Advances in Computers

by Zelkowitz

• ISBN13: 9780120121663
• ISBN10: 0120121662
• Format: Hardcover
• Copyright: 2006-05-31
• Publisher: Elsevier Science

Summary

This volume of Advances in Computers is number 66 in the series that began back in 1960. This series presents the ever changing landscape in the continuing evolution of the development of the computer and the field of information processing. Each year three volumes are produced presenting approximately 20 chapters that describe the latest technology in the use of computers today. Volume 66, subtitled Quality software development, is concerned about the current need to create quality software. It describes the current emphasis in techniques for creating such software and in methods to demonstrate that the software indeed meets the expectations of the designers and purchasers of that software.

Table of Contents

CONTRIBUTORS	ix
PREFACE	xiii
Calculating Software Process Improvement's Return on Investment
Rini van Solingen and David F. Rico
1. Introduction	2	(2)
2. Return-on-Investment for Analysing Cost and Benefits	4	(10)
2.1. ROI Metrics	6	(1)
2.2. A Survey of Literature on the ROI Metric for SPI	7	(3)
2.3. Cost of SPI	10	(2)
2.4. Benefits of SPI	12	(1)
2.5. A Priori and A Posteriori ROI Analysis	12	(2)
3. Using Quantitative Models for SPI Decision Making	14	(6)
3.1. Cost Models for SPI	14	(1)
3.2. Benefit Models for SPI	15	(2)
3.3. Modelling Cost and Benefits of SPI	17	(1)
3.4. ROI Models for SPI	18	(1)
3.5. Limitations of the Quantitative Models	19	(1)
4. Using Quantitative Measurements for SPI Investment Evaluations	20	(7)
4.1. Measuring Benefits Is Just as Easy as Measuring Cost	20	(1)
4.2. Involve Stakeholders for Benefit Estimations	21	(1)
4.3. Case 1: GQM-Based Measurement Program	22	(2)
4.4. Case 2: CMM-Based Improvement Program	24	(1)
4.5. Limitations of Quantitative Measurements	25	(2)
5. Conclusions	27	(1)
Acknowledgements	28	(1)
Appendix A: Background of the Quantitative Models	28	(8)
A.1. Inspection: Detailed ROI Estimation Procedures	29	(1)
A.2. PSP': Detailed ROI Estimation Procedures	30	(1)
A.3. TSP': Detailed ROI Estimation Procedures	31	(1)
A.4. SW-CMM®: Detailed ROI Estimation Procedures	32	(1)
A.5. ISO 9001: Detailed ROI Estimation Procedures	33	(2)
A.6. CMMI®: Detailed ROI Estimation Procedures	35	(1)
References	36	(8)
Quality Problem in Software Measurement Data
Pierre Rebours and Taghi M. Khoshgoftaar
1. Introduction	44	(3)
2. Noise-Handling Techniques	47	(4)
2.1. Class-Noise Filters	47	(2)
2.2. Data Noise and Exceptions	49	(1)
2.3. Other Methods to Handle Data Noise	49	(2)
3. Ensemble-Partitioning Filter	51	(5)
3.1. Partitioning the Dataset	51	(1)
3.2. Creation of the Base Learners	51	(2)
3.3. Voting Scheme	53	(1)
3.4. Iterative Approach	54	(1)
3.5. Specialized Filters	55	(1)
3.6. Configuration of the Parameters	56	(1)
4. Modeling Methodology	56	(5)
4.1. Model-Selection Strategy	57	(1)
4.2. Performance Evaluation	57	(1)
4.3. Efficiency Paired Comparison	58	(3)
5. Empirical Evaluation	61	(11)
5.1. System Description	61	(1)
5.2. Creation of the Filters	62	(2)
5.3. Noise Elimination Results	64	(2)
5.4. Performance of the Final Learners	66	(1)
5.5. Results of the Efficiency Paired Comparisons	67	(5)
6. Conclusion	72	(1)
Acknowledgements	73	(1)
References	73	(7)
Requirements Management for Dependable Software Systems
William G. Bail
1. Introduction	80	(4)
2. Dependability	84	(10)
2.1 IFIP WG 10.4	85	(1)
2.2 The Dependability Tree	86	(1)
2.3 Information Assurance (IA)	87	(1)
2.4 Acceptability	88	(3)
2.5 System Quality	91	(1)
2.6 Types of Failure	91	(3)
3. Nature of Requirements	94	(9)
3.1 IEEE Definition of Requirements	94	(2)
3.2 Derivation of Requirements	96	(4)
3.3 Hierarchies of Requirementss	100	(3)
4. Categories of Requirements	103	(12)
4.1. Behavioral Requirements	106	(5)
4.2. Quality of Construction Requirements	111	(1)
4.3. Implementation Requirements	112	(2)
4.4. Programmatic Requirements	114	(1)
5. Handling Requirements	115	(3)
5.1. Overview of Development Processes	115	(2)
5.2. Effect of Requirements on Development Processes	117	(1)
6. Requirements Quality Attributes	118	(8)
6.1. Complete	119	(2)
6.2. Unambiguous	121	(1)
6.3. Correct	121	(1)
6.4. Consistent	122	(1)
6.5. Verifiable	122	(1)
6.6. Modifiable	123	(1)
6.7. Traceable	124	(1)
6.8. Ranked for Importance	125	(1)
6.9. Ranked for Stability	126	(1)
7. Requirements and Dependability	126	(1)
8. Common Requirements Challenges	127	(11)
8.1. Requirements Not Matching Users' Real Needs	128	(1)
8.2. Volatile and Late-Defined Requirements	129	(3)
8.3. Unknown "Physics" for Embedded Systems	132	(1)
8.4. Fear of Excessive Detail	133	(1)
8.5. Test Environment Does Not Match Operational Environment	134	(1)
8.6. Ineffective and Unusable Human–Computer Interfaces	135	(2)
8.7. Over-Specified/Over-Constrained/Unbounded	137	(1)
9. Summary	138	(1)
References	139	(5)
Mechanics of Managing Software Risk
William G. Bail
1. Introduction	144	(1)
2. Project Planning	145	(4)
3. Fundamentals of Risk	149	(7)
3.1. Formal Definition of Risk	150	(2)
3.2. Risk Likelihood	152	(1)
3.3. Risk Impact	153	(3)
4. Sources of Risk	156	(5)
5. Handling Risks	161	(7)
5.1. Risk Levels	161	(4)
5.2. Risk Mitigation	165	(3)
6. Conclusion	168	(2)
References	170	(5)
The PERFECT Approach to Experience-Based Process Evolution
Brian A. Nejmeh and William E. Riddle
1. Introduction	175	(2)
2. Improvement Game Plans	177	(4)
3. Process Evolution	181	(1)
3.1. Process Evolution Focus and Intent	181	(1)
3.2. The Nature of Process Evolution	182	(1)
3.3. Process Evolution Requirements	182	(1)
4. The PEDAL Framework	182	(15)
4.1. A General View of Process Evolution	183	(2)
4.2. Process Evolution Stages	185	(4)
4.3. Process-Related Information	189	(1)
4.4. The PEDAL Framework	190	(7)
5. Describing Process Evolution Dynamics	197	(16)
5.1. Process Evolution Description Case Studies	197	(9)
5.2. Observations	206	(2)
5.3. Lessons Learned	208	(1)
5.4. Process Evolution Description	209	(4)
6. Process Evolution Infrastructure	213	(11)
6.1. Additional Assets	213	(2)
6.2. Process Information Gathering	215	(503)
6.3. Activity Category-Specific Support	718	(52)
6.4. Process Change Team Support	770
6.5. Process Evolution Infrastructure Summary	224	(1)
7. Value and Future Improvements	224	(9)
7.1. Value of PEDAL and PERFECT	225	(1)
7.2. Improvements	226	(504)
7.3. Game Plan Focusing	730
7.4. Process Visualization	231	(1)
7.5. Process Evolution Planning and Management	232	(1)
8. Summary	233	(2)
Acknowledgements	235	(1)
References	235	(5)
The Opportunities, Challenges, and Risks of High Performance Computing in Computational Science and Engineering
Douglass E. Post, Richard P. Kendall, and Robert F. Lucas
1. Introduction	240	(2)
2. Computational Science and Engineering Analysis	242	(1)
3. General Characteristics of a Large Scale Computational Simulation	243	(5)
4. FALCON: An Example of a Large-Scale Scientific Code Project	248	(9)
4.1. FALCON Characteristics	248	(2)
4.2. FALCON Life Cycle	250	(2)
4.3. Workflows and Tasks	252	(4)
4.4. "Lessons Learned" from the FALCON Project	256	(1)
4.5. Observations and Conclusions for the FALCON Project Case Study	256	(1)
5. The Challenges Facing Computational Science and Engineering	257	(19)
5.1. The Performance Challenge	257	(5)
5.2. The Programming Challenge	262	(3)
5.3. The Prediction Challenge	265	(4)
5.4. Scientific Software Characteristics and Issues	269	(2)
5.5. Success Is not Guaranteed!	271	(3)
5.6. The Development Challenge	274	(2)
6. A Comparative Case Study	276	(8)
6.1. Quantitative Estimation	279	(5)
7. Verification and Validation	284	(6)
7.1. Verification	284	(2)
7.2. Validation	286	(4)
8. Software Quality and Software Project Management	290	(5)
9. Conclusions and Path Forward	295	(2)
Acknowledgements	297	(1)
References	297	(6)
AUTHOR INDEX	303	(8)
SUBJECT INDEX	311	(12)
CONTENTS OF VOLUMES IN THIS SERIES	323