating System Log Data to Lower Business Process Cost 8
Elimination of a Bottleneck in Completing a Critical Process 10
Finding Resource-Intensive Programs in Routinely Processed Jobs 11
Reducing the Volume of Input/Output for Blocked Datasets 13
Finding Dominant Cause of Repeated Program Abend Dumps 16
Notifying Programmers of Other Programmers' Changes to JCL 17
Verifying System Development Projects Are Still on Schedule 18
Eliminating Delay in Loading an Online Database for Update 18
Finding Excessive Paper Usage and Optimizing of Reports 20
Identifying the Savings Potential from a New Storage Device 20
Eliminating Excessive Tape-Waits for Critical Datasets 20
Customer Demographic Survey and Technology Needs Assessment 21
Finding Customer Areas That Need Attention to Terminal Needs 21
How to Capture and Accumulate System Audit Log Data 22
System Accounting Standards Needed for Software Metric Automation 38
2. Vendor Products That Manage Software Quality Measurement Data 41
Vendor System Log Performance Data Administration Product: MXG 42
Vendor System Performance Database Management Product: MICS 57
3. Turning Software Failures Into Systematic Success 79
How Computers Know When Something Has Gone Wrong 79
What Kinds of Problems Can Operating Systems Detect? 82
Measuring and Controlling Catastrophic System Failures 83
Measuring Levels of System Fault Tolerance 85
Measuring the Impact of Human Errors 90
Customizing Error Codes to Log Special Program Actions 91
Determining the Cost of Software Errors 93
Predicting Software Failure Rates for Managing Impact of Errors 94
Isolating the Impact of Software Failures 96
4. Vendor Products that Help Manage Software Errors 101
Vendor Application Program Failure Analysis Product: ABEND-AID 101
Vendor Application Program Efficiency Optimizer Product: Strobe 112
5. Getting to the Source of Your Software Quality 129
How Programs Get Executed by Computer Operating Systems 129
High-Level Language Coding Interpretation by Operating Systems 130
How Compilers and Interpreters Measure Program Characteristics 134
How System Logs Measure Execution of Program Modules 134
Measuring the Size of High-Level Program Modules 135
High-Level Program Library Archival and Sourcecode Storage 144
Measuring Functional Compliexity of Application Program Modules 145
Standardizing Program Sourcecode for Maximum Efficiency 146
Benchmarking and Baseline Comparison of Application Software 151
6. Vendor Products that Help Measure Program Sourcecode 153
Vendor Product to Measure Program Sourcecode Quality: Q/AUDITOR 153
Vendor Product to Help Measure Program Source Objects: FILE-AID 162
7. Sizing Up Your Software Against the Competition 169
Software Industry Databases and Comparative Information Sources 170
Vendor Software Performance Benchmarks and Calibration Methods 172
Productivity Indexes and Software Industry Quality Baselines 173
Business Process Benchmarks and Business Unit Comparisons 174
Process Benchmark Index for Comparison to External Business Units 180
Forecasting Future Internal and External Software Quality Costs 182
Pareto Ranking Method for Comparing Predominant Process Influence 184
Software Demographics to Describe Business Unit Process Costs 186
Demographic Penetration Data for Gauging Spread of New Technology 188
System Process Quality Index for Internal Comparison of Software 188
8. Vendor Services to Integrate Benchmark Databases 191
Vendor Service to Assist Data Center Benchmarking: KPMG 192
Vendor Services Providing System Development Project Benchmarks 205
9. Understanding the Limits of Your Software 207
The Importance of Consistency to Industrial Production Processes 207
Importance of Consistency to Computer System Operation Throughput 209
Managing Mass Production to Achieve Systematic Economies of Scale 211
Determining Critical Descriptive Software Quality Control Limits 214
Measuring Critical Trending Limits for System Management Control 214
Control-Delimited Threshold Management of Computer Operations 216
Measuring Production Operations to Achieve Scaled Efficiency 219
Managing Limited Production to Achieve Special Process Function 219
Measuring Ad Hoc Workloads for Standardizing Nonconventional Tasks 221
10. Vendor Products to Control Software Quality 223
Vendor Statistical Quality Control Reporting Product: SAS/QC 224
Vendor Statistical Process Control Reporting Product: SPC-PC 224
11. Valuing Software in Your In-House System Inventory 231
Historical Perspective of Valuing and Pricing In-House Software 231
Mediating Influences That Adjust the Value of Software 233
Importance of Proprietary Influences upon Value of Software 234
Relationship of Value to Financing of Software Acquisitions 234
Functionality and Use of Software Size Metrics to Assign Value 235
The Table-of-Elements Model of Assigning Value Based on Language 236
Automated Methods of Collecting and Updating Software Inventories 236
Capital Property Improvement Models Based on Real Estate 237
Tying Automated Software Valuations to Life-Cycle Decision Making 240
Vendors That Can Assist in Inventory Management of Software 241
12. Managing Automated Software Factories of the Future 243
What Software Factories of the Future May Look Like 243
Visions of the Software Factory of the Future 244
IBM's Host-Based Information Warehouse of the Future 245
IBM's Application Development Factory of the Future: AD/CYCLE 246
Software Factories of the Future and Software Engineering 247
Telecommunications Industry Impact Upon Traditional Data Centers 248
Upcoming Changes in the Nature of Programs and Programming 253
Potential Impact of Increasing Regulation of Information Industry 254
How System Log Measurement Data May Change in the Future 255
How System Logs Will Fit into Software Factories of the Future 256
Appendix A Automated Software Quality Metrics Product and Service Vendors 257
Appendix B Automated Software Quality Measurement Support Organizations 269
Appendix C Automated Software Quality Measurement Basic SAS Language Toolkit 277
Appendix D Software Problem Management and Program Failure Codes 287
Appendix E Automated Software Quality Measurements Annotated Bibliography 309
Index 317
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