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“If you can’t measure it,you can’t manage it”
Tom DeMarco, 1982
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• Process Measure the efficacy of processes. What works, what doesn't.
• Project Assess the status of projects. Track risk. Identify problem areas. Adjust work flow.
• ProductMeasure predefined product attributes (generally related to ISO9126 Software Characteristics)
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Other classifications
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Classification by phases of software system • Process metrics – metrics related to the software
development process• Product metrics – metrics related to software maintenance
Classification by subjects of measurements• Quality• Timetable• Effectiveness (of error removal and maintenance
services)• Productivity
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1. Facilitate management control, planning and managerial intervention.
Based on: · Deviations of actual from planned performance. · Deviations of actual timetable and budget
performance from planned.
2. Identify situations for development or maintenance process improvement (preventive or corrective actions).
Based on: · Accumulation of metrics information regarding
the performance of teams, units, etc.
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• KLOC — classic metric that measures the size of software by thousands of code lines.
• Number of function points (NFP) — a measure of the development resources (human resources) required to develop a program, based on the functionality specified for the software system.
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Calculation of NCE Calculation of WCE
Error severity class Number of Errors Relative Weight Weighted Errors
a b c D = b x c
low severity 42 1 42
medium severity 17 3 51
high severity 11 9 99
Total 70 --- 192
NCE 70 --- ---
WCE --- 192
Process Metrics
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Software process quality metrics◦ Error density metrics◦ Error severity metrics
Software process timetable metrics
Software process error removal effectiveness metrics
Software process productivity metrics
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Code Name Calculation formula
CED Code Error Density NCECED = ----------- KLOC
DED Development Error Density NDEDED = ----------- KLOC
WCED Weighted Code Error Density WCEWCDE = --------- KLOC
WDED Weighted Development Error Density WDEWDED = --------- KLOC
WCEF Weighted Code Errors per Function Point
WCEWCEF = ----------
NFP
WDEF Weighted Development Errors per Function Point
WDEWDEF = ----------
NFP
NCE = The number of code errors detected by code inspections and testing.NDE = total number of development (design and code) errors) detected in the development process.WCE = weighted total code errors detected by code inspections and testing.WDE = total weighted development (design and code) errors detected in development process.
A software development department may apply two alternative metrics for calculation of code error density: CED and WCED.
The unit has to determine indicators for unacceptable software quality:
CED > 2 and WCED > 4
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Code Name Calculation formula
ASCE Average Severity of Code Errors
WCEASCE = -----------
NCE
ASDE Average Severity of Development Errors
WDEASDE = -----------
NDE
NCE = The number of code errors detected by code inspections and testing.NDE = total number of development (design and code) errors detected in the development process.WCE = weighted total code errors detected by code inspections and testing.WDE = total weighted development (design and code) errors detected in development process.
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Code Name Calculation formula
TTO Time Table Observance MSOTTTO = -----------
MS
ADMC Average Delay of Milestone Completion
TCDAMADMC = -----------
MS
MSOT = Milestones completed on time.MS = Total number of milestones.TCDAM = Total Completion Delays (days, weeks, etc.) for all milestones.
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Code Name Calculation formula
DERE Development Errors Removal Effectiveness
NDEDERE = ---------------- NDE + NYF
DWERE Development Weighted Errors Removal Effectiveness
WDEDWERE = ------------------ WDE+WYF
NDE = total number of development (design and code) errors) detected in the development process.WCE = weighted total code errors detected by code inspections and testing.WDE = total weighted development (design and code) errors detected in development process. NYF = number software failures detected during a year of maintenance service. WYF = weighted number of software failures detected during a year of maintenance service.
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Code Name Calculation formula
DevP Development Productivity DevHDevP = ---------- KLOC
FDevP Function point Development Productivity
DevHFDevP = ----------
NFP
CRe Code Reuse ReKLOCCre = --------------
KLOC
DocRe Documentation Reuse ReDocDocRe = ----------- NDoc
DevH = Total working hours invested in the development of the software system.ReKLOC = Number of thousands of reused lines of code.ReDoc = Number of reused pages of documentation.NDoc = Number of pages of documentation.
Product Metrics
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* HD quality metrics:
* HD calls density metrics - measured by the number of calls. * HD calls severity metrics - the severity of the HD issues raised. * HD success metrics – the level of success in responding to HD calls.
* HD productivity metrics.
* HD effectiveness metrics.
* Corrective maintenance quality metrics.* Software system failures density metrics * Software system failures severity metrics * Failures of maintenance services metrics * Software system availability metrics
* Corrective maintenance productivity and effectiveness metrics.
Code Name Calculation Formula
HDD HD calls density NHYCHDD = -------------- KLMC
WHDD Weighted HD calls density WHYCWHYC = ------------ KLMC
WHDF Weighted HD calls per function point
WHYCWHDF = ------------ NMFP
NHYC = the number of HD calls during a year of service.KLMC = Thousands of lines of maintained software code.WHYC = weighted HD calls received during one year of service.NMFP = number of function points to be maintained.
Code Name Calculation Formula
ASHC Average severity of HD calls WHYCASHC = --------------
NHYC
NHYC = the number of HD calls during a year of service.
WHYC = weighted HD calls received during one year of service.
Code Name Calculation Formula
HDS HD service success NHYOTHDS = -------------- NHYC
NHYNOT = Number of yearly HD calls completed on time during one year of service. NHYC = the number of HD calls during a year of service.
Code Name Calculation Formula
HDP HD Productivity HDYHHDP= -------------- KLNC
FHDP Function Point HD Productivity HDYHFHDP = ---------- NMFP
HDE HD effectiveness HDYHHDE = -------------- NHYC
HDYH = Total yearly working hours invested in HD servicing of the software system.KLMC = Thousands of lines of maintained software code.NMFP = number of function points to be maintained.NHYC = the number of HD calls during a year of service.
Code Name Calculation Formula
SSFD Software System Failure Density NYF SSFD = --------------
KLMC
WSSFD Weighted Software System Failure Density
WYFWFFFD = ---------
KLMC
WSSFF Weighted Software System Failures per Function point
WYFWSSFF = ---------- NMFP
NYF = number of software failures detected during a year of maintenance service.WYF = weighted number of yearly software failures detected during one year of maintenance service.NMFP = number of function points designated for the maintained software.KLMC = Thousands of lines of maintained software code.
Code Name Calculation Formula
ASSSF Average Severity of Software System Failures
WYFASSSF = --------------
NYF
NYF = number of software failures detected during a year of maintenance service.WYF = weighted number of yearly software failures detected during one year.
Code Name Calculation Formula
MRepF Maintenance Repeated repair Failure metric -
RepYFMRepF = --------------
NYF
NYF = number of software failures detected during a year of maintenance service. RepYF = Number of repeated software failure calls (service failures).
Code Name Calculation Formula
FA Full Availability NYSerH - NYFHFA = -----------------------
NYSerH
VitA Vital Availability NYSerH - NYVitFHVitA = -----------------------------
NYSerH
TUA Total Unavailability NYTFHTUA = ------------ NYSerH
NYSerH = Number of hours software system is in service during one year. NYFH = Number of hours where at least one function is unavailable (failed) during one year, including total failure of the software system. NYVitFH = Number of hours when at least one vital function is unavailable (failed) during one year, including total failure of the software system. NYTFH = Number of hours of total failure (all system functions failed) during one year.NYFH ≥ NYVitFH ≥ NYTFH.1 – TUA ≥ VitA ≥FA
Code Name Calculation Formula
CMaiP Corrective Maintenance Productivity
CMaiYHCMaiP = ---------------
KLMC
FCMP Function point Corrective Maintenance Productivity
CMaiYHFCMP = --------------
NMFP
CMaiE Corrective Maintenance Effectiveness
CMaiYHCMaiE = ------------
NYF
CMaiYH = Total yearly working hours invested in the corrective maintenance of the software system. NYF = number of software failures detected during a year of maintenance service. NMFP = number of function points designated for the maintained software. KLMC = Thousands of lines of maintained software code.
Defining new Software Quality Metrics
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Limitations of Software Quality Metrics
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* Budget constraints in allocating the necessary resources.
* Human factors, especially opposition of employees to evaluation of their activities.
* Validity Uncertainty regarding the data's, partial and biased reporting.
* Parameters used in development process
metrics: KLOC, NDE, NCE.
* Parameters used in product (maintenance) metrics: KLMC, NHYC, NYF.
a. Programming style (KLOC).b. Volume of documentation comments (KLOC).c. Software complexity (KLOC, NCE).d. Percentage of reused code (NDE, NCE).e. Professionalism and thoroughness of design review and
software testing teams: affects the number of defects detected (NCE).
f. Reporting style of the review and testing results: concise reports vs. comprehensive reports (NDE, NCE).
a. Quality of installed software and its documentation (NYF, NHYC).
b. Programming style and volume of documentation comments included in the code be maintained (KLMC).
c. Software complexity (NYF).d. Percentage of reused code (NYF).e. Number of installations, size of the user population and
level of applications in use: (NHYC, NYF).
Goal Question Metrics Approach“GQM” Approach
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The GQM approach is based on the idea that in order to measure in a meaningful way we must measure that which will help us to assess and meet our organizational goals.
– A Goal is defined for an object, for a variety of reasons, with respect to various models of quality, from various points of view, relative to a particular environment. The objects of measurement are products, processes and resources.
– Questions are used to characterize the way the assessment/achievement of a specific goal is going to be performed based on some characterizing model. Questions try to characterize the object of measurement with respect to a selected quality issue and to determine its quality from the selected viewpoint. Questions must be answerable in a quantitative manner.
– Metrics are associated with every question in order to answer it in a quantitative way.
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– Goal: Customer Satisfaction
– Question: Are customers dissatisfied when problems occur?
– Metric: Number of customer defect reports
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– Goal: To improve the outcome of design inspections from the quality managers point of view.
– Question: What is the current yield of design inspections?– Metric: inspection yield = nr defects found / est. total
defects
– Question: What is the current inspection rate?– Metric: individual inspection rate, inspection period,
overall inspection rate
– Question: Is design inspection yield improving?– Metric: current design inspection yield / baseline design
inspection yield * 10038
organization’s goals: is to evaluate the effectiveness of the coding standard.
Some of the associated questions might be:
◦ Who is using the standard?
◦ What is coder productivity?
◦ What is the code quality?
For these questions, the corresponding metrics might be:
◦ What proportion of coders are using the standard?◦ How have the number of LOC or FPs generated per day per coder
changed?◦ How have appropriate measures of quality for the code changed?
(Appropriate measures might be errors found per LOC or cyclomatic complexity.)
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WILLIAW E. LEWIS, “SOFTWARE TESTING AND CONTINUOUS QUALITY IMPROVEMENT”, THIRD EDITION, CRC PRESS, 2009.
K. NAIK AND P. TRIPATHY: “SOFTWARE TESTING AND QUALITY ASSURANCE”, WILEY, 2008.
IAN SOMMERVILLE, SOFTWARE ENGINEERING, 8TH EDITION, 2006.
ADITYA P. MATHUR,“FOUNDATIONS OF SOFTWARE TESTING”, PEARSON EDUCATION, 2009.
D. GALIN, “SOFTWARE QUALITY ASSURANCE: FROM THEORY TO IMPLEMENTATION”, PEARSON EDUCATION, 2004
DAVID GUSTAFSON, “THEORY AND PROBLEMS OF SOFTWARE ENGINEERING”, Schaum’s Outline Series, McGRAW-HILL, 2002.
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