VM-STUDYPOINT:
Unit II: Project Management Process, Metrics, Estimations & Risks
In this unit, we will explore the fundamentals of software project management, covering metrics, estimations, planning, and risk management. Proper project management ensures that software is delivered on time, within budget, and with high quality.
1. Measures, Metrics & Indicators
a. Understanding Measures, Metrics, and Indicators
Software measurement helps quantify different aspects of a project, ensuring better decision-making.
| Term | Definition | Example |
|---|---|---|
| Measure | A single quantitative value related to software attributes. | "Lines of Code (LOC)" for a module. |
| Metric | A derived or calculated value based on one or more measures. | "Defect Density = Number of Defects / LOC" |
| Indicator | A meaningful interpretation of a metric to aid decision-making. | "High defect density means poor code quality." |
2. Metrics in Process & Project Domains - Software Measurement
a. Process Metrics
These metrics evaluate how well a software process performs.
Examples:
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Defect Removal Efficiency (DRE) = (Defects found before release / Total defects) × 100%
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Process Productivity = LOC produced per developer per day.
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Cycle Time = Time taken to complete one development cycle.
b. Project Metrics
Project metrics focus on the overall performance of a project.
Examples:
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Schedule Variance (SV) = (Actual Time – Estimated Time).
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Effort Estimation Accuracy = (Estimated Effort / Actual Effort) × 100%.
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Cost Performance Index (CPI) = Earned Value / Actual Cost.
3. Metrics for Software Quality
Software quality is measured using quality metrics, which ensure that the software meets user expectations.
| Quality Metric | Description | Formula (if applicable) |
|---|---|---|
| Defect Density | Number of defects per KLOC (Thousand Lines of Code). | Defect Density = Defects / KLOC |
| Mean Time to Failure (MTTF) | The average time the software runs before failing. | Total operational time / Number of failures |
| Mean Time to Repair (MTTR) | The average time taken to fix a failure. | Total downtime / Number of repairs |
| Customer Satisfaction Index (CSI) | Measures user feedback and satisfaction. | Surveys and rating systems |
| Code Maintainability Index | Determines how easily the software can be modified. | Complexity, documentation, and modularity factors |
High-quality software should have:
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Low defect density.
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High maintainability.
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Low failure rates.
4. Metrics for Small Organizations
In small organizations, resources are limited, so lightweight agile-based metrics are preferred:
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Burn-down charts: Track work completion over time.
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Velocity: Number of tasks completed per sprint.
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Code Review Effectiveness: Percentage of bugs found during code review.
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Customer Feedback Metrics: Direct feedback from users.
5. Software Project Planning
a. Scope Management
Scope defines what is included and what is NOT included in a project. A well-defined scope helps prevent scope creep (uncontrolled expansion of project features).
Steps in Scope Planning:
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Define objectives (What problem does the software solve?).
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Identify deliverables (What features will be included?).
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Set boundaries (What will NOT be developed?).
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Get stakeholder approval (Ensure alignment with business needs).
6. Project Resources
Resources include:
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Human Resources: Developers, testers, project managers.
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Hardware: Servers, computers, networks.
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Software Tools: IDEs, version control (Git), testing tools.
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Budget: Cost estimates for salaries, equipment, licenses.
Effective resource allocation ensures a project is completed on time and within budget.
7. Software Estimation Techniques
Software estimation predicts the time, effort, and cost required for development.
a. Estimation Methods
| Method | Description | Example |
|---|---|---|
| Lines of Code (LOC) Estimation | Estimates project size based on expected LOC. | If 1000 LOC takes 10 days, 5000 LOC will take 50 days. |
| Function Point Analysis (FPA) | Measures complexity based on inputs, outputs, and user interactions. | Used for estimating effort in business applications. |
| COCOMO (Constructive Cost Model) | Uses mathematical formulas to predict effort and cost. | Effort = a × (Size)^b, where a and b are constants. |
| Use Case-Based Estimation | Estimates effort based on the number of use cases. | "Login feature = 3 days, Payment feature = 7 days." |
8. Decomposition Techniques
Decomposition is breaking down a large project into smaller, manageable tasks.
Types of Decomposition
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Functional Decomposition: Breaking down software into modules (e.g., Login module, Payment module).
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Work Breakdown Structure (WBS): Hierarchical breakdown of tasks.
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Effort Decomposition: Dividing the project into different stages (e.g., Analysis, Design, Development).
9. Software Risk Management
a. Types of Risks
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Technical Risks: Bugs, performance issues, technology failures.
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Project Risks: Budget overruns, missed deadlines.
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Business Risks: Market demand changes, competition.
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Security Risks: Cybersecurity threats, data breaches.
b. Risk Identification
Identifying risks before they cause failure. Examples:
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Requirement risks: Unclear specifications.
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Technology risks: Using an untested technology.
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Human risks: Developer resignations.
c. Risk Projection
Predicting how severe a risk is using risk matrices:
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Probability (Low, Medium, High).
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Impact (Minor, Major, Critical).
Example:
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High probability + High impact → Critical risk.
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Low probability + Low impact → Acceptable risk.
10. Risk Refinement & RMMM Plan
a. Risk Refinement
Breaking risks into detailed categories for better management.
Example:
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Initial risk: "Technology failure."
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Refined risk: "Database crashes under high load."
b. Risk Mitigation, Monitoring, and Management (RMMM) Plan
RMMM is a structured approach to handling risks.
| Step | Description |
|---|---|
| Mitigation | Actions to reduce the likelihood of risk. |
| Monitoring | Tracking risks continuously. |
| Management | Taking action when risk occurs. |
Example RMMM Plan
| Risk | Mitigation | Monitoring | Management |
|---|---|---|---|
| Server crash | Use cloud backup | Monitor CPU load | Switch to backup server |
| Developer resigns | Cross-train team members | Track workload | Hire temporary staff |
Final Thoughts
Managing metrics, estimation, and risks ensures a successful software project. Key takeaways:
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Metrics help measure quality and efficiency.
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Proper estimation prevents cost and time overruns.
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Risk management ensures early detection and mitigation.
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Project planning and decomposition lead to better organization.
