Bounded rationality, introduced by Herbert A. Simon, describes decision-making under cognitive and informational constraints. In foraging theory, animals make food choices based on limited sensory and cognitive resources. In economics, it explains why individuals opt for satisfactory solutions rather than optimal ones.

Optimal Foraging Theory (OFT) models how animals maximize energy intake while foraging. It applies to economics in resource allocation decisions, predicting behaviors that balance costs and benefits under constraints.

Satisficing, coined by Herbert A. Simon, refers to choosing an option that meets minimum requirements rather than optimizing. In foraging, animals select adequate food sources to conserve energy. In economics, individuals and firms settle for satisfactory outcomes due to bounded rationality.

Tacit knowledge, per Michael Polanyi, is hard-to-articulate expertise gained through experience. In software testing, it includes intuitive skills like recognizing patterns in bugs.

Biases are systematic errors in judgment. In social and cognitive science, they affect perception and decision-making.

Cognitive Biases

• Confirmation Bias: Seeking information that supports existing beliefs.
• Availability Heuristic: Overestimating the importance of readily recalled information.
• Anchoring Bias: Relying too heavily on initial information.
• Dunning-Kruger Effect: Overestimating ability at low skill levels.

Social Biases

• Stereotyping: Making assumptions based on group characteristics.
• In-group Bias: Favoring one’s own group over others.

Decision-Making Biases

• Sunk Cost Fallacy: Continuing investment due to past costs.
• Groupthink: Prioritizing consensus over critical analysis.

Perception shapes how individuals interpret sensory information, influencing testing by affecting how testers notice defects or prioritize issues.

Human factors study how ergonomic and psychological elements impact system usability, critical for designing testable software interfaces.

Heuristics are mental shortcuts used in decision-making. In testing, they guide exploratory testing but can lead to oversights if misapplied.

Deliberate practice involves focused, structured efforts to improve skills, essential for mastering complex testing techniques.

The science of play explores how playful activities foster creativity and problem-solving, applicable to innovative testing approaches.

Constructivism posits that learners build knowledge through experience, relevant for testers learning from real-world system interactions.

Interactional expertise enables communication across disciplines, while trading zones facilitate collaboration, both vital for cross-functional testing teams.

Task analysis breaks down activities into steps, helping testers identify potential failure points in workflows.

Grounded theory develops hypotheses from data, useful for testers analyzing bug patterns to inform test strategies.

• Binary Arithmetic: Operations using base-2 numbers, foundational for computing.
• Probability: Quantifies likelihood, used in risk-based testing.
• Statistics: Analyzes data to identify trends, critical for test result interpretation.
• Combinatorics: Studies combinations, applied in test case generation.
• Set Theory: Defines collections, useful for modeling system states.
• Graph Theory: Models relationships, used in network testing.
• Information Theory: Quantifies data transmission, relevant for performance testing.

• Formal Logic: Structures valid reasoning, essential for test case design.
• Lateral Thinking: Encourages creative problem-solving in testing.
• Critical Thinking: Evaluates evidence, crucial for defect analysis.
• Scientific Thinking - Plausible Reasoning: Uses probabilities to assess hypotheses.
• Scientific Thinking - Research Design: Plans systematic investigations.
• Scientific Thinking - Design of Experiments: Structures controlled tests.
• Scientific Thinking - Naturalistic Inquiry: Observes systems in real-world contexts.
• Text Analysis: Interprets documentation for test planning.
• Decision Theory: Models choices under uncertainty.
• Measurement Theory: Defines metrics for test evaluation.

• Modelling: Represents systems for analysis.
• Non-Linearity: Addresses unpredictable system behaviors.
• Complexity: Manages intricate system interactions.
• Statistics & Dynamics: Analyzes system behavior over time.

• Popular Terminology: Common testing terms and jargon.
• Schools of Testing Thought: Different testing philosophies (e.g., context-driven).
• Heuristics: Practical techniques for exploratory testing.
• Testing History: Evolution of testing practices.

• Rhetorics of Testing - Safety Language: Uses cautious language to report issues.
• Rhetorics of Testing - Tester Self-Defense: Protects testers from blame.
• Rhetorics of Testing - Test Reporting: Crafts clear defect reports.
• Interviewing People: Gathers requirements through dialogue.
• Writing and Document Design: Creates clear test documentation.
• Writing Instructions: Provides precise user guides.
• Social Legibility: Ensures clarity in team interactions.
• Semiotics: Interprets signs in user interfaces.

• Tools: Software for test automation and management.
• Data Modelling: Structures data for testing.
• Data Wrangling: Cleans data for analysis.
• Platforms & Frameworks: Environments for test execution.
• Programming: Scripts tests in code.
• Failure Studies: Analyzes system failures.
• Computer Science: Underpins testing methodologies.
• Testability: Designs systems for easier testing.

• Software Engineering Economics: Balances cost and quality.
• Software Project Management: Oversees testing projects.
• Folklore of Software Development: Common development myths.
• Agile and DevOps: Integrates testing in rapid cycles.

• Ethics: Guides responsible testing practices.
• Managing Inquiry: Directs investigative testing.
• Mission and Charters: Defines testing objectives.
• Planning, Preparing, Estimation: Organizes testing efforts.
• Negotiating for What You Need: Secures testing resources.
• Record-Keeping: Documents test processes.
• Emotional Self-Care: Supports tester well-being.
• Persuasion and Conflict Resolution: Manages team dynamics.
• Consulting and Coaching: Mentors testing teams.