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

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@@ -70,6 +70,8 @@ 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=$( extractQueryParameter "projection_node_label" "${@}" )
@@ -99,6 +101,8 @@ 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=$( extractQueryParameter "projection_node_label" "${@}" )
@@ -129,6 +133,8 @@ 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 copy.cypher‎

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// Anomaly Detection Summary: Summarizes all labelled archetypes by their anomaly score including their archetype rank. For code units with more than one archetype, the one with the higher rank is shown. 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' 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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ORDER BY codeUnit.anomalyScore DESC, archetypeRank ASC, codeUnitName ASC, archetype ASC
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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(anomalyScore, 4, 'HALF_UP') AS `Anomaly Score`
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,collect(archetype)[0] AS `Archetype`
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,collect(archetypeRank)[0] AS `Archetype Rank`
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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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//,collect(archetype)[1] AS secondaryArchetype
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//,collect(archetypeRank)[1] AS secondaryArchetypeRank

‎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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