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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Four paper stations connect system purpose, quality goals, risk cards and focused investigation with a target and gap profile.
Architecture
LASR (Lightweight Approach for Software Reviews)
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration: scenarios and architectural decisions are connected to identified risks.
Architecture
ATAM (Architecture Tradeoff Analysis Method)
Purposedifferent
When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects.LASR helps development teams identify where their software falls short of important quality goals and which improvements to consider. A small group with existing system knowledge can make an initial assessment and investigate open questions in more detail.When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.ATAM helps teams weigh architecture decisions when quality goals compete. The team considers business goals, stakeholder expectations, and technical decisions together. The evaluation shows which risks need further investigation.
Complexitydifferent
HighMediumMediumHigh
Timedifferent
1-4 Wochen3–4 h for initial assessment; preparation and deeper analysis additional1-5 TageSeveral meetings plus preparation and analysis; total effort depends on scope
Participantsdifferent
1-61 or a small team; particularly suitable for 3–4 peopleNutzertrafficEvaluation team, architects, and relevant stakeholders
Formatdifferent
AsyncWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryLean Mission Statement describing the software’s purpose, Prioritized quality goals and evaluation criteria, Risks and estimated gaps against quality goals, More closely examined findings and open checksClick Data, Interest Signal, Learning DecisionPrioritized quality scenarios in a utility tree, Architecture risks with reasoning and assumptions, Sensitivity and trade-off points, Findings report with open investigations
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
ArchitectureQualityRiskAssessmentLean
ValidationExperimentsDemandDiscovery
ArchitectureQualityRiskTradeoffsStakeholders
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