E

early development stage, 80

counting at, 85

education of nontechnical staff, 263

efficiency of defect removal, 242–245

effort multipliers, Cocomo II model, 66

effort, project

allocating to various activities, 233–238

collecting data on, 95, 96

comparing estimates for, 218

computing, 210

estimating, 207–219

with fuzzy logic, 138

with industry average data, 210–216

influences on, 207–208

from project size, 209–210

software for, 158

practical considerations (ideal vs. planned), 239–241

tradeoffs with scheduling, 227, 228–230

EMs (effort multipliers), Cocomo II model, 67–70

environment, programming, 65

equations

Basic Schedule Equation, the, 221

Complex Standard Deviation Formula, 122

Dutch Method's Indicative Function Point Count Formula, 203

Informal Comparison to Past Projects Formula, 223

ISBSG Effort Formula for Desktop Projects, 217

ISBSG Effort Formula for Enhancement Projects, 217

ISBSG Effort Formula for Fourth Generation Projects, 217

ISBSG Effort Formula for General Projects, 216

ISBSG Effort Formula for Mainframe Projects, 216

ISBSG Effort Formula for Mid-Range Projects, 217

ISBSG Effort Formula for New Development Projects, 217

ISBSG Effort Formula for Third Generation Projects, 217

Magnitude of Relative Error (MRE) Formula, 110

Modified Complex Standard Deviation Formula, 124

PERT Formula for Estimating Number of Components, 139

Pessimistic PERT Formula, 109

Program Evaluation and Review Technique (PERT) Formula, 109

Simple Standard Deviation Formula, 121

errors in project. See software quality

errors of estimation. See sources of estimation error

estimate accuracy. See also sources of estimation error

benefits of, 27–29

counting error. See counting

expressing uncertainty, 251–255

flow of estimates (reestimating), 171–180

chronological, 173–175

poorly estimated projects, 171

recalibrating after missed milestones, 175–179

scheduling reestimation, 177–178

well-estimated projects, 172–173

historical data and, 91–95

need for, 13

overestimation vs. underestimation, 21–24

precision vs., 51–52

reviewing. See reviews of estimates

software industry track record, 24–27

Estimate Express tool, 163

estimate influences, 55–72

diseconomies of scale, 56–61, 70

effort estimates, 208

modeling after historical data, 99

software to account for, 160

when unimportant, 60

kind of software, 61–63, 236

miscellaneous other sources, 65–70

personnel factors, 63

political, 260–263

programming language, 64–65

size. See project size

estimate precision, unwarranted, 51–52

estimate presentation styles, 249–257

assumption communication, 249–251

expressing uncertainty, 251–255

ranges, 256–257

estimate rejection, 262

estimates, communicating about, 4–6

estimates, debating, 172, 269. See also negotiation and problem solving

estimates, defined, 3–14, 173

common definitions, 9

good estimates, 9

plans vs., 4

probability statements, 6–9

working definition, 14

estimates, reviewing. See reviews of estimates

estimating models, industry differences in, 63

estimating software size. See size, project

estimation error, sources of, 33–53. See also accuracy of estimates; accuracy of estimation method

chaotic development processes, 41

Cone of Uncertainty, 35–41

reestimating throughout project, 173–175

schedule estimates and, 222

miscellaneous other sources, 52

off-the-cuff estimates, 49–51

omitted activities, 44–46

politics, 259–270

attributes of executives, 259–260

avoiding with historical data, 93–95

influences on estimates, 260–263

negotiation and problem solving, 259–260, 261, 263–270

subjectivity and bias, 47–49

unfounded optimism, 46

unstable project requirements, 42, 247

requirements omitted from estimates, 44–46, 110

software to account for, 160

unwarranted precision, 51–52

estimation flow (reestimating), 171–180

chronological, 173–175

poorly estimated projects, 171

recalibrating after missed milestones, 175–179

scheduling reestimation, 177–178

well-estimated projects, 172–173

estimation negotiation, 263–270

attributes of executives and, 259–260

estimates vs. commitments, 261

estimation politics, 259–270

attributes of executives and, 259–260

avoiding with historical data, 93–95

influences on estimates, 260–263

negotiation and problem solving, 263–270

attributes of executives and, 259–260

estimates vs. commitments, 261

estimation skill, testing, 15–19, 273

estimation software, 157–164

calibrating, 162

computing effort with, 210

computing schedule with, 225

estimating project size with, 205

list of, 163–164

estimation techniques, 77–81, 80

by analogy, 127–133

basic approach, 127–132

effort estimates, 209–210

estimating project size, 205

estimating schedule, 223–224

obtaining detailed information, 128

size comparisons, 129

uncertainty with, 128

applicability tables, explained, 81

computation, 83–84

converting counts to estimates, 86–88

stage-gate processes, 187

counting, 84–86

computing estimates with, 86–88

function points, 200

stage-gate processes, 187

Delphi technique, 150–155

how to choose, 77–80

judgment. See expert judgment; off-the-cuff estimates

multiple approaches, using, 165–169

for effort, 218

for project size, 206

ranges, presenting, 256

for schedules, 231–232

stage-gate processes, 187

proxy-based, 135–147

fuzzy logic, 136–138, 205

standard components approach, 138–141

story points, 142–144, 205

t-shirt sizing, 145–146

events, unforeseen, 12

evolutionary delivery, 79

evolutionary prototyping, 79

executives, attributes of, 259–260

expected-case calculation, 108–109, 120

complex standard deviation formula, 122–124

by decomposition. See decomposition

simple standard deviation formula, 121–122

expert judgment, 83–84, 88–89, 105–112

comparing to actuals, 110–106

group (structured) judgment, 106–110, 149–155

estimating project size with, 205

Wideband Delphi technique, 150–155

insisting on objective criteria, 268

exploratory estimate (stage-gate processes), 184, 185, 188

exponential increases with project size. See diseconomies of scale

extending schedule to reduce effort, 228

external bias, 48

external I/O, as function points, 200

external interface files, as function points, 200

external political constraints, 260

extreme programming, 79

story points, 142–144, 205