A classification of runtime pathologies used to describe failure patterns and possible responses.
88 · Immunity & Medicine
Nosology
in GenOS.
A classification of runtime pathologies used to describe failure patterns and possible responses.
DEFINITION AND SCIENCE
What it means
in GenOS.
Medical nosology organizes diseases by observable patterns and causes. A software failure taxonomy borrows classification discipline but is not a medical diagnostic system.
Medical nosology groups conditions by signs and causes. GenOS applies explicit grouping to runtime failure patterns, with separate evidence for each classification.
A classification of runtime pathologies used to describe failure patterns and possible responses.
Define classes C with explicit inclusion predicates P_c(x). Multi-label classification returns {c∈C:P_c(x)} and uncertainty, followed by independent response verification.
ANIMATED DIAGRAM · INTERACTIVE MODEL
01 / 03Explore the mechanism: Nosology
A qualitative teaching model of this concept. It does not run GenOS or validate its implementation.
01Collect observed failuresINPUT
02Separate failure classesMECHANISM
03Revise the taxonomyCONDITIONAL OUTCOME
Current transition · Step 1Collect observed failures
The modeled transition may proceed. Change the assumption and move through the stages to inspect the decision path.
PROCESS AND USE
How it works
at a glance.
Collect observed failures
A classification of runtime pathologies used to describe failure patterns and possible responses.
Separate failure classes
Define classes C with explicit inclusion predicates P_c(x). Multi-label classification returns {c∈C:P_c(x)} and uncertainty, followed by independent response verification.
Revise the taxonomy
Revise the taxonomy. Medical nosology organizes diseases by observable patterns and causes. A software failure taxonomy borrows classification discipline but is not a medical diagnostic system.
RUNTIME IMPLEMENTATION
What is connected,
and how far.
The linked, versioned GenOS source defines this concept's supported operations and limits. The status axes describe the implementation and evidence recorded for this entry; they do not establish general mission success, scientific equivalence or behavior beyond that scope.
The published runtime catalog covers 28 simulated conditions, nine families and 48 bounded marker transformations. Persistent application requires scoped authorization, valid targets and durable receipts; recommendations never imply automatic treatment. This is not clinical software.
Failure modes have not yet been separately cataloged for this entry; follow the source and evidence links before relying on the mechanism.
PRIMARY RESEARCH · MECHANISM LEVEL
The mechanism
behind the analogy.
Design of fault-tolerant computers
Algirdas Avižienis · AFIPS Fall Joint Computer Conference, 733–743
Original fault-tolerance design work. It motivates software failure analysis but does not validate a GenOS pathology label.
Open publication ↗Primary research describes the cited mechanism; specific technologies may instead cite their original technical documentation. These sources provide context and do not validate the GenOS implementation.
EVIDENCE AND LIMITS
Scope and validation boundaries
The linked, versioned GenOS source defines this concept's supported operations and limits. The status axes describe the implementation and evidence recorded for this entry; they do not establish general mission success, scientific equivalence or behavior beyond that scope.