An approach for quantitative aggregation of evidence from controlled experiments in software engineering:
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Hochschulschrift/Dissertation Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Stuttgart
Fraunhofer-Verl.
2012
|
| Schriftenreihe: | PhD theses in experimental software engineering
42 |
| Schlagwörter: | |
| Links: | http://deposit.dnb.de/cgi-bin/dokserv?id=4220825&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027800762&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XII, 233 S. graph. Darst. 24 cm |
| ISBN: | 9783839604809 383960480X |
Internformat
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Datensatz im Suchindex
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|---|---|
| adam_text | IMAGE 1
TABLE OF CONTENTS
1 INTRODUCTION 1
1.1 MOTIVATION 1
1.2 STATE OF THE PRACTICE AND STATE O F THE ART 5
1.2.1 STATE O F THE PRACTICE 5
1.2.2 STATE OF THE ART 6
1.3 RESEARCH OBJECTIVES 7
1.3.1 PROBLEM STATEMENTS 8
1.3.2 THESIS GOALS 9
1.3.3 THESIS SCOPE 10
1.4 RESEARCH APPROACH AND METHOD 13
1.5 RESEARCH CONTRIBUTIONS 14
1.6 EVALUATION GOALS 16
1.7 THESIS STRUCTURE 19
2 STATE OF THE PRACTICE 21
2.1 BACKGROUND 21
2.2 AGGREGATION O F EVIDENCE AS SOLUTION IDEA 25
2.3 AGGREGATION IN SOFTWARE ENGINEERING 27
2.4 STATE-OF-THE-PRACTICE AGGREGATION APPROACH: NARRATIVE REVIEW 29
2.5 PROBLEMS AND REQUIREMENTS 3 4
2.5.1 CHALLENGES 34
2.5.2 PROBLEMS 36
2.5.3 REQUIREMENTS FOR AGGREGATION APPROACHES IN SOFTWARE ENGINEERING 37
2.5.4 MAPPING TO PROBLEMS AND GOALS 39
2.6 SUMMARY 39
3 STATE OF THE ART 41
3.1 VOTE COUNTING 41
3.1.1 METHOD DESCRIPTION 41
3.1.2 EXAMPLE 43
3.1.3 EVALUATION 4 4
V
HTTP://D-NB.INFO/1029253900
IMAGE 2
3.2 COMBINED SIGNIFICANCE TESTS 47
3.2.1 METHOD DESCRIPTION 47
3.2.2 EXAMPLE 48
3.2.3 EVALUATION 49
3.3 META-ANALYSIS 51
3.3.1 METHOD DESCRIPTION 51
3.3.2 EXAMPLE 53
3.3.3 EVALUATION 54
3.4 BPCH/EMPEROR 57
3.4.1 METHOD DESCRIPTION 57
3.4.2 EXAMPLE 59
3.4.3 EVALUATION 59
3.5 COMPARISON 61
3.6 SUMMARY 63
4 THE FUSE APPROACH FOR GOAL-ORIENTED AGGREGATION 65
4.1 SOLUTION IDEA 65
4.2 OVERVIEW AGGREGATION PROCESS 67
4.3 STEP 1: DEFINE GOAL 70
4.3.1 EXAMPLE 72
4.4 STEP 2: PLAN AGGREGATION 72
4.4.1 DEFINE A SEARCH STRATEGY 73
4.4.2 DESIGN DATA COLLECTION FORMS 73
4.4.3 EXAMPLE 7 4
4.5 STEP 3: FIND AND SELECT EVIDENCE 7 4
4.5.1 FIND EVIDENCE 7 4
4.5.2 ASSESS EVIDENCE QUALITY 75
4.6 STEP. 4: STANDARDIZE EVIDENCE 76
4.6.1 STANDARDIZE EVIDENCE FOR COMPLETE INFORMATION: COMPUTE SINGLE
EFFECT SIZES 7 8
4.6.2 STANDARDIZE EVIDENCE FOR INCOMPLETE INFORMATION: ESTIMATION
OPERATORS TO ESTIMATE SINGLE EFFECT SIZES 7 9
4.6.3 EXAMPLE 82
4.7 STEP 5: AGGREGATE EVIDENCE (HOLISTIC AGGREGATION) 83
4.7.1 COMBINE EFFECT SIZES 85
4.7.2 DETECT INCONSISTENCIES: ASSESS HETEROGENEITY 87
4.7.3 EXPLAIN INCONSISTENCIES: ANALYZE VARIATION FACTORS... 89
VI
IMAGE 3
4.8 STEP 5: AGGREGATE EVIDENCE (INCREMENTAL AGGREGATION).... 9 4
4.8.1 AGGREGATION STATES AND INCREMENTAL AGGREGATION OPERATORS 95
4.8.2 DETECTING AND EXPLAINING INCONSISTENCIES: MODER ATOR ANALYSES 99
4.8.3 APPLICATION SCENARIO: UPDATE AGGREGATION W I T H ATOMIC EVIDENCE
100
4.8.4 SUMMARY: INCREMENTAL AGGREGATION 106
4.9 STEP 6: PACKAGE 107
4.9.1 CREATE DECISION MODEL 107
4.9.2 EXAMPLE 108
4.10 CONCEPTS FOR VISUALIZING AGGREGATION OUTCOMES 109
4.10.1 VISUALIZING AGGREGATION RESULTS 109
4.10.2VISUALIZING THE AGGREGATION STRUCTURE 114
4.10.3VISUALIZATION FOR PLANNING 116
4.10.4SUMMARY OF VISUALIZATION CONCEPTS 119
4.11 SUMMARY OF THE FUSE APPROACH 121
5 EVALUATION 123
5.1 EVALUATION GOALS AND HYPOTHESES 123
5.2 PROOF: CORRECTNESS O F AGGREGATION OPERATORS 127
5.2.1 CONTEXT AND GOAL 127
5.2.2 PROOF FOR EVALUATION GOAL EG 1.2 128
5.2.3 PROOF FOR EVALUATION GOAL EG 1.1 129
5.2.4 SUMMARY 132
5.3 STUDY 1: INTUITIVENESS OF AGGREGATION RESULTS 133
5.3.1 STUDY CONTEXT AND EVALUATION GOAL 133
5.3.2 COMPARISON O F AGGREGATION AND POOLED RAW DATA .. 133
5.3.3 SUMMARY :.... 136
5.4 SYSTEMATIC LITERATURE REVIEW: EFFECTIVENESS O F PBR 136
5.4.1 STUDY CONTEXT AND EVALUATION GOAL 137
5.4.2 DEFINE AGGREGATION GOAL 137
5.4.3 EXISTING SUMMARIES O F PBR EFFECTIVENESS 138
5.4.4 SELECT AND ASSESS EVIDENCE 140
5.4.5 STANDARDIZE EVIDENCE 142
5.4.6 AGGREGATE EVIDENCE 143
5.4.7 ANALYSIS O F EVALUATION GOALS 151
5.4.8 DISCUSSION 158
5.4.9 STUDY SUMMARY 161
VII
IMAGE 4
5.4.10EVALUATION GOALS SUMMARY 162
5.5 USEFULNESS STUDY: POTENTIALITY ANALYSIS 163
5.5.1 POTENTIAL T O SUPPORT TECHNOLOGY DECISIONS 163
5.5.2 POTENTIAL T O SUPPORT PLANNING O F STUDIES 168
5.5.3 USEFULNESS ANALYSIS SUMMARY 170
5.6 EVALUATION SUMMARY 171
5.6.1 SUMMARY OF EVALUATION RESULTS 171
5.6.2 FULFILLMENT O F REQUIREMENTS 174
5.6.3 LIMITATIONS 176
6 CONCLUSION AND FUTURE WORK 177
6.1 SUMMARY AND CONCLUSION 177
6.2 OPEN QUESTIONS AND FUTURE WORK 181
A GLOSSARY OF TERMS 185
B CONCEPTUAL MODEL 191
B.1 DATA MODEL 191
B.2 VISUALIZATION CONCEPTS 192
B.2.1 REPRESENTATION O F QUANTITATIVE INFORMATION 192
B.2.2 TRUST VISUALIZATION 193
B.2.3 VISUALIZATION O F STRUCTURE 193
B.3 VISUALIZATION FOR PLANNING: EXPLORATION 195
C DATA ANALYSIS MATERIALS 197
C.1 OVERVIEW OF PBR TEAM EFFECTIVENESS DATA 198
C.2 PBR MODERATOR ANALYSIS: EFFECT SIZE DATA 199
C.3 PBR MODERATOR ANALYSIS: HETEROGENEITY AND VARIANCE 207
C.4 DENDROGRAM 215
REFERENCES 217
VIII
|
| any_adam_object | 1 |
| author | Ciolkowski, Marcus 1973- |
| author_GND | (DE-588)1030069018 |
| author_facet | Ciolkowski, Marcus 1973- |
| author_role | aut |
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| dewey-full | 005.1 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
| dewey-raw | 005.1 |
| dewey-search | 005.1 |
| dewey-sort | 15.1 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Thesis Book |
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| indexdate | 2024-12-20T17:09:16Z |
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| language | English |
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| publishDate | 2012 |
| publishDateSearch | 2012 |
| publishDateSort | 2012 |
| publisher | Fraunhofer-Verl. |
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| series | PhD theses in experimental software engineering |
| series2 | PhD theses in experimental software engineering |
| spellingShingle | Ciolkowski, Marcus 1973- An approach for quantitative aggregation of evidence from controlled experiments in software engineering PhD theses in experimental software engineering Requirements engineering (DE-588)4213997-1 gnd Aggregation (DE-588)4000728-5 gnd Empirische Forschung (DE-588)4300400-3 gnd Leistungsbewertung (DE-588)4167271-9 gnd Beweis (DE-588)4132532-1 gnd Software Engineering (DE-588)4116521-4 gnd |
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| title | An approach for quantitative aggregation of evidence from controlled experiments in software engineering |
| title_auth | An approach for quantitative aggregation of evidence from controlled experiments in software engineering |
| title_exact_search | An approach for quantitative aggregation of evidence from controlled experiments in software engineering |
| title_full | An approach for quantitative aggregation of evidence from controlled experiments in software engineering von Marcus Ciolkowski |
| title_fullStr | An approach for quantitative aggregation of evidence from controlled experiments in software engineering von Marcus Ciolkowski |
| title_full_unstemmed | An approach for quantitative aggregation of evidence from controlled experiments in software engineering von Marcus Ciolkowski |
| title_short | An approach for quantitative aggregation of evidence from controlled experiments in software engineering |
| title_sort | an approach for quantitative aggregation of evidence from controlled experiments in software engineering |
| topic | Requirements engineering (DE-588)4213997-1 gnd Aggregation (DE-588)4000728-5 gnd Empirische Forschung (DE-588)4300400-3 gnd Leistungsbewertung (DE-588)4167271-9 gnd Beweis (DE-588)4132532-1 gnd Software Engineering (DE-588)4116521-4 gnd |
| topic_facet | Requirements engineering Aggregation Empirische Forschung Leistungsbewertung Beweis Software Engineering Hochschulschrift |
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