Software MetricsFaculty Prof.V.Narayana K.S.Prakasa Rao P.Linga Reddy

Software Metrics - TopicsWhy measure What to measure When to measure Data collection Metric analysis Simple statistical tools Improvements Issues Ideaspace Solutions Limited All Rights ReservedSlide 2 of 43 Version:1.0 Date :05/08/2002

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Why measure ?Software project goalsquality of deliverables timely delivery and cost

If you do not measure, you do not know where you are and do not know what to improve

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Why measure ?Need Quantitative Datato monitor progress to analyze trends to identify areas that need improvement to initiate improvements

Continuous improvement

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Why measure ?effort in person days in completing a task or number of defects reported in testing a module of software product or process For e.g.., Effort deviation percentage (planned versus actual) Defect density = defects per unit size of work product.

Measurement - A quantified observation For eg.,

Metric - A comparative measure of the performance

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What to measure ?Project management metricsSchedule metrics Effort metrics Phase-wise effort distribution

Quality metricsDefect metrics Customer satisfaction Maintenance metrics

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What to measure ? (contd)Cost metricsCost variance Cost of Quality

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Schedule metricsTo monitor the trends in the actual calendar days spent on completion of specific tasks/ activities against planned calendar days Development projects - phase wise measurements Sustenance projects - work request wise measurements Used for re-planning at the project level and as input for estimation at the company levelWhere Ideas Drive IT Ideaspace Solutions Limited All Rights ReservedSlide 8 of 43 Version:1.0 Date :05/08/2002

Schedule metrics (contd)Planned calendar days)/Planned calendar days) * 100

Schedule deviation = ((Actual calendar days -

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Effort metricsTo monitor the trends in the person days spent on completion of specific tasks/ activities against planned person days Development projects - phase wise measurements Sustenance projects - work request wise measurements Used for re-planning at the project level and as input for estimation at the company levelWhere Ideas Drive IT Ideaspace Solutions Limited All Rights ReservedSlide 10 of 43 Version:1.0 Date :05/08/2002

Effort metrics (contd)Planned person days)/ Planned person days) * 100

Effort deviation = ((Actual person days -

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Phase-wise effort distributionAnalysis of effort spent on each phase for different kinds of projects Comparison with size of work product at each phase Provides norms at the company levelfor preparation of proposals for project planning

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Defect metricsTo monitor trends in defects at each phase of development as well as during acceptance by the customer Classification by severity of defect and origin of defect helps in initiating corrective actions

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Defect metrics (contd)Defect densityNo of defects/size of the work product

Severity of defectsclassification of defects as critical, major & minor and their distribution at each phase

Origin of defectsclassification of defects based on the origin of defects such as requirements, design or coding

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Defect metrics (contd)Defects seepageDefects reported by customer during acceptance as a percentage of total defects reported during pre-delivery system testing

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Customer satisfactionBased on customer satisfaction survey, analyze the data and identify areas of strengths and weakness Identify causes that result in customer dissatisfaction and take corrective actions

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Maintenance metricsAnalysis of defects reported during warranty support Mean time taken to resolve problems reported by the customer

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Cost metricsCost variance = ((Actual cost - Planned cost)/Planned cost) * 100 Cost of QualityPrevention cost Appraisal cost Failure cost (Internal failures and external failures)

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When to measurePeriodic - on a time bound basis (daily or weekly) Milestone - on completion of a specific mile stone

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Data collectionPlanned start date and close date for each phase Actual start date and close date for each phase Planned effort for each phase Actual effort for each phase Defects at each phase of review and testingWhere Ideas Drive IT Ideaspace Solutions Limited All Rights ReservedSlide 20 of 43 Version:1.0 Date :05/08/2002

Data collection (contd)Customer satisfaction survey data Customer feedback and complaints data Sustenance projects - schedule and effort (planned and actual) for each work request

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Metric analysisSchedule variance = ((Actual calendar days Planned calendar days)/ Planned calendar days)) * 100 Effort variance = ((Actual effort in person days Planned effort in person days)/ Planned effort in person days)) * 100 Effort distribution metric = Percentage of effort spent for each phaseSlide 22 of 43 Version:1.0 Date :05/08/2002

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Metric analysis (contd)Defect metrics Defect density = Number of defects/size of the work product Defect distribution = Percentage of defects by defect severity and origin of defects Defects seepage = Defects reported during acceptance as a percentage of defects reported during internal testingSlide 23 of 43 Version:1.0 Date :05/08/2002

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Metric analysis (contd)Customer satisfaction surveyCustomer satisfaction survey is conducted quarterly/mile-stone for large projects and end of project for small projects Parameters measured - Quality, Delivery, Service, Communication, Relationship and Value Rating for each parameter - 5 Excellent, 4 Fully satisfied, 3 Average, 2 Fair and 1 PoorSlide 24 of 43 Version:1.0 Date :05/08/2002

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Metric analysis (contd)Customer satisfaction survey (contd)Each parameter to have a score of 3 plus and an overall score of more than 70% Analyzed for each customer and plotted for score of each parameter and total score

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Metric analysis (contd)Maintenance MetricsAnalysis of Time taken to respond to customer reported defects Analysis of type of defects by type and severity

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Metric analysis (contd)Cost MetricsCost variance = ((Actual cost - Planned cost)/ Planned cost)*100 Cost of QualityPrevention cost (Planning, training etc.,) Appraisal cost (Reviews and testing) Failure cost (Rework, customer complaints etc.,)

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Simple statistical toolsScatter diagram Histogram Pareto Analysis Brainstorming Cause and effect diagrams Control chartsSlide 28 of 43 Version:1.0 Date :05/08/2002

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Scatter diagramDiscover, confirm or display relationships between two sets of data

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HistogramDisplay the dispersion or spread of data

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Histogram

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