Estimation Techniques

Estimation Techniques - ISTQB CTFL Guide

Introduction to Estimation Techniques

Estimation Techniques are fundamental practices in test management that help teams predict the time, resources, and effort required to complete testing activities. This guide provides a comprehensive overview of estimation techniques for the ISTQB CTFL examination.

Why Estimation Techniques Are Important

Effective estimation is crucial for several reasons:

• Resource Planning: Helps allocate human resources appropriately across testing activities
• Schedule Management: Enables realistic project timelines and deadline setting
• Cost Control: Assists in budget planning and cost forecasting
• Risk Management: Identifies potential bottlenecks and resource constraints early
• Stakeholder Communication: Provides realistic expectations to project sponsors and clients
• Quality Assurance: Ensures sufficient time is allocated for thorough testing

What Are Estimation Techniques?

Estimation techniques are systematic methods used to predict the amount of effort, time, and resources needed for testing activities. They provide a structured approach to converting past experience and available data into future predictions.

Key characteristics of estimation techniques include:

• Based on historical data and experience
• Use structured methodologies
• Account for uncertainties and risks
• Support informed decision-making
• Help create realistic project plans

Common Estimation Techniques

1. Expert Judgment

Definition: Relies on the experience and expertise of seasoned professionals to estimate testing effort.

How it works:

• Involves consultation with experienced testers or test managers
• Based on their intuitive understanding of similar projects
• Often used when historical data is unavailable
• Can be subjective but valuable for unique projects

Advantages:

• Quick to perform
• Incorporates tacit knowledge
• Useful for novel or unique projects
• Takes into account project-specific factors

Disadvantages:

• Highly subjective
• Prone to bias (optimism or pessimism)
• Lacks objective foundation
• Difficult to defend estimates

2. Analogous Estimation

Definition: Uses data from similar past projects to estimate current testing effort.

How it works:

• Identifies comparable historical projects
• Adjusts estimates based on differences between projects
• Scales effort metrics accordingly
• Requires good historical project data

Advantages:

• Grounded in actual project data
• More objective than pure expert judgment
• Relatively quick to execute
• Easy to explain and justify

Disadvantages:

• Requires reliable historical data
• Assumes similarity between projects
• May miss unique project characteristics
• Limited by available comparable data

3. Parametric Estimation

Definition: Uses statistical relationships between project variables and testing effort.

How it works:

• Identifies key parameters (lines of code, test cases, complexity)
• Establishes mathematical relationships from historical data
• Applies formulas or models to current project
• Produces estimates based on quantifiable metrics

Advantages:

• Data-driven and objective
• Can be automated
• Scalable across projects
• Provides statistical basis for estimates

Disadvantages:

• Requires substantial historical data
• Complex mathematical models needed
• May not account for qualitative factors
• Dependent on data accuracy

4. Three-Point Estimation

Definition: Uses optimistic, most likely, and pessimistic scenarios to calculate expected effort.

How it works:

• Identifies three scenarios: optimistic (best case), most likely, and pessimistic (worst case)
• Applies formula: Expected Estimate = (Optimistic + 4×Most Likely + Pessimistic) / 6
• Also known as PERT (Program Evaluation and Review Technique)
• Accounts for uncertainty and risk

Advantages:

• Accounts for uncertainty explicitly
• Provides range of possible outcomes
• Reduces impact of single-point estimates
• Encourages risk thinking

Disadvantages:

• More time-consuming than single-point estimation
• Requires defining three scenarios
• Complex calculations needed
• Subjective scenario definitions

5. Planning Poker (Agile Estimation)

Definition: A consensus-based estimation technique used in Agile teams to estimate effort collaboratively.

How it works:

• Team members independently estimate effort using cards
• Estimates typically use Fibonacci sequence (1, 2, 3, 5, 8, 13, etc.)
• Discusses differences and reaches consensus
• Iterates until agreement is reached

Advantages:

• Leverages team intelligence
• Identifies differing perspectives
• Builds team commitment
• Reduces individual bias

Disadvantages:

• Time-consuming process
• Requires all team members present
• Can be influenced by dominant personalities
• Difficult with distributed teams

6. Delphi Estimation

Definition: A structured group consensus technique where experts provide anonymous estimates.

How it works:

• Multiple experts provide estimates independently and anonymously
• Facilitator collects and summarizes estimates
• Experts receive feedback and reasons for outlier estimates
• Process repeats until consensus emerges

Advantages:

• Reduces influence of dominant personalities
• Anonymous, encouraging honest estimates
• Structured feedback process
• Often produces reliable estimates

Disadvantages:

• Lengthy and resource-intensive
• Complex process management
• Requires skilled facilitator
• May dilute expert opinions through consensus

How Estimation Techniques Work in Practice

Step 1: Gather Information

Collect details about the project, including scope, complexity, risks, and constraints.

Step 2: Select Appropriate Technique

Choose the technique that best fits your project context and available data.

Step 3: Identify Key Parameters

Define what will be estimated (effort in hours/days, number of test cases, duration, etc.).

Step 4: Apply Estimation Method

Execute the selected technique using appropriate tools and processes.

Step 5: Validate Estimates

Review estimates for reasonableness and consistency with historical data.

Step 6: Document and Communicate

Record estimates, assumptions, and rationale for stakeholder communication.

Step 7: Monitor and Adjust

Track actual effort against estimates and refine future estimates based on variances.

Exam Questions: Common Formats and Examples

Example Question 1: Selecting the Right Technique

Question: A project has extensive historical data from 15 previous similar projects. Which estimation technique would be most appropriate?

Options:

• A) Expert Judgment
• B) Analogous Estimation
• C) Parametric Estimation
• D) Three-Point Estimation

Answer: B - Analogous Estimation is ideal when reliable historical data from similar projects is available.

Example Question 2: Understanding Techniques

Question: Which estimation technique explicitly accounts for uncertainty by using optimistic, most likely, and pessimistic estimates?

Options:

• A) Planning Poker
• B) Three-Point Estimation
• C) Expert Judgment
• D) Delphi Technique

Answer: B - Three-Point Estimation (PERT) explicitly incorporates uncertainty through three scenarios.

Example Question 3: Technique Characteristics

Question: Your team is distributed across multiple time zones, making it difficult to gather for consensus meetings. Which estimation technique would be most suitable?

Options:

• A) Planning Poker
• B) Delphi Estimation
• C) Expert Judgment (one expert)
• D) Parametric Estimation

Answer: B or D - Delphi can be conducted asynchronously, or Parametric Estimation requires no team meetings if models are established.

Exam Tips: Answering Questions on Estimation Techniques

Tip 1: Know the Key Characteristics of Each Technique

Memorize distinguishing features of each technique:

• Expert Judgment: Quick, subjective, experience-based
• Analogous: Historical data-driven, comparable projects
• Parametric: Mathematical models, quantitative parameters
• Three-Point: Uncertainty modeling, PERT formula
• Planning Poker: Collaborative, consensus, Agile teams
• Delphi: Anonymous, iterative consensus, structured feedback

Tip 2: Recognize When Each Technique Is Appropriate

Questions often ask which technique fits a specific scenario. Remember:

• Use Expert Judgment when: No historical data available, quick estimate needed, unique project
• Use Analogous when: Good historical data exists, similar past projects available
• Use Parametric when: Quantifiable parameters exist, large datasets available, need scalability
• Use Three-Point when: High uncertainty, need risk ranges, formal documentation required
• Use Planning Poker when: Agile team, co-located team, need team buy-in
• Use Delphi when: Need expert consensus, distributed team, reducing bias important

Tip 3: Understand Advantages and Disadvantages

Exam questions frequently test understanding of pros and cons. Create a comparison matrix mentally:

• Questions asking "which is fastest?" → Expert Judgment or Analogous
• Questions asking "which is most objective?" → Parametric or Three-Point
• Questions asking "which reduces bias?" → Delphi or Planning Poker
• Questions asking "which accounts for uncertainty?" → Three-Point

Tip 4: Remember the Three-Point Estimation Formula

If parametric questions appear, you may need the PERT formula:

Expected Estimate = (Optimistic + 4 × Most Likely + Pessimistic) / 6

The coefficient 4 is important—it weighs the most likely estimate more heavily than the extremes.

Tip 5: Read Context Clues Carefully

Scenario questions provide hints:

• "The team is distributed globally" → Suggests Delphi or Parametric, not Planning Poker
• "We have 20 years of historical data" → Suggests Parametric or Analogous
• "The project is novel with no similar predecessors" → Suggests Expert Judgment
• "We need to account for risks" → Suggests Three-Point Estimation
• "Team members are co-located" → Suggests Planning Poker

Tip 6: Distinguish Between Estimation Accuracy and Effort

Know the effort required for each technique:

• Low Effort: Expert Judgment, Analogous (if data ready)
• Medium Effort: Three-Point, Planning Poker
• High Effort: Delphi, Parametric (model building)

Tip 7: Understand Applicability to Different Contexts

Different techniques suit different environments:

• Waterfall projects: Analogous, Parametric, Three-Point
• Agile projects: Planning Poker, Three-Point
• Large organizations: Parametric, Analogous
• Small teams: Expert Judgment, Planning Poker

Tip 8: Watch for Questions About Estimation Confidence

Some questions ask which technique provides most/least confidence:

• Most confident: Parametric (if good data), Analogous (if truly similar)
• Least confident: Expert Judgment (single person), Three-Point (ranges are wide)

Tip 9: Be Aware of Technique Combinations

Real-world practice often combines techniques:

• Use Expert Judgment to identify parameters, then Parametric Estimation for calculation
• Use Analogous as baseline, then Three-Point to add uncertainty bands
• Use Delphi to build consensus on parameters for Parametric Estimation

Tip 10: Practice with Scenario-Based Questions

The ISTQB exam emphasizes practical application:

• Read entire scenario before choosing answer
• Identify constraints and context (team size, location, data availability, time)
• Eliminate obviously wrong answers
• Select technique that best addresses scenario requirements

Tip 11: Know Common Misconceptions

Avoid these common mistakes:

• Mistake: Thinking Planning Poker works for distributed teams
• Reality: Works best with co-located teams; Delphi is better for distributed

• Mistake: Assuming Parametric Estimation is always most accurate
• Reality: Requires good historical data and established relationships

• Mistake: Believing Three-Point Estimation eliminates all uncertainty
• Reality: It quantifies uncertainty, not eliminates it

• Mistake: Thinking Expert Judgment is unreliable always
• Reality: Valuable when experts have relevant experience and data is unavailable

Tip 12: Time Management in Exam

For estimation technique questions:

• Questions typically take 45-90 seconds
• If answer isn't clear in first read, mark and return
• Look for keywords: "distributed," "historical data," "novel," "uncertainty," "collaborative"
• Use process of elimination when unsure

Summary Table of Estimation Techniques

Final Exam Strategy

Before the exam:

• Create flashcards for each technique with key attributes
• Practice with sample questions from official ISTQB materials
• Develop a mental decision tree for selecting techniques
• Review the PERT formula multiple times until automatic

During the exam:

• Read questions carefully for context clues
• Eliminate obviously incorrect answers first
• Select the technique that best matches the scenario
• Trust your preparation and avoid overthinking

Remember: Estimation Techniques questions test both knowledge of definitions and practical judgment. Understanding not just what each technique is, but when and why to use it, is essential for success on the ISTQB CTFL examination.