Modeling software failures during systematic testing: the influence of environmental factors
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
Aachen
Shaker
2003
|
| Schriftenreihe: | Berichte aus der Wirtschaftsinformatik
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XVI, 262 S. graph. Darst. |
| ISBN: | 3832220356 |
Internformat
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Datensatz im Suchindex
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| adam_text | Contents
List of figures viii
List of tables x
Frequently used notation xi
1 Introduction 1
2 Software reliability models and testing 3
2.1 Introduction to the chapter 3
2.2 Important concepts in software reliability engineering 4
2.3 Operational versus systematic testing 6
2.3.1 Operational testing 6
2.3.1.1 Brief method description 6
2.3.1.2 Advantages and disadvantages of operational testing 7
2.3.2 Systematic testing 9
2.3.2.1 Black box techniques 10
2.3.2.2 White box techniques 10
2.3.2.3 Advantages and disadvantages of systematic testing 13
2.4 A survey of software reliability growth models 14
2.4.1 Jelinski Moranda model 14
2.4.2 Goel Okumoto model 15
2.4.3 Models with a time varying testing effort 16
2.4.4 Musa basic execution time model 18
2.4.5 Characteristics of the fault exposure ratio 19
2.4.6 Musa Okumoto model 21
2.4.7 Enhanced non homogeneous Poisson process framework 22
2.4.8 Approach by Piwowarski et al 24
2.4.9 Rivers Vouk model 26
2.5 A model framework 30
ii Contents
2.6 Testing techniques and structural coverage 33
2.7 Concluding remarks 35
3 The partial redundancy models 37
3.1 Introduction to the chapter 37
3.2 The basic partial redundancy model 38
3.2.1 Approximated expected structural coverage 39
3.2.2 The distribution of the number of code constructs covered 42
3.2.3 Exact expected structural coverage 46
3.3 Extended partial redundancy models 48
3.3.1 The first extended partial redundancy model 49
3.3.1.1 The approximated expected number of failure occurrences ... 50
3.3.1.2 The distribution of the number of failure occurrences 50
3.3.1.3 The exact expected number of failure occurrences 53
3.3.2 The second extended partial redundancy model 54
3.3.2.1 The approximated number of expected failure occurrences ... 55
3.3.2.2 The distribution of the number of failure occurrences 56
3.3.2.3 The exact expected number of failure occurrences 61
3.4 Including the models in the model framework 63
3.5 Model estimation 64
3.5.1 General remarks 64
3.5.2 Least squares estimation 66
3.5.2.1 Fitting the cumulative number of failure occurrences 66
3.5.2.2 Fitting the number of failure occurrences per test case 67
3.5.3 Maximum likelihood estimation 68
3.5.3.1 Interpreting the partial redundancy models as NHPP models . . 68
3.5.3.2 Maximizing the likelihood implied by the model setup 69
3.5.4 Staged estimation procedures 73
3.5.4.1 Stage 1: Estimating the basic partial redundancy model .... 73
3.5.4.2 Stage 2: Estimating the extended partial redundancy models . . 75
3.6 Analyzing model performance 77
3.6.1 The models and the estimation procedures 77
3.6.2 The data sets 78
3.6.3 The criteria 78
3.6.3.1 Measures of the deviations of predictions 78
3.6.3.2 Measures of noise 80
3.6.3.3 Measures based on the likelihood function 81
Contents iii
3.6.3.4 The estimated fraction of detectable faults discovered 82
3.6.4 The results 83
3.7 Concluding remarks 88
4 Software process maturity models 91
4.1 Introduction to the chapter 91
4.2 The Capability Maturity Model for Software 92
4.2.1 History 92
4.2.2 The reference model 93
4.2.3 How to conduct appraisals 97
4.2.4 Expected benefits of increased process maturity 98
4.2.5 Criticisms of the SW CMM 99
4.2.6 Empirical evidence 100
4.2.6.1 Case studies and surveys 100
4.2.6.2 Statistical analyses of reliability 101
4.2.6.3 Statistical analyses of validity 102
4.3 Emerging standard ISO/IEC 15504 103
4.3.1 History 103
4.3.2 The reference model 104
4.3.3 An assessment model and how to perform assessments 108
4.3.4 Expected benefits of increased process capability 109
4.3.5 Criticisms of the emerging standard ISO/IEC 15504 110
4.3.6 Empirical evidence 110
4.3.6.1 Statistical analyses of reliability Ill
4.3.6.2 Statistical analyses of validity 113
4.4 Assessing process capability in the PETS project 113
4.4.1 Basic decisions 113
4.4.2 Capability questions in the PETS questionnaire 115
4.4.3 Analyzing the reliability of the capability questions 117
4.4.4 Analyzing the validity of the capability questions 120
4.5 Concluding remarks 123
5 The influence of environmental factors 125
5.1 Introduction to the chapter 125
5.2 The data sets 127
5.3 Influence on the estimated fault density 129
5.3.1 Bivariate analyses of software development process capability 129
5.3.2 Bivariate analyses of other environmental factors 131
iv Contents
5.3.3 Multivariate analyses 136
5.4 Influence on the estimated redundancy level 140
5.4.1 Bivariate analyses 140
5.4.2 Multivariate analyses 147
5.5 Concluding remarks 152
6 Conclusions and outlook 153
A Proofs and derivations 155
A.I Mean value function of the model by Yamada et al 155
A.2 Mean value function of the discrete Rivers Vouk model 156
A.3 Recursive formulations of expected values 156
A.3.1 First extended partial redundancy model 156
A.3.2 Second extended partial redundancy model 162
A.4 Relationship between E(Mt) and £(~j) 164
B Information on the data sets 167
B.I Project A 168
B.2 Project B 169
B.3 Project C 172
B.4 Project D 173
B.5 Project E 174
B.6 Project F 176
B.7 Project G 177
B.8 Project H 178
B.9 Project I 179
B.10 Project J 180
B.ll Project K 181
B.12 Project L 182
B.13 Project M 183
B.14 Project N 185
B.15 Project O 188
B.16 Project P 189
C Tables of model performance measures 191
C.I Project A 193
C.2 Project B 194
C.3 Project C 195
Contents v
C.4 Project D 196
C.5 Project E 197
C.6 Project F 200
C.7 Project G 201
C.8 Project H 202
C.9 Project I 203
CIO Project J 204
C.ll Project K 205
C.12 Project L 206
C.13 Project M 207
C.14 Project N 210
C.15 Project O 216
C.16 Project P 217
D Elements of semantic data modeling 221
E The PETS questionnaire 223
Bibliography 251
List of figures
2.1 Models included in the continuous variant of the model framework 32
2.2 Models included in the discrete variant of the model framework 33
2.3 Expected structural coverage growth in the approach by Piwowarski et al. and in
the Rivers Vouk model for G=1000 and p=10 34
3.1 Structure of the basic partial redundancy model 39
3.2 Probability mass functions ofQt for G = 100, p = 10 and r = 1 calculated via
the closed form expression (|) and recursively (o) 45
3.3 Probability mass functions o/Qioo for G = 1000, p = 10 and various redundancy
levels r 46
3.4 Expected structural coverage growth in the basic partial redundancy model for
G = 1000, p = 10 and various redundancy levels r 48
3.5 Structure of the first extended partial redundancy model 49
3.6 Probability mass functions of Mioo according to the first extended model for
G = 1000, p = 10, Uo = 100 and various redundancy levels r and activation
probabilities s 53
3.7 Structure of the second extended partial redundancy model 54
3.8 Probability mass functions of Mioo according to the second extended model for
G = 1000, p = 10, Uo = 100 and various redundancy levels r and activation
probabilities s 59
3.9 Expected number of failure occurrences in the first and second extended partial
redundancy model for G = 1000, p = 10, u0 = 100, r = 0.9 and s = 0.5 62
4.1 Maturity levels and related key process areas in the SW CMM 95
4.2 Structure of the SW CMM reference model 96
4.3 Expected benefits of increased software process maturity 99
4.4 Capability levels and related process attributes in the ISO/IEC TR 15504 refer¬
ence model 106
4.5 Structure of the ISO/IEC TR 15504 reference and assessment models 107
viii List of figures
4.6 Box and whisker plot of the deviations of the mean scores from the normalized
summative scores 122
B.I Project A, failure data 168
B.2 Project B, raw failure data 169
B.3 Project B, testing effort and number of failure occurrences per test case 170
B.4 Project B, adjusted failure data 171
B.5 Project C, failure data 172
B.6 Project D, failure data 173
B.7 Project E (second and third integration test cycle), failure data 174
B.8 Project E (first system test cycle), failure data 175
B.9 Project E (second system test cycle), failure data 175
B.10 Project F, failure data 176
B.ll Project G, failure data 177
B.12 Project H, failure data 178
B.13 Project I, failure data 179
B.14 Project J, failure data 180
B.15 Project K, failure data 181
B.16 Project L, failure data 182
B.17 Project M, failure data 183
B.18 Project M, coverage data 184
B.19 Project N (all plug ins), failure data 185
B.20 Project N (all plug ins), coverage data 186
B.21 Project N (plug in S only), failure data 186
B.22 Project N (plug in S only), coverage data 187
B.23 Project O, failure data 188
B.24 Project P, failure data 189
B.25 Project P, coverage data 190
D.I Cardinalities in the crowsfoot notation 221
D.2 Example for a relationship type 222
D.3 Example for an inheritance relationship 222
List of tables
3.1 Unified functional forms of fi(i) and E(Mi) for both extended partial redundancy
models 65
3.2 Interpretation of the parameters in the unified functions 65
3.3 Mean ranks of the seven approaches based on failure data only 84
3.4 Mean ranks of twenty two approaches, including staged procedures, omitting the
estimates based on the first 4 data points 86
3.5 Mean ranks of twenty two approaches, including staged procedures, omitting the
estimates based on the first 15 data points 87
4.1 Number of projects (out of 14) for which the processes were not applicable or for
which ratings were not available 118
4.2 Correlations matrix for the mean ratings of all applicable development processes 119
4.3 Processes evaluated in an assessment and with the PETS questionnaire 120
5.1 Parameter estimates obtained for the first extended partial redundancy model via
the ML NHPP procedure 129
5.2 Correlations between all process scores and (the logarithm of) the estimated fault
density 130
5.3 Environmental factors related to software development and the software product. 132
5.4 (Average) Correlations between the environmental factors related to software de¬
velopment and the product 134
5.5 (Average) Correlations between environmental factors and (the logarithm of) the
estimated fault density 135
5.6 Fitted models of estimated fault density 137
5.7 Estimated fault densities according to the first extended partial redundancy model
and average fitted values of the models (I) and (II) 138
5.8 Fitted models of the logarithm of the estimated fault density 139
5.9 Influence of testing capability on the estimated redundancy level 143
5.10 Environmental factors related to the test process 144
5.11 (Average) Correlations between the environmental factors related to testing . . . 146
x List of tables
5.12 Influence of the environmental factors related to testing on the estimated redun¬
dancy level 147
5.13 Results of fitting the zero inflated binomial model 151
C.I Explanation of entries in the tables of results 191
C.2 Model performance measures for project A 193
C.3 Model performance measures for project B 194
C.4 Model performance measures for project C 195
C.5 Model performance measures for project D 196
C.6 Model performance measures for project E (second a. third integration test cycle) 197
C.7 Model performance measures for project E (first system test cycle) 198
C.8 Model performance measures for project E (second system test cycle) 199
C.9 Model performance measures for project F 200
CIO Model performance measures for project G 201
C. 11 Model performance measures for project H 202
C.12 Model performance measures for project I 203
C.13 Model performance measures for project J 204
C.14 Model performance measures for project K 205
C.15 Model performance measures for project L 206
C.16 Model performance measures for project M 207
C.17 Model performance measures for project N (all plug ins) 210
C.18 Model performance measures for project N (plug in S only) 213
C.19 Model performance measures for project O 216
C.20 Model performance measures for project P 217
|
| any_adam_object | 1 |
| author | Grottke, Michael |
| author_facet | Grottke, Michael |
| author_role | aut |
| author_sort | Grottke, Michael |
| author_variant | m g mg |
| building | Verbundindex |
| bvnumber | BV017671071 |
| classification_rvk | QH 500 ST 233 |
| ctrlnum | (OCoLC)57066456 (DE-599)BVBBV017671071 |
| discipline | Informatik Wirtschaftswissenschaften |
| format | Thesis Book |
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| indexdate | 2024-07-09T19:20:35Z |
| institution | BVB |
| isbn | 3832220356 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-010626335 |
| oclc_num | 57066456 |
| open_access_boolean | |
| owner | DE-29 DE-N2 DE-12 DE-355 DE-BY-UBR DE-703 DE-473 DE-BY-UBG DE-19 DE-BY-UBM DE-188 |
| owner_facet | DE-29 DE-N2 DE-12 DE-355 DE-BY-UBR DE-703 DE-473 DE-BY-UBG DE-19 DE-BY-UBM DE-188 |
| physical | XVI, 262 S. graph. Darst. |
| publishDate | 2003 |
| publishDateSearch | 2003 |
| publishDateSort | 2003 |
| publisher | Shaker |
| record_format | marc |
| series2 | Berichte aus der Wirtschaftsinformatik |
| spelling | Grottke, Michael Verfasser aut Modeling software failures during systematic testing the influence of environmental factors Michael Grottke Aachen Shaker 2003 XVI, 262 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Berichte aus der Wirtschaftsinformatik Zugl.: Erlangen-Nürnberg, Univ., Diss., 2003 Störfaktor (DE-588)4323168-8 gnd rswk-swf Softwareentwicklung (DE-588)4116522-6 gnd rswk-swf Redundanz (DE-588)4157937-9 gnd rswk-swf Zuverlässigkeit (DE-588)4059245-5 gnd rswk-swf Qualität (DE-588)4047966-3 gnd rswk-swf Softwaretest (DE-588)4132652-0 gnd rswk-swf Fehlermodell (DE-588)4380447-0 gnd rswk-swf Modell (DE-588)4039798-1 gnd rswk-swf Testen (DE-588)4367264-4 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Softwaretest (DE-588)4132652-0 s Zuverlässigkeit (DE-588)4059245-5 s Redundanz (DE-588)4157937-9 s Modell (DE-588)4039798-1 s Störfaktor (DE-588)4323168-8 s DE-604 Softwareentwicklung (DE-588)4116522-6 s Testen (DE-588)4367264-4 s Fehlermodell (DE-588)4380447-0 s Qualität (DE-588)4047966-3 s HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010626335&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Grottke, Michael Modeling software failures during systematic testing the influence of environmental factors Störfaktor (DE-588)4323168-8 gnd Softwareentwicklung (DE-588)4116522-6 gnd Redundanz (DE-588)4157937-9 gnd Zuverlässigkeit (DE-588)4059245-5 gnd Qualität (DE-588)4047966-3 gnd Softwaretest (DE-588)4132652-0 gnd Fehlermodell (DE-588)4380447-0 gnd Modell (DE-588)4039798-1 gnd Testen (DE-588)4367264-4 gnd |
| subject_GND | (DE-588)4323168-8 (DE-588)4116522-6 (DE-588)4157937-9 (DE-588)4059245-5 (DE-588)4047966-3 (DE-588)4132652-0 (DE-588)4380447-0 (DE-588)4039798-1 (DE-588)4367264-4 (DE-588)4113937-9 |
| title | Modeling software failures during systematic testing the influence of environmental factors |
| title_auth | Modeling software failures during systematic testing the influence of environmental factors |
| title_exact_search | Modeling software failures during systematic testing the influence of environmental factors |
| title_full | Modeling software failures during systematic testing the influence of environmental factors Michael Grottke |
| title_fullStr | Modeling software failures during systematic testing the influence of environmental factors Michael Grottke |
| title_full_unstemmed | Modeling software failures during systematic testing the influence of environmental factors Michael Grottke |
| title_short | Modeling software failures during systematic testing |
| title_sort | modeling software failures during systematic testing the influence of environmental factors |
| title_sub | the influence of environmental factors |
| topic | Störfaktor (DE-588)4323168-8 gnd Softwareentwicklung (DE-588)4116522-6 gnd Redundanz (DE-588)4157937-9 gnd Zuverlässigkeit (DE-588)4059245-5 gnd Qualität (DE-588)4047966-3 gnd Softwaretest (DE-588)4132652-0 gnd Fehlermodell (DE-588)4380447-0 gnd Modell (DE-588)4039798-1 gnd Testen (DE-588)4367264-4 gnd |
| topic_facet | Störfaktor Softwareentwicklung Redundanz Zuverlässigkeit Qualität Softwaretest Fehlermodell Modell Testen Hochschulschrift |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010626335&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT grottkemichael modelingsoftwarefailuresduringsystematictestingtheinfluenceofenvironmentalfactors |