Science & Testing
Testing is applied research into software quality using scientific approaches and evidence to help stakeholders make informed decisions
Computer Science & Software Engineering
Testing isn’t algorithms, problem solving, solution building or process management but a knowledge of both is important for testing
Quality
Defined as value to some person(s), which can include expectations met and positive feelings
Value
Primarily an ability to solve a problem, complete a task or achieve a goal making software a social or cognitive prosthesis or tool
Feelings & Emotions
Focus on people’s feelings as the indicator to quality but be careful to avoid being fooled by illusions
Expectations & Oracles
Expectations are mental models of how software works or delivers value; built from references which can be used as oracles to evaluate and identify problems
Objective vs Subjective vs Relative
Quality is subjective, relative truth with an objective, relative analysis and is formed from relationships between people and software
Quantitative vs Qualitative
Testing is journaling, note-taking and immersion resulting in a written evaluation of quality carefully supported by metrics where appropriate
Reliability vs Validity
Avoid misleading information by ensuring consistent and accurate testing through diversity of testing methods and approaches
Confirmation vs Falsification
Testing is scepticism, falsification and invalidation not confirmation, verification or demonstration
Deduction vs Induction
Testing is constantly building and falsifying hypotheses of quality using logical reasoning to uncover information
Method
Testing scientific model and process of research question, background investigation, analysis, hypothesis, experiment, evaluation, action (reporting)
Story
Quality is evaluated and communicated as stories of context known as events that contain the who, what, where, when, why and how of value to someone