thesis - Faculty of Information and Communication Technologies ...

More documents

Recommendations

Info

Contents 4.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 5 Growth Dynamics 90 5.1 Nature of Software Metric Data . . . . . . . . . . . . . . . . 92 5.1.1 Summarising with Descriptive Statistics . . . . . . . 93 5.1.2 Distribution Fitting to Understand Metric Data . . . 95 5.2 Summarizing Software Metrics . . . . . . . . . . . . . . . . . 98 5.2.1 Gini Coefficient - An Overview . . . . . . . . . . . . . 98 5.2.2 Computing the Gini Coefficient . . . . . . . . . . . . 99 5.2.3 Properties of Gini Coefficient . . . . . . . . . . . . . . 101 5.2.4 Application of the Gini Coefficient - An Example . . 102 5.3 Analysis Approach . . . . . . . . . . . . . . . . . . . . . . . . 103 5.3.1 Metrics Analyzed . . . . . . . . . . . . . . . . . . . . . 103 5.3.2 Metric Correlation . . . . . . . . . . . . . . . . . . . . 104 5.3.3 Checking Shape of Metric Data Distribution . . . . . 105 5.3.4 Computing Gini Coefficient for Java Programs . . . . 106 5.3.5 Identifying the Range of Gini Coefficients . . . . . . . 106 5.3.6 Analysing the Trend of Gini Coefficients . . . . . . . 107 5.4 Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 5.4.1 Correlation between measures . . . . . . . . . . . . . 109 5.4.2 Metric Data Distributions are not Normal . . . . . . 111 5.4.3 Evolution of Metric Distributions . . . . . . . . . . . 111 5.4.4 Bounded Nature of Gini Coefficients . . . . . . . . . 113 ix
Contents 5.4.5 Identifying Change using Gini Coefficient . . . . . . 115 5.4.6 Extreme Gini Coefficient Values . . . . . . . . . . . . 117 5.4.7 Trends in Gini Coefficients . . . . . . . . . . . . . . . 118 5.4.8 Summary of Observations . . . . . . . . . . . . . . . 119 5.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 5.5.1 Correlation between Metrics . . . . . . . . . . . . . . 122 5.5.2 Dynamics of Growth . . . . . . . . . . . . . . . . . . . 123 5.5.3 Preferential Attachment . . . . . . . . . . . . . . . . . 124 5.5.4 Stability in Software Evolution . . . . . . . . . . . . . 126 5.5.5 Significant Changes . . . . . . . . . . . . . . . . . . . 128 5.5.6 God Classes . . . . . . . . . . . . . . . . . . . . . . . . 130 5.5.7 Value of Gini Coefficient . . . . . . . . . . . . . . . . . 132 5.5.8 Machine-generated Code . . . . . . . . . . . . . . . . 134 5.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136 6 Change Dynamics 138 6.1 Detecting and Measuring Change . . . . . . . . . . . . . . . 140 6.1.1 Approaches for Detecting Change . . . . . . . . . . . 140 6.1.2 Our Approach for Detecting Change in a Class . . . 142 6.1.3 Identifying Modified, New and Deleted Classes . . . . 143 6.1.4 Measuring Change . . . . . . . . . . . . . . . . . . . . 144 6.1.5 Measuring Popularity and Complexity of a Class . . 145 6.2 Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 x
Page 1 and 2: Growth and Change Dynamics in Open
Page 3 and 4: Dedicated to all my teachers ii
Page 5 and 6: Declaration I declare that this the
Page 7 and 8: 7. R. Vasa, M. Lumpe, P. Branch, an
Page 9: Contents 3.4 Selection Criteria . .
Page 13 and 14: Contents 7.2.2 Software Metric Tool
Page 15 and 16: List of Figures 4.7 Class diagram s
Page 17 and 18: List of Figures 6.9 Probability of
Page 19 and 20: List of Tables 5.2 Spearman’s Ran
Page 21 and 22: Chapter 1. Introduction in the laws
Page 23 and 24: Chapter 1. Introduction models that
Page 25 and 26: Chapter 1. Introduction compute at
Page 27 and 28: Chapter 1. Introduction undergo con
Page 29 and 30: Chapter 2 Software Evolution How do
Page 31 and 32: Chapter 2. Software Evolution Proce
Page 33 and 34: Chapter 2. Software Evolution Softw
Page 35 and 36: Chapter 2. Software Evolution devel
Page 37 and 38: Chapter 2. Software Evolution [59,
Page 39 and 40: Chapter 2. Software Evolution These
Page 41 and 42: Chapter 2. Software Evolution and C
Page 43 and 44: Chapter 2. Software Evolution Tursk
Page 45 and 46: Chapter 2. Software Evolution nenti
Page 47 and 48: Chapter 2. Software Evolution The o
Page 49 and 50: Chapter 2. Software Evolution used
Page 51 and 52: Chapter 2. Software Evolution durin
Page 53 and 54: Chapter 2. Software Evolution added
Page 55 and 56: Chapter 2. Software Evolution that
Page 57 and 58: Chapter 2. Software Evolution the c
Page 59 and 60: Chapter 2. Software Evolution The q
Page 61 and 62:
Chapter 3. Data Selection Methodolo
Page 63 and 64:
Page 65 and 66:
Page 67 and 68:
Page 69 and 70:
Page 71 and 72:
Page 73 and 74:
Page 75 and 76:
Page 77 and 78:
Page 79 and 80:
Chapter 4 Measuring Evolving Softwa
Page 81 and 82:
Chapter 4. Measuring Evolving Softw
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
Page 89 and 90:
Page 91 and 92:
Page 93 and 94:
Page 95 and 96:
Page 97 and 98:
Page 99 and 100:
Page 101 and 102:
Page 103 and 104:
Page 105 and 106:
Page 107 and 108:
Page 109 and 110:
Chapter 5 Growth Dynamics Current m
Page 111 and 112:
Chapter 5. Growth Dynamics used to
Page 113 and 114:
Chapter 5. Growth Dynamics mean, me
Page 115 and 116:
Chapter 5. Growth Dynamics bution p
Page 117 and 118:
Chapter 5. Growth Dynamics Though,
Page 119 and 120:
Chapter 5. Growth Dynamics Figure 5
Page 121 and 122:
Chapter 5. Growth Dynamics 5.2.4 Ap
Page 123 and 124:
Chapter 5. Growth Dynamics measure
Page 125 and 126:
Chapter 5. Growth Dynamics 5.3.1) [
Page 127 and 128:
Page 129 and 130:
Chapter 5. Growth Dynamics • The
Page 131 and 132:
Chapter 5. Growth Dynamics 50.0% 45
Page 133 and 134:
Chapter 5. Growth Dynamics Metric M
Page 135 and 136:
Page 137 and 138:
Chapter 5. Growth Dynamics ber of M
Page 139 and 140:
Chapter 5. Growth Dynamics Spearman
Page 141 and 142:
Chapter 5. Growth Dynamics Spearman
Page 143 and 144:
Chapter 5. Growth Dynamics as exist
Page 145 and 146:
Chapter 5. Growth Dynamics sented i
Page 147 and 148:
Chapter 5. Growth Dynamics System M
Page 149 and 150:
Chapter 5. Growth Dynamics populati
Page 151 and 152:
Chapter 5. Growth Dynamics abstract
Page 153 and 154:
Page 155 and 156:
Chapter 5. Growth Dynamics Another
Page 157 and 158:
Chapter 6 Change Dynamics It is a w
Page 159 and 160:
Chapter 6. Change Dynamics 6.1 Dete
Page 161 and 162:
Chapter 6. Change Dynamics often ma
Page 163 and 164:
Chapter 6. Change Dynamics The set
Page 165 and 166:
Chapter 6. Change Dynamics analysis
Page 167 and 168:
10 12 14 16 18 20 22 24 26 28 30 32
Page 169 and 170:
Chapter 6. Change Dynamics Age (Day
Page 171 and 172:
Chapter 6. Change Dynamics erties h
Page 173 and 174:
Chapter 6. Change Dynamics 100% 90%
Page 175 and 176:
Chapter 6. Change Dynamics the meas
Page 177 and 178:
Chapter 6. Change Dynamics 50.0% 45
Page 179 and 180:
Chapter 6. Change Dynamics Figure 6
Page 181 and 182:
Chapter 6. Change Dynamics new clas
Page 183 and 184:
Chapter 6. Change Dynamics We obser
Page 185 and 186:
Chapter 6. Change Dynamics the chan
Page 187 and 188:
Chapter 6. Change Dynamics other en
Page 189 and 190:
Chapter 6. Change Dynamics 6.3.4 Po
Page 191 and 192:
Chapter 6. Change Dynamics stance,
Page 193 and 194:
Chapter 6. Change Dynamics ing a lo
Page 195 and 196:
Chapter 6. Change Dynamics Lanza et
Page 197 and 198:
Chapter 6. Change Dynamics smells t
Page 199 and 200:
Chapter 6. Change Dynamics growth i
Page 201 and 202:
Chapter 7. Implications ically, we
Page 203 and 204:
Chapter 7. Implications overall str
Page 205 and 206:
Chapter 7. Implications contain new
Page 207 and 208:
Chapter 7. Implications ciently bro
Page 209 and 210:
Chapter 7. Implications tional supp
Page 211 and 212:
Chapter 7. Implications where a sof
Page 213 and 214:
Chapter 8. Conclusions • We prese
Page 215:
Chapter 8. Conclusions [302], and g
Page 218 and 219:
Appendix A Meta Data Collected for
Page 220 and 221:
Appendix C Mapping between Metrics
Page 222 and 223:
Chapter D. Metric Extraction Illust
Page 224 and 225:
Appendix F Change Dynamics Data Fil
Page 226 and 227:
References [1] S. Alam and P. Duger
Page 228 and 229:
References Software. In Proceedings
Page 230 and 231:
References [43] N. Chapin, J. Hale,
Page 232 and 233:
References [68] M. Di Penta, L. Cer
Page 234 and 235:
References [91] C. Gini. Measuremen
Page 236 and 237:
References [115] I. Held. The Scien
Page 238 and 239:
References [140] H. Kagdi, S. Yusuf
Page 240 and 241:
References [164] M. Lanza, H. Gall,
Page 242 and 243:
References [190] T. J. McCabe. A Co
Page 244 and 245:
References [214] H. Olague, L. Etzk
Page 246 and 247:
References [242] C. Roy, J. Cordy,
Page 248 and 249:
References [266] G. Succi, W. Pedry
Page 250 and 251:
References ECOOP Workshop on Quanti
Page 252:
References [315] T. Zimmermann, V.
show all

thesis - Faculty of Information and Communication Technologies ...

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?