chapter04 soft process metrics rpl
TRANSCRIPT
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Chapter 4Software Process and Project Metrics
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Measurement & Metrics
... collecting metrics is too hard ...
it's too time-consuming ... it's too
political ... it won't prove anything ...
Anyth ing that you need to
quant i fy can be measured in
som e way that is super ior to
no t measu ring it at all ..
Tom Gilb
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Why do we Measure?
To characterize
To evaluate
To predict
To improve
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
A Good Manager Measures
measurement
What do we
use as a
basis?
size?
function?
project metricsprocess metrics
process
product
product metrics
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Process Metrics
majority focus on quality achieved as aconsequence of a repeatable or managedprocess
statistical SQA data error categorization & analysis
defect removal efficiency propagation from phase to phase
reuse data
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Project Metrics
Effort/time per SE task
Errors uncovered per review hour
Scheduled vs. actual milestone dates
Changes (number) and their characteristics
Distribution of effort on SE tasks
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Product Metrics
focus on the quality of deliverables
measures of analysis model
complexity of the design internal algorithmic complexityarchitectural complexitydata flow complexity
code measures (e.g., Halstead)
measures of process effectivenesse.g., defect removal efficiency
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Metrics Guidelines
Use common sense and organizational sensitivity when
interpreting metrics data. Provide regular feedback to the individuals and teams who
have worked to collect measures and metrics.
Dont use metrics to appraise individuals.
Work with practitioners and teams to set clear goals andmetrics that will be used to achieve them.
Never use metrics to threaten individuals or teams.
Metrics data that indicate a problem area should not beconsidered negative. These data are merely an indicator forprocess improvement.
Dont obsess on a single metric to the exclusion of other
important metrics.
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Normalization for Metrics
Normalized data are used to evaluate the process
and the product (but never individual people)
size-oriented normalizationthe line of code approach
function-oriented normalizationthe function pointapproach
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Typical Size-Oriented Metrics
errors per KLOC (thousand lines ofcode)
defects per KLOC
$ per LOC
page of documentation per KLOCerrors / person-month
LOC per person-month
$ / page of documentation
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Typical Function-Oriented Metrics
errors per FP (thousand lines of code)
defects per FP
$ per FP
pages of documentation per FP
FP per person-month
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Why Opt for FP Measures?
independent of programming language
uses readily countable characteristics of the"information domain" of the problem
does not "penalize" inventive implementations thatrequire fewer LOC than others
makes it easier to accommodate reuse and thetrend toward object-oriented approaches
C ti F ti P i t
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Computing Function PointsAnalyze informationdomain of theapplicationand develop counts
Weight each count byassessing complexity
Assess influence ofglobal factors that affectthe application
Computefunction points
Establish countfor input domain andsystem interfaces
Assign level of complexity or weightto each count
Grade significance of external factors, Fsuch as reuse, concurrency, OS, ...
degree of influence: N = Fi
complexity multiplier: C = (0.65 + 0.01 x N)
function points = (count x weight) x C
where:
i
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Analyzing the Information Domain
complexity multiplier
function points
number of user inputs
number of user outputs
number of user inquiries
number of files
number of ext.interfaces
measurement parameter
3
4
3
7
5
countweighting factor
simple avg. complex
4
5
4
10
7
6
7
6
15
10
=
=
=
=
=
count-total
X
X
X
X
X
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Taking Complexity into Account
Factors are rated on a scale of 0 (not important)to 5 (very important):
data communicationsdistributed functions
heavily used configurationtransaction rateon-line data entryend user efficiency
on-line updatecomplex processing
installation easeoperational easemultiple sitesfacilitate change
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Measuring Quality
Correctness the degree to which a programoperates according to specification
Maintainabilitythe degree to which aprogram is amenable to change
Integritythe degree to which a program isimpervious to outside attack
Usabilitythe degree to which a program iseasy to use
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Defect Removal Efficiency
DRE = (errors) / (errors + defects)
whereerrors= problems found before release
defects= problems found after release
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These courseware materials are to be used in conjunction with Software Engineering: A Practitioners Approach,5/e and areprovided with permission by R.S. Pressman & Associates, Inc., copyright 1996, 2001
Managing Variation
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19
Project s
Er,Erro rs fo u nd /re vie w
ho u r
The mR Control Chart