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Add anomaly detection Markdown summary report
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‎domains/anomaly-detection/anomalyDetectionCsv.sh‎

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@@ -68,6 +68,8 @@ anomaly_detection_features() {
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# Required Parameters:
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# - projection_node_label=...
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# Label of the nodes that will be used for the projection. Example: "Package"
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# - projection_language=...
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# Name of the associated programming language. Default: "Java". Example: "Typescript"
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anomaly_detection_queries() {
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local nodeLabel
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nodeLabel=$( extractQueryParameter "projection_node_label" "${@}" )
@@ -97,6 +99,8 @@ anomaly_detection_queries() {
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# Required Parameters:
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# - projection_node_label=...
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# Label of the nodes that will be used for the projection. Example: "Package"
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# - projection_language=...
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# Name of the associated programming language. Examples: "Java", "Typescript"
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anomaly_detection_labels() {
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local nodeLabel
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nodeLabel=$( extractQueryParameter "projection_node_label" "${@}" )
@@ -127,6 +131,8 @@ anomaly_detection_labels() {
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# Label of the nodes that will be used for the projection. Example: "Package"
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# - projection_weight_property=...
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# Name of the node property that contains the dependency weight. Example: "weight"
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# - projection_language=...
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# Name of the associated programming language. Examples: "Java", "Typescript"
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anomaly_detection_csv_reports() {
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time anomaly_detection_features "${@}"
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time anomaly_detection_queries "${@}"

‎domains/anomaly-detection/summary/AnomaliesDeepDiveArchetypes.cypher‎

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// Anomaly Detection Summary: Summarizes all labelled archetypes by their anomaly score including examples. Requires all other labels/*.cypher queries to run first. Variables: projection_language, projection_node_label
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MATCH (codeUnit)
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WHERE $projection_node_label IN labels(codeUnit)
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UNWIND keys(codeUnit) AS codeUnitProperty
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WITH *
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WHERE codeUnitProperty STARTS WITH 'anomaly'
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AND codeUnitProperty ENDS WITH 'Rank'
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WITH *
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,coalesce(codeUnit.fqn, codeUnit.globalFqn, codeUnit.fileName, codeUnit.signature, codeUnit.name) AS codeUnitName
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,split(split(codeUnitProperty, 'anomaly')[1], 'Rank')[0] AS archetype
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,codeUnit[codeUnitProperty] AS archetypeRank
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,codeUnit.anomalyScore AS anomalyScore
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WITH *, collect(archetype)[0] AS archetype
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ORDER BY codeUnit.anomalyScore DESC, archetypeRank ASC, codeUnitName ASC, archetype ASC
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WITH archetype
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,anomalyScore
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,CASE WHEN codeUnit.anomalyScore <= 0 THEN 'Typical'
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WHEN codeUnit.anomalyTopFeature1 IS NULL THEN 'Undetermined'
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ELSE 'Anomalous' END AS modelStatus
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,codeUnitName
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RETURN archetype AS `Archetype`
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,count(DISTINCT codeUnitName) AS `Count`
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,round(max(anomalyScore), 4, 'HALF_UP') AS `Max. Score`
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,modelStatus AS `Model Status`
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,apoc.text.join(collect(DISTINCT codeUnitName)[0..3], ', ') AS `Examples`
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ORDER BY modelStatus, archetype, `Max. Score` DESC

‎domains/anomaly-detection/summary/AnomaliesDeepDiveOverview.cypher‎

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// Anomaly Detection DeepDive: Overview of analyzed code units and the number of anomalies detected. Requires all other labels/*.cypher queries to run first. Variables: projection_language, projection_node_label
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MATCH (codeUnit)
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WHERE $projection_node_label IN labels(codeUnit)
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AND (codeUnit.incomingDependencies IS NOT NULL
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OR codeUnit.outgoingDependencies IS NOT NULL)
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WITH sum(codeUnit.anomalyLabel) AS anomalyCount
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,sum(sign(codeUnit.anomalyAuthorityRank)) AS authorityCount
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,sum(sign(codeUnit.anomalyBottleneckRank)) AS bottleNeckCount
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,sum(sign(codeUnit.anomalyBridgeRank)) AS bridgeCount
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,sum(sign(codeUnit.anomalyHubRank)) AS hubCount
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,sum(sign(codeUnit.anomalyOutlierRank)) AS outlierCount
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//,collect(codeUnit.name)[0..4] AS exampleNames
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RETURN anomalyCount AS `Anomalies`
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,authorityCount AS `Authorities`
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,bottleNeckCount AS `Bottlenecks`
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,bridgeCount AS `Bridges`
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,hubCount AS `Hubs`
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,outlierCount AS `Outliers`
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//,exampleNames

‎domains/anomaly-detection/summary/AnomaliesInTotal.cypher‎

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// Anomaly Detection Summary: Overview of all analyzed code units in total. Requires all other labels/*.cypher queries to run first. Variables: projection_language, projection_node_label
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MATCH (codeUnit)
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WHERE (codeUnit.incomingDependencies IS NOT NULL
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OR codeUnit.outgoingDependencies IS NOT NULL)
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WITH count(DISTINCT codeUnit) AS codeUnitCount
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,sum(codeUnit.anomalyLabel) AS anomalyCount
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,sum(sign(codeUnit.anomalyAuthorityRank)) AS authorityCount
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,sum(sign(codeUnit.anomalyBottleneckRank)) AS bottleNeckCount
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,sum(sign(codeUnit.anomalyBridgeRank)) AS bridgeCount
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,sum(sign(codeUnit.anomalyHubRank)) AS hubCount
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,sum(sign(codeUnit.anomalyOutlierRank)) AS outlierCount
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//,collect(codeUnit.name)[0..4] AS exampleNames
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RETURN codeUnitCount AS `Analyzed Units`
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,anomalyCount AS `Anomalies`
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,authorityCount AS `Authorities`
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,bottleNeckCount AS `Bottlenecks`
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,bridgeCount AS `Bridges`
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,hubCount AS `Hubs`
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,outlierCount AS `Outliers`
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//,exampleNames
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ORDER BY anomalyCount DESC, codeUnitCount DESC

‎domains/anomaly-detection/summary/AnomaliesPerAbstractionLayer.cypher‎

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// Anomaly Detection Summary: Overview of analyzed code units and the number of anomalies detected. Requires all other labels/*.cypher queries to run first. Variables: projection_language, projection_node_label
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MATCH (codeUnit)
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WHERE (codeUnit.incomingDependencies IS NOT NULL
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OR codeUnit.outgoingDependencies IS NOT NULL)
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UNWIND labels(codeUnit) AS codeUnitLabel
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WITH *
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WHERE NOT codeUnitLabel STARTS WITH 'Mark4'
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AND NOT codeUnitLabel IN ['File', 'Directory', 'ByteCode', 'GenericDeclaration']
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WITH collect(codeUnitLabel) AS codeUnitLabels
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,codeUnit
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WITH apoc.text.join(codeUnitLabels, ',') AS codeUnitLabels
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,count(DISTINCT codeUnit) AS codeUnitCount
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,sum(codeUnit.anomalyLabel) AS anomalyCount
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,sum(sign(codeUnit.anomalyAuthorityRank)) AS authorityCount
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,sum(sign(codeUnit.anomalyBottleneckRank)) AS bottleNeckCount
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,sum(sign(codeUnit.anomalyBridgeRank)) AS bridgeCount
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,sum(sign(codeUnit.anomalyHubRank)) AS hubCount
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,sum(sign(codeUnit.anomalyOutlierRank)) AS outlierCount
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//,collect(codeUnit.name)[0..4] AS exampleNames
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RETURN codeUnitLabels AS `Abstraction Level`
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,codeUnitCount AS `Units`
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,anomalyCount AS `Anomalies`
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,authorityCount AS `Authorities`
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,bottleNeckCount AS `Bottlenecks`
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,bridgeCount AS `Bridges`
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,hubCount AS `Hubs`
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,outlierCount AS `Outliers`
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//,exampleNames
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ORDER BY anomalyCount DESC, codeUnitCount DESC

‎domains/anomaly-detection/summary/AnomalyDeepDiveTopAnomalies.cypher‎

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// Anomaly Detection Summary: Lists top anomalies (at most 20), the top 3 features that contributed to the decision and the archetype(s) classification (if available) they are assigned to. Requires all other labels/*.cypher queries to run first. Variables: projection_language, projection_node_label
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MATCH (codeUnit)
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WHERE $projection_node_label IN labels(codeUnit)
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AND codeUnit.anomalyScore > 0
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ORDER BY codeUnit.anomalyScore DESC
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UNWIND keys(codeUnit) AS codeUnitProperty
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WITH codeUnit
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,CASE WHEN codeUnitProperty STARTS WITH 'anomaly'
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AND codeUnitProperty ENDS WITH 'Rank'
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THEN split(split(codeUnitProperty, 'anomaly')[1], 'Rank')[0]
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END AS archetype
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,CASE WHEN codeUnitProperty STARTS WITH 'anomaly'
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AND codeUnitProperty ENDS WITH 'Rank'
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THEN codeUnit[codeUnitProperty]
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END AS archetypeRank
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ORDER BY codeUnit.anomalyScore DESC, archetypeRank ASC
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WITH codeUnit
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,coalesce(codeUnit.fqn, codeUnit.globalFqn, codeUnit.fileName, codeUnit.signature, codeUnit.name) AS codeUnitName
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,apoc.text.join(collect(DISTINCT archetype), ', ') AS archetypes
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OPTIONAL MATCH (artifact:Java:Artifact)-[:CONTAINS]->(codeUnit)
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WITH *, artifact.name AS artifactName
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OPTIONAL MATCH (projectRoot:Directory)<-[:HAS_ROOT]-(proj:TS:Project)-[:CONTAINS]->(codeUnit)
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WITH *, last(split(projectRoot.absoluteFileName, '/')) AS projectName
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OPTIONAL MATCH (codeDirectory:File:Directory)-[:CONTAINS]->(codeUnit)
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WITH *, split(replace(codeDirectory.fileName, './', ''), '/')[-2] AS directoryName
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WITH *, coalesce(artifactName, projectName, directoryName, "") AS projectName
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RETURN codeUnitName AS `Name`
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,projectName AS `Contained in`
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,round(codeUnit.anomalyScore, 4, 'HALF_UP') AS `Anomaly Score`
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,collect(archetypes)[0] AS `Archetypes`
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,nullif(codeUnit.anomalyTopFeature1, "") AS `Top Feature 1`
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,nullif(round(codeUnit.anomalyTopFeatureSHAPValue1, 4, 'HALF_UP'), 0.0) AS `Top Feature 1 SHAP`
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,nullif(codeUnit.anomalyTopFeature2, "") AS `Top Feature 2`
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,nullif(round(codeUnit.anomalyTopFeatureSHAPValue2, 4, 'HALF_UP'), 0.0) AS `Top Feature 2 SHAP`
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,nullif(codeUnit.anomalyTopFeature3, "") AS `Top Feature 3`
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,nullif(round(codeUnit.anomalyTopFeatureSHAPValue3, 4, 'HALF_UP'), 0.0) AS `Top Feature 3 SHAP`
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,CASE WHEN codeUnit.anomalyScore <= 0 THEN 'Typical'
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WHEN codeUnit.anomalyTopFeature1 IS NULL THEN 'Undetermined'
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ELSE 'Anomalous' END AS `Model Status`
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LIMIT 20

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