ML.NET is an open source and cross-platform machine learning framework for .NET.
This report presents the forensic synthetic code analysis of dotnet/machinelearning, a C# project with 9,341 GitHub stars. SynthScan v2.0 examined 1,220,503 lines of code across 3968 source files, recording 2237 pattern matches distributed across 18 syntactic categories. The overall adjusted score of 2.7 places this repository in the Likely human-written band.
The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).
This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.
Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.
This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.
The scanner identified 2237 distinct pattern matches across 18 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.
Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | eng/common/SetupNugetSources.sh | 1 | #!/usr/bin/env bash | COMMENT |
| LOW | eng/common/vmr-sync.sh | 1 | #!/bin/bash | COMMENT |
| LOW | eng/common/vmr-sync.sh | 21 | ### | COMMENT |
| LOW | eng/common/native/init-distro-rid.sh | 1 | #!/bin/sh | COMMENT |
| LOW | eng/common/native/init-distro-rid.sh | 61 | COMMENT | |
| LOW | …common/templates-official/variables/pool-providers.yml | 1 | # Select a pool provider based off branch name. Anything with branch name containing 'release' must go into an -Svc pool | COMMENT |
| LOW | eng/common/templates/vmr-build-pr.yml | 1 | # This pipeline is used for running the VMR verification of the PR changes in repo-level PRs. | COMMENT |
| LOW | eng/common/templates/variables/pool-providers.yml | 1 | # Select a pool provider based off branch name. Anything with branch name containing 'release' must go into an -Svc pool | COMMENT |
| LOW | eng/common/core-templates/stages/renovate.yml | 1 | # -------------------------------------------------------------------------------------- | COMMENT |
| LOW | eng/common/core-templates/steps/install-microbuild.yml | 1 | parameters: | COMMENT |
| LOW | eng/common/core-templates/job/renovate.yml | 1 | # -------------------------------------------------------------------------------------- | COMMENT |
| LOW | eng/common/core-templates/job/source-build.yml | 1 | parameters: | COMMENT |
| LOW | eng/common/core-templates/job/source-build.yml | 21 | # published by source-build. | COMMENT |
| LOW | …toML.SourceGenerator/Template/SweepableEstimator_T_.cs | 1 | // ------------------------------------------------------------------------------ | COMMENT |
| LOW | ….AutoML.SourceGenerator/Template/SweepableEstimator.cs | 1 | // ------------------------------------------------------------------------------ | COMMENT |
| LOW | ….SourceGenerator/Template/SweepableEstimatorFactory.cs | 1 | // ------------------------------------------------------------------------------ | COMMENT |
| LOW | …soft.ML.AutoML.SourceGenerator/Template/SearchSpace.cs | 1 | // ------------------------------------------------------------------------------ | COMMENT |
| LOW | …soft.ML.AutoML.SourceGenerator/Template/SearchSpace.cs | 281 | /// <summary> | COMMENT |
| LOW | …ft.ML.AutoML.SourceGenerator/Template/EstimatorType.cs | 1 | // ------------------------------------------------------------------------------ | COMMENT |
| LOW | …osoft.ML.InternalCodeAnalyzer/Descriptions.Designer.cs | 1 | //------------------------------------------------------------------------------ | COMMENT |
| LOW | tools-local/Microsoft.ML.InternalCodeAnalyzer/Utils.cs | 1 | // Licensed to the .NET Foundation under one or more agreements. | COMMENT |
| LOW | test/Microsoft.ML.Core.Tests/UnitTests/TestLoss.cs | 21 | COMMENT | |
| LOW | …t/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs | 161 | CheckSameValues(data1.OutputData, data2.OutputData); | COMMENT |
| LOW | …t/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs | 181 | COMMENT | |
| LOW | …t/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs | 201 | // var postSelectDv = Env.CreateTransform("Keep{col=ColA col=ColB}", postDropDv); | COMMENT |
| LOW | …t/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs | 1441 | COMMENT | |
| LOW | …t/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs | 1461 | // } | COMMENT |
| LOW | …t/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs | 1481 | // } | COMMENT |
| LOW | test/Microsoft.ML.Core.Tests/UnitTests/TestVBuffer.cs | 1081 | /// <param name="len">The length of the vectors to generate</param> | COMMENT |
| LOW | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 2181 | /// <param name="onnxTxtName">Optional file path to write the text version of the onnx model.</param> | COMMENT |
| LOW | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 2201 | { | COMMENT |
| LOW | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 2221 | where TRow : class | COMMENT |
| LOW | …ML.Tests/TrainerEstimators/MatrixFactorizationTests.cs | 381 | // Apply the trained model to the examples with out-of-range indexes. | COMMENT |
| LOW | …ML.Tests/TrainerEstimators/MatrixFactorizationTests.cs | 501 | COMMENT | |
| LOW | …ML.Tests/TrainerEstimators/MatrixFactorizationTests.cs | 521 | // s.NumIterations = 100; | COMMENT |
| LOW | …arios/Api/CookbookSamples/CookbookSamplesDynamicApi.cs | 161 | // a caching step, which provides the same caching function, will be inserted in the considered "pipeline." | COMMENT |
| LOW | …arios/Api/CookbookSamples/CookbookSamplesDynamicApi.cs | 241 | // Inspect the model parameters. | COMMENT |
| LOW | …L.Tests/Scenarios/Api/Estimators/PredictAndMetadata.cs | 41 | COMMENT | |
| LOW | test/Microsoft.ML.TestFramework/TestCommandBase.cs | 141 | { | COMMENT |
| LOW | test/Microsoft.ML.TestFramework/TestCommandBase.cs | 401 | var paths = toCompare.Where(pa => (pa.CmpUsage & situation) != PathArgument.Usage.None).ToArray(); | COMMENT |
| LOW | test/Microsoft.ML.TestFramework/TestCommandBase.cs | 421 | return TestCoreCore(ctx, cmdName, dataPath, PathArgument.Usage.DataModel, null, ctx.ModelPath(), loaderArgs, | COMMENT |
| LOW | test/Microsoft.ML.TestFramework/TestCommandBase.cs | 461 | /// stdout</param> | COMMENT |
| LOW | test/Microsoft.ML.TestFramework/TestCommandBase.cs | 481 | { | COMMENT |
| LOW | test/Microsoft.ML.TestFramework/BaseTestBaseline.cs | 981 | if (inner != null) | COMMENT |
| LOW | …icrosoft.ML.TestFramework/DataPipe/TestDataPipeBase.cs | 161 | { | COMMENT |
| LOW | …mmon/SavePipe/SavePipeTermDictionaryNgramHash-Data.txt | 1 | #@ TextLoader{ | COMMENT |
| LOW | …t/Common/SavePipe/SavePipeCountTargetEncoding-Data.txt | 1 | #@ TextLoader{ | COMMENT |
| LOW | …t/Common/SavePipe/SavePipeTermDictionaryNgram-Data.txt | 1 | #@ TextLoader{ | COMMENT |
| LOW | …aselineOutput/Common/SavePipe/SavePipeWordBag-Data.txt | 1 | #@ TextLoader{ | COMMENT |
| LOW | …ineOutput/Common/SavePipe/SavePipeInvertHash3-Data.txt | 1 | #@ TextLoader{ | COMMENT |
| LOW | …ineOutput/Common/SavePipe/SavePipeInvertHash2-Data.txt | 1 | #@ TextLoader{ | COMMENT |
| LOW | …selineOutput/Common/SavePipe/SavePipeExprVec2-Data.txt | 1 | #@ TextLoader{ | COMMENT |
| LOW | …t/BaselineOutput/Common/SavePipe/SavePipeHash-Data.txt | 1 | #@ TextLoader{ | COMMENT |
| LOW | …mon/SavePipe/SavePipeTrainAndScoreFccFastTree-Data.txt | 1 | #@ TextLoader{ | COMMENT |
| LOW | …ineOutput/Common/SavePipe/SavePipeInvertHash4-Data.txt | 1 | #@ TextLoader{ | COMMENT |
| LOW | …ineOutput/Common/SavePipe/SavePipeInvertHash5-Data.txt | 1 | #@ TextLoader{ | COMMENT |
| LOW | …selineOutput/Common/SavePipe/SavePipeExpr-All-Data.txt | 1 | #@ TextLoader{ | COMMENT |
| LOW | …selineOutput/Common/SavePipe/SavePipeKeyToVec-Data.txt | 1 | #@ TextLoader{ | COMMENT |
| LOW | …Common/SavePipe/TestParquetPrimitiveDataTypes-Data.txt | 1 | #@ TextLoader{ | COMMENT |
| LOW | …st/BaselineOutput/Common/SavePipe/SavePipeLda-Data.txt | 1 | #@ TextLoader{ | COMMENT |
| 1852 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| CRITICAL | …oft.ML.TestFramework/Attributes/OnnxTheoryAttribute.cs | 25 | && Microsoft.ML.TestFrameworkCommon.Utility.NativeLibrary.NativeLibraryExists("onnxruntime"); | CODE |
| CRITICAL | …ML.TestFramework/Attributes/TorchSharpFactAttribute.cs | 26 | // && Microsoft.ML.TestFrameworkCommon.Utility.NativeLibrary.NativeLibraryExists("torch_cpu"); | COMMENT |
| CRITICAL | …ML.TestFramework/Attributes/TensorflowFactAttribute.cs | 26 | && Microsoft.ML.TestFrameworkCommon.Utility.NativeLibrary.NativeLibraryExists("tensorflow"); | CODE |
| CRITICAL | ….TestFramework/Attributes/TensorflowTheoryAttribute.cs | 26 | && Microsoft.ML.TestFrameworkCommon.Utility.NativeLibrary.NativeLibraryExists("tensorflow"); | CODE |
| CRITICAL⚡ | …Rank/FastRank-TrainTest-MSM-sparse-sample-test-out.txt | 16 | at Microsoft.ML.Runtime.Data.TestCommand.RunCore(IChannel ch) in C:\DotNet\machinelearning\src\Microsoft.ML.Data\Comm | CODE |
| CRITICAL⚡ | …Rank/FastRank-TrainTest-MSM-sparse-sample-test-out.txt | 17 | at Microsoft.ML.Runtime.Data.TestCommand.Run() in C:\DotNet\machinelearning\src\Microsoft.ML.Data\Commands\TestComman | CODE |
| CRITICAL⚡ | …Rank/FastRank-TrainTest-MSM-sparse-sample-test-out.txt | 18 | at Microsoft.ML.Runtime.Tools.Maml.MainCore(ConsoleEnvironment env, String args, Boolean alwaysPrintStacktrace) in C: | CODE |
| CRITICAL | test/Microsoft.ML.CodeGenerator.Tests/UtilTest.cs | 200 | var actualStr = Microsoft.ML.CodeGenerator.Utilities.Utils.Normalize(testStrArray[i]); | CODE |
| CRITICAL | test/Microsoft.ML.AutoML.Tests/TunerTests.cs | 397 | Thread.CurrentThread.CurrentCulture.NumberFormat.NumberDecimalSeparator.Should().Be("."); | CODE |
| CRITICAL | test/Microsoft.ML.AutoML.Tests/TunerTests.cs | 410 | Thread.CurrentThread.CurrentCulture.NumberFormat.NumberDecimalSeparator.Should().Be(","); | CODE |
| CRITICAL | …les/Dynamic/Trainers/Regression/LightGbmWithOptions.cs | 43 | Booster = new Microsoft.ML.Trainers.LightGbm.GossBooster.Options() | CODE |
| CRITICAL | …c/Microsoft.ML.StandardTrainers/Standard/SdcaBinary.cs | 327 | int numFeatures = data.Schema.Feature.Value.Type.GetVectorSize(); | CODE |
| CRITICAL | …c/Microsoft.ML.StandardTrainers/Standard/SdcaBinary.cs | 2026 | int numFeatures = data.Schema.Feature.Value.Type.GetVectorSize(); | CODE |
| CRITICAL | …osoft.ML.Mkl.Components/SymSgdClassificationTrainer.cs | 703 | int numFeatures = data.Schema.Feature.Value.Type.GetVectorSize(); | CODE |
| CRITICAL | src/Microsoft.ML.FastTree/FastTreeRanking.cs | 150 | FeatureCount = trainData.Schema.Feature.Value.Type.GetValueCount(); | CODE |
| CRITICAL | src/Microsoft.ML.FastTree/GamTrainer.cs | 233 | InputLength = context.TrainingSet.Schema.Feature.Value.Type.GetValueCount(); | CODE |
| CRITICAL | src/Microsoft.ML.FastTree/RandomForestClassification.cs | 224 | FeatureCount = trainData.Schema.Feature.Value.Type.GetValueCount(); | CODE |
| CRITICAL | src/Microsoft.ML.FastTree/FastTreeClassification.cs | 197 | FeatureCount = trainData.Schema.Feature.Value.Type.GetValueCount(); | CODE |
| CRITICAL | src/Microsoft.ML.FastTree/TreeEnsembleFeaturizer.cs | 655 | if (vm.InputType.GetVectorSize() != data.Schema.Feature.Value.Type.GetVectorSize()) | CODE |
| CRITICAL | src/Microsoft.ML.FastTree/TreeEnsembleFeaturizer.cs | 659 | vm.InputType.GetVectorSize(), data.Schema.Feature.Value.Type.GetVectorSize()); | CODE |
| CRITICAL | src/Microsoft.ML.FastTree/TreeEnsembleFeaturizer.cs | 726 | if (data != null && vm.InputType.GetVectorSize() != data.Schema.Feature.Value.Type.GetVectorSize()) | CODE |
| CRITICAL | src/Microsoft.ML.FastTree/TreeEnsembleFeaturizer.cs | 730 | vm.InputType.GetVectorSize(), data.Schema.Feature.Value.Type.GetVectorSize()); | CODE |
| CRITICAL | src/Microsoft.ML.FastTree/FastTreeTweedie.cs | 130 | FeatureCount = trainData.Schema.Feature.Value.Type.GetValueCount(); | CODE |
| CRITICAL | src/Microsoft.ML.FastTree/RandomForestRegression.cs | 363 | FeatureCount = trainData.Schema.Feature.Value.Type.GetValueCount(); | CODE |
| CRITICAL | src/Microsoft.ML.FastTree/FastTreeRegression.cs | 120 | FeatureCount = trainData.Schema.Feature.Value.Type.GetValueCount(); | CODE |
| CRITICAL | …soft.ML.Data/Scorers/MulticlassClassificationScorer.cs | 417 | var keyType = trainSchema.Label.Value.Annotations.Schema.GetColumnOrNull(AnnotationUtils.Kinds.KeyValues)?.T | CODE |
| CRITICAL | …soft.ML.Data/Scorers/MulticlassClassificationScorer.cs | 493 | var type = trainSchema.Label.Value.Annotations.Schema.GetColumnOrNull(AnnotationUtils.Kinds.KeyValues)?.Type | CODE |
| CRITICAL | src/Microsoft.ML.Data/Scorers/BinaryClassifierScorer.cs | 67 | var keyType = trainSchema.Label.Value.Annotations.Schema.GetColumnOrNull(AnnotationUtils.Kinds.KeyValues)?.T | CODE |
| CRITICAL | src/Microsoft.ML.Data/Utilities/StreamUtils.cs | 21 | return Microsoft.ML.Internal.IO.ZStreamIn.Open(fileName); | CODE |
| CRITICAL | src/Microsoft.ML.Data/Transforms/ValueMapping.cs | 508 | else if (Microsoft.ML.Data.Conversion.Conversions.DefaultInstance.TryParse(in value, out res)) | CODE |
| CRITICAL | …/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs | 155 | switch (data.Schema.Label.Value.Type.GetRawKind()) | CODE |
| CRITICAL | …oft.ML.TorchSharp/NasBert/TextClassificationTrainer.cs | 219 | Microsoft.ML.Internal.Utilities.Utils.MarshalActionInvoke(SaveLabelValues<int>, labelColType.ItemType.RawTyp | CODE |
| CRITICAL | …oft.ML.TorchSharp/NasBert/TextClassificationTrainer.cs | 284 | var labelGetter = Microsoft.ML.Internal.Utilities.Utils.MarshalInvoke(_decodeInitMethodInfo, vecType.ItemTyp | CODE |
| CRITICAL | src/Microsoft.ML.TorchSharp/NasBert/NerTrainer.cs | 282 | Microsoft.ML.Internal.Utilities.Utils.MarshalActionInvoke(SaveLabelValues<int>, labelColType.ItemType.RawTyp | CODE |
| CRITICAL | src/Microsoft.ML.TorchSharp/NasBert/NerTrainer.cs | 347 | var labelGetter = Microsoft.ML.Internal.Utilities.Utils.MarshalInvoke(_decodeInitMethodInfo, vecType.ItemTyp | CODE |
| CRITICAL | src/Microsoft.ML.TorchSharp/NasBert/NasBertTrainer.cs | 521 | var getter = Microsoft.ML.Internal.Utilities.Utils.MarshalInvoke(_makeLabelAnnotationGetter, this, k | CODE |
| CRITICAL | src/Microsoft.ML.TorchSharp/NasBert/NasBertTrainer.cs | 543 | var getter = Microsoft.ML.Internal.Utilities.Utils.MarshalInvoke(_makeLabelAnnotationGetter, this, k | CODE |
| CRITICAL | …t.ML.TorchSharp/AutoFormerV2/ObjectDetectionTrainer.cs | 626 | Microsoft.ML.Internal.Utilities.Utils.MarshalActionInvoke(SaveLabelValues<int>, labelColType.ItemType.RawTyp | CODE |
| CRITICAL | …t.ML.TorchSharp/AutoFormerV2/ObjectDetectionTrainer.cs | 701 | var labelGetter = Microsoft.ML.Internal.Utilities.Utils.MarshalInvoke(_decodeInitMethodInfo, vecType.ItemTyp | CODE |
| CRITICAL | …t.ML.TorchSharp/AutoFormerV2/ObjectDetectionTrainer.cs | 756 | var getter = Microsoft.ML.Internal.Utilities.Utils.MarshalInvoke(_makeLabelAnnotationGetter, this, keyTy | CODE |
| CRITICAL⚡ | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 740 | T = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.TensorProto(); | CODE |
| CRITICAL⚡ | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 748 | G = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.GraphProto(); | CODE |
| CRITICAL⚡ | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 756 | SparseTensor = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.SparseTenso | CODE |
| CRITICAL⚡ | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 4627 | TensorType = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.TypeProto | CODE |
| CRITICAL⚡ | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 4634 | SequenceType = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.TypePro | CODE |
| CRITICAL⚡ | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 4641 | MapType = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.TypeProto.Ty | CODE |
| CRITICAL⚡ | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 4648 | SparseTensorType = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.Typ | CODE |
| CRITICAL⚡ | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 4655 | OpaqueType = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.TypeProto | CODE |
| CRITICAL | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 804 | T = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.TensorProt | CODE |
| CRITICAL | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 813 | G = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.GraphProto | CODE |
| CRITICAL | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 864 | SparseTensor = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper | CODE |
| CRITICAL | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 1109 | Type = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.TypeProto(); | CODE |
| CRITICAL | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 1140 | Type = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.TypePro | CODE |
| CRITICAL | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 1903 | Graph = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.GraphProto(); | CODE |
| CRITICAL | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 1956 | Graph = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.GraphP | CODE |
| CRITICAL | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 3220 | Segment = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.TensorProto.Type | CODE |
| CRITICAL | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 3276 | Segment = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.Tens | CODE |
| CRITICAL | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 3820 | Values = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.TensorProto(); | CODE |
| CRITICAL | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 3828 | Indices = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.TensorProto(); | CODE |
| CRITICAL | src/Microsoft.ML.OnnxConverter/OnnxMl.cs | 3851 | Values = new global::Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper.Tenso | CODE |
| 14 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 90 | // Step 2: Convert ML.NET model to ONNX format and save it as a model file and a text file. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 93 | // Step 3: Check ONNX model's text format. This test will be not necessary if Step 2 can run on Linux and | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 310 | // Step 1: Test calibrator with binary prediction trainer | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 318 | // Step 2: Test calibrator without any binary prediction trainer | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 323 | // Step 3: Test calibrator with a non-default Score column name and without any binary prediction trainer | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 1783 | // Step 2: Load back the saved .idv | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 1790 | // Step 3: Create ONNX model which simply applies Identity to Label column | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 1798 | // Step 4: Get input and output names of model | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 1805 | // Step 5: Apply Onnx Model | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 1810 | // Step 6: Compare results to an onnx model created using the mappedData IDataView | COMMENT |
| LOW | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 68 | // Step 1: Create and train a ML.NET pipeline. | COMMENT |
| LOW | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 168 | // Step 2: Convert ML.NET model to ONNX format and save it as a model file and a text file. | COMMENT |
| LOW | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 209 | // Step 2: Convert ML.NET model to ONNX format and save it as a model file and a text file. | COMMENT |
| LOW | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 564 | // Step 1: Create and train a ML.NET pipeline. | COMMENT |
| LOW | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 595 | // Step 1: Create and train a ML.NET pipeline. | COMMENT |
| LOW | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 1759 | // Step 1: Load the Iris Dataset and apply a Value To Key Mapping to it. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 66 | // Step 1: Read the data as an IDataView. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 73 | // Step 2: Create a binary classifier. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 77 | // Step 3: Train the pipeline created. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 80 | // Step 4: Make prediction and evaluate its quality (on training set). | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 90 | // Step 5: Inspect the prediction of the first example. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 225 | // Step 1: Read the data as an IDataView. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 232 | // Step 2: Create a binary classifier. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 237 | // Step 3: Train the pipeline created. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 240 | // Step 4: Make prediction and evaluate its quality (on training set). | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 249 | // Step 5: Inspect the prediction of the first example. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 267 | // Step 1: Read the data as an IDataView. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 274 | // Step 2: Create a binary classifier. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 280 | // Step 3: Train the pipeline created. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 283 | // Step 4: Make prediction and evaluate its quality (on training set). | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 302 | // Step 1: Read the data as an IDataView. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 309 | // Step 2: Create a binary classifier. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 314 | // Step 3: Train the pipeline created. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 317 | // Step 4: Make prediction and evaluate its quality (on training set). | COMMENT |
| LOW | .github/workflows/ci-scan.agent.md | 83 | ## Step 1 - Select the source build | COMMENT |
| LOW | .github/workflows/ci-scan.agent.md | 94 | ## Step 2 - Walk the timeline | COMMENT |
| LOW⚡ | .github/workflows/ci-scan.agent.md | 118 | ## Step 3 - Classify each failure | COMMENT |
| LOW⚡ | .github/workflows/ci-scan.agent.md | 122 | ## Step 4 - Follow-up gate | COMMENT |
| LOW⚡ | .github/workflows/ci-scan.agent.md | 126 | ## Step 5 - Dedup | COMMENT |
| LOW⚡ | .github/workflows/ci-scan.agent.md | 130 | ## Step 6 - File the KBE | COMMENT |
| LOW⚡ | .github/workflows/ci-scan.agent.md | 134 | ## Step 7 - Tally | COMMENT |
| LOW⚡ | .github/agents/code-testing-generator.agent.md | 28 | ### Step 1: Clarify the Request | COMMENT |
| LOW⚡ | .github/agents/code-testing-generator.agent.md | 36 | ### Step 2: Choose Execution Strategy | COMMENT |
| LOW⚡ | .github/agents/code-testing-generator.agent.md | 46 | ### Step 3: Research Phase | COMMENT |
| LOW | .github/agents/code-testing-generator.agent.md | 59 | ### Step 4: Planning Phase | COMMENT |
| LOW | .github/agents/code-testing-generator.agent.md | 72 | ### Step 5: Implementation Phase | COMMENT |
| LOW | .github/agents/code-testing-generator.agent.md | 83 | ### Step 6: Final Build Validation | COMMENT |
| LOW⚡ | .github/agents/code-testing-generator.agent.md | 94 | ### Step 7: Final Test Validation | COMMENT |
| LOW⚡ | .github/agents/code-testing-generator.agent.md | 102 | ### Step 8: Coverage Gap Iteration | COMMENT |
| LOW⚡ | .github/agents/code-testing-generator.agent.md | 112 | ### Step 9: Report Results | COMMENT |
| LOW | .github/skills/code-testing-agent/SKILL.md | 66 | ### Step 1: Determine the user request | COMMENT |
| LOW | .github/skills/code-testing-agent/SKILL.md | 72 | ### Step 2: Invoke the Test Generator | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 550 | // Step 1: Get backadd wave | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 553 | // Step 2: FFT transformation | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 561 | // Step 3: Calculate mags of FFT | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 577 | // Step 4: Calculate spectral | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 585 | // Step 5: IFFT transformation | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 726 | //Step 8: Calculate Expected Value | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 735 | //Step 8: Calculated Expected Value | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 738 | //Step 9: Calculate Boundary Unit | COMMENT |
| 23 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | …toML.SourceGenerator/Template/SweepableEstimator_T_.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | ….AutoML.SourceGenerator/Template/SweepableEstimator.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | ….SourceGenerator/Template/SweepableEstimatorFactory.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | …soft.ML.AutoML.SourceGenerator/Template/SearchSpace.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | …ft.ML.AutoML.SourceGenerator/Template/EstimatorType.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | …osoft.ML.InternalCodeAnalyzer/Descriptions.Designer.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | test/Microsoft.ML.Tokenizers.Tests/BpeTests.cs | 696 | "mock testing with AI-generated scenarios: # test_database.py from unittest.mock import Mock import | CODE |
| HIGH | …es/Azure/Model/AzureObjectDetectionModelOutputClass.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | …or/Templates/Azure/Model/AzureImageModelOutputClass.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | …Generator/Templates/Azure/Console/AzureModelBuilder.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | …oft.ML.CodeGenerator/Templates/Console/ModelBuilder.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | …oft.ML.CodeGenerator/Templates/Console/ModelProject.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | …oft.ML.CodeGenerator/Templates/Console/ConsumeModel.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | …ML.CodeGenerator/Templates/Console/ModelOutputClass.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | …t.ML.CodeGenerator/Templates/Console/PredictProgram.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | …t.ML.CodeGenerator/Templates/Console/PredictProject.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | ….ML.CodeGenerator/Templates/Console/ModelInputClass.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | src/Microsoft.Data.Analysis/Strings.Designer.cs | 3 | // This code was generated by a tool. | COMMENT |
| HIGH | …crosoft.ML.Transforms/Properties/Resources.Designer.cs | 3 | // This code was generated by a tool. | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 90 | // Step 2: Convert ML.NET model to ONNX format and save it as a model file and a text file. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 93 | // Step 3: Check ONNX model's text format. This test will be not necessary if Step 2 can run on Linux and | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 310 | // Step 1: Test calibrator with binary prediction trainer | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 318 | // Step 2: Test calibrator without any binary prediction trainer | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 323 | // Step 3: Test calibrator with a non-default Score column name and without any binary prediction trainer | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 1783 | // Step 2: Load back the saved .idv | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 1790 | // Step 3: Create ONNX model which simply applies Identity to Label column | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 1798 | // Step 4: Get input and output names of model | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 1805 | // Step 5: Apply Onnx Model | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 1810 | // Step 6: Compare results to an onnx model created using the mappedData IDataView | COMMENT |
| LOW | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 68 | // Step 1: Create and train a ML.NET pipeline. | COMMENT |
| LOW | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 168 | // Step 2: Convert ML.NET model to ONNX format and save it as a model file and a text file. | COMMENT |
| LOW | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 209 | // Step 2: Convert ML.NET model to ONNX format and save it as a model file and a text file. | COMMENT |
| LOW | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 564 | // Step 1: Create and train a ML.NET pipeline. | COMMENT |
| LOW | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 595 | // Step 1: Create and train a ML.NET pipeline. | COMMENT |
| LOW | test/Microsoft.ML.Tests/OnnxConversionTest.cs | 1759 | // Step 1: Load the Iris Dataset and apply a Value To Key Mapping to it. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 66 | // Step 1: Read the data as an IDataView. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 73 | // Step 2: Create a binary classifier. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 77 | // Step 3: Train the pipeline created. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 80 | // Step 4: Make prediction and evaluate its quality (on training set). | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 90 | // Step 5: Inspect the prediction of the first example. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 225 | // Step 1: Read the data as an IDataView. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 232 | // Step 2: Create a binary classifier. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 237 | // Step 3: Train the pipeline created. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 240 | // Step 4: Make prediction and evaluate its quality (on training set). | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 249 | // Step 5: Inspect the prediction of the first example. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 267 | // Step 1: Read the data as an IDataView. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 274 | // Step 2: Create a binary classifier. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 280 | // Step 3: Train the pipeline created. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 283 | // Step 4: Make prediction and evaluate its quality (on training set). | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 302 | // Step 1: Read the data as an IDataView. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 309 | // Step 2: Create a binary classifier. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 314 | // Step 3: Train the pipeline created. | COMMENT |
| LOW⚡ | test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs | 317 | // Step 4: Make prediction and evaluate its quality (on training set). | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 550 | // Step 1: Get backadd wave | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 553 | // Step 2: FFT transformation | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 561 | // Step 3: Calculate mags of FFT | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 577 | // Step 4: Calculate spectral | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 585 | // Step 5: IFFT transformation | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 726 | //Step 8: Calculate Expected Value | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 735 | //Step 8: Calculated Expected Value | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 738 | //Step 9: Calculate Boundary Unit | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 743 | //Step 10: Calculate UpperBound and LowerBound | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 830 | //Step 8: Calculate Expected Value | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 834 | //Step 9: Calculate Boundary Unit | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 839 | //Step 10: Calculate UpperBound and LowerBound | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 847 | //Step 11: Update Anomaly Score | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 850 | //Step 12: Update IsAnomaly | COMMENT |
| LOW⚡ | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 853 | //Step 13: Update Expected Value, LowerBound and UpperBound for not anomaly points. | COMMENT |
| LOW | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 606 | // Step 6: Calculate mag and ave_mag of IFFT | COMMENT |
| LOW | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 619 | // Step 7: Calculate raw score and set result | COMMENT |
| LOW | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 714 | //Step 8: Calculate Expected Value | COMMENT |
| LOW | …/Microsoft.ML.TimeSeries/SrCnnEntireAnomalyDetector.cs | 812 | //Step 11: Update Anomaly Score, Expected Value and Boundaries | COMMENT |
| LOW⚡ | …c/Microsoft.ML.TimeSeries/SrCnnAnomalyDetectionBase.cs | 174 | // Step 1: Get backadd wave | COMMENT |
| LOW⚡ | …c/Microsoft.ML.TimeSeries/SrCnnAnomalyDetectionBase.cs | 177 | // Step 2: FftTransform transformation | COMMENT |
| LOW⚡ | …c/Microsoft.ML.TimeSeries/SrCnnAnomalyDetectionBase.cs | 183 | // Step 3: Calculate mags of FftTransform | COMMENT |
| LOW⚡ | …c/Microsoft.ML.TimeSeries/SrCnnAnomalyDetectionBase.cs | 190 | // Step 4: Calculate spectral | COMMENT |
| LOW⚡ | …c/Microsoft.ML.TimeSeries/SrCnnAnomalyDetectionBase.cs | 199 | // Step 5: IFFT transformation | COMMENT |
| LOW⚡ | …c/Microsoft.ML.TimeSeries/SrCnnAnomalyDetectionBase.cs | 220 | // Step 6: Calculate mag and ave_mag of IFFT | COMMENT |
| LOW⚡ | …c/Microsoft.ML.TimeSeries/SrCnnAnomalyDetectionBase.cs | 228 | // Step 7: Calculate score and set result | COMMENT |
| 3 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | …ommon/core-templates/steps/enable-internal-sources.yml | 24 | # If running on dnceng (internal project), just use the default behavior for NuGetAuthenticate. | COMMENT |
| MEDIUM | test/Microsoft.ML.TestFramework/TestCommandBase.cs | 640 | /// do not use this, but instead utilize the <see cref="TestCommandBase.RunContextBase.InitPath"/> | COMMENT |
| MEDIUM | …ard/LogisticRegression/MulticlassLogisticRegression.cs | 173 | // Should we instead leverage the pass made by the LBFGS base class? Ideally, it wouldn't | COMMENT |
| MEDIUM | src/Microsoft.ML.FastTree/GamTrainer.cs | 76 | /// Whether to utilize the disk or the data's native transposition facilities (where applicable) when perfor | COMMENT |
| MEDIUM | src/Microsoft.ML.FastTree/FastTreeArguments.cs | 397 | /// Whether to utilize the disk or the data's native transposition facilities (where applicable) when performing | COMMENT |
| MEDIUM | src/Microsoft.ML.TimeSeries/STL/InnerStl.cs | 113 | /// The core for the robust trend-seasonal decomposition. See the ref: http://www.wessa.net/download/stl.pdf, | COMMENT |
| MEDIUM | src/Microsoft.ML.TimeSeries/STL/Loess.cs | 132 | /// This is used for robust weight, It is one iteration step of loess. | COMMENT |
| MEDIUM | src/Microsoft.ML.TimeSeries/STL/Loess.cs | 175 | /// The number of iterations for robust regression. | COMMENT |
| MEDIUM | src/Microsoft.ML.Core/Utilities/Stats.cs | 234 | /// <remarks>Should be robust for all values of n, p</remarks> | COMMENT |
| MEDIUM | src/Microsoft.ML.Core/Data/ServerChannel.cs | 37 | /// performant though more robust calls to <see cref="Register{TRet}"/> and | COMMENT |
| MEDIUM | src/Microsoft.ML.Data/DataView/CacheDataView.cs | 740 | /// robust to that usage.) | COMMENT |
| MEDIUM | …soft.ML.Data/DataLoadSave/LegacyCompositeDataLoader.cs | 345 | /// Essentially, this is a helper method for the LoadTransform class. | COMMENT |
| MEDIUM | src/Microsoft.ML.Data/DataLoadSave/MultiFileSource.cs | 29 | /// The provided <paramref name="paths"/> can utilize wildcards to load all source files. For example: | COMMENT |
| MEDIUM | src/Microsoft.ML.Data/DataLoadSave/TransformWrapper.cs | 12 | /// Note that there are some important differences in usages that make this shimming somewhat non-seamless, so the g | COMMENT |
| MEDIUM | …c/Microsoft.ML.Data/DataLoadSave/Binary/BinarySaver.cs | 843 | /// <param name="type">The type of the codec to write and utilize</param> | COMMENT |
| MEDIUM | src/Microsoft.ML.Data/Utilities/ApplyTransformUtils.cs | 77 | // It's probably more robust to make CompositeDataLoader not even be an IDataView, this | COMMENT |
| MEDIUM | src/Microsoft.ML.Data/Transforms/Normalizer.cs | 50 | /// * Robust Scaling - Optionally centers the data and scales based on the range of data and the quantile min and ma | COMMENT |
| MEDIUM | src/Microsoft.ML.Data/Transforms/InvertHashUtils.cs | 48 | // Second choice: if key, utilize the KeyValues metadata for that key, if it has one and is text. | COMMENT |
| MEDIUM | …crosoft.ML.Data/Transforms/TrainAndScoreTransformer.cs | 103 | // Essentially, all trainer estimators when fitted return a transformer that produces scores -- which is to say, all | COMMENT |
| MEDIUM | …oft.ML.Data/Transforms/ValueToKeyMappingTransformer.cs | 69 | // REVIEW: This pattern isn't robust enough. If a new field is added, this code needs | COMMENT |
| MEDIUM | …/Microsoft.ML.Data/Transforms/LabelConvertTransform.cs | 165 | // Certainly there's nothing contractual requiring I suppress this. Should I suppress | COMMENT |
| MEDIUM | src/Microsoft.ML.Data/Dirty/IniFileUtils.cs | 19 | // TODO: Should be made more robust to handle things like "Evaluators = " sand such. | COMMENT |
| MEDIUM | src/Microsoft.ML.Data/Commands/SaveDataCommand.cs | 165 | // If it is a text saver, utilize a special utility for this purpose. | COMMENT |
| MEDIUM | …ft.ML.AutoML/API/MulticlassClassificationExperiment.cs | 32 | /// Collection of trainers the AutoML experiment can leverage. | COMMENT |
| MEDIUM | src/Microsoft.ML.AutoML/API/RecommendationExperiment.cs | 24 | /// Collection of trainers the AutoML experiment can leverage. | COMMENT |
| MEDIUM | …rosoft.ML.AutoML/API/BinaryClassificationExperiment.cs | 34 | /// Collection of trainers the AutoML experiment can leverage. | COMMENT |
| MEDIUM | src/Microsoft.ML.AutoML/API/RegressionExperiment.cs | 32 | /// Collection of trainers the AutoML experiment can leverage. | COMMENT |
| MEDIUM | src/Microsoft.ML.AutoML/API/RankingExperiment.cs | 23 | /// Collection of trainers the AutoML experiment can leverage. | COMMENT |
| MEDIUM | src/Microsoft.ML.DataView/VBuffer.cs | 368 | /// if one is doing a more involved computation involving many operations, it may be faster to utilize | COMMENT |
| MEDIUM | …osoft.ML.Transforms/MissingValueHandlingTransformer.cs | 117 | /// <param name="replaceWith">The replacement method to utilize.</param> | COMMENT |
| MEDIUM | src/Microsoft.ML.Transforms/NormalizerCatalog.cs | 327 | /// Create a <see cref="NormalizingEstimator"/>, which normalizes using statistics that are robust to outliers b | COMMENT |
| MEDIUM | src/Microsoft.ML.Transforms/NormalizerCatalog.cs | 358 | /// Create a <see cref="NormalizingEstimator"/>, which normalizes using statistics that are robust to outliers b | COMMENT |
| MEDIUM | src/Microsoft.ML.Transforms/LambdaTransform.cs | 92 | /// argument into its <typeparamref name="TDst"/> argument and can utilize the per-cursor <typeparamref name="TS | COMMENT |
| MEDIUM | …icrosoft.ML.Transforms/Text/NgramHashingTransformer.cs | 833 | // re-used. The collector will utilize its copier to make it safe, in | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | …L.Transforms/PermutationFeatureImportanceExtensions.cs | 44 | /// In this implementation, PFI computes the change in all possible regression evaluation metrics for each featu | COMMENT |
| HIGH | …L.Transforms/PermutationFeatureImportanceExtensions.cs | 107 | /// In this implementation, PFI computes the change in all possible regression evaluation metrics for each featu | COMMENT |
| HIGH | …L.Transforms/PermutationFeatureImportanceExtensions.cs | 194 | /// In this implementation, PFI computes the change in all possible binary classification evaluation metrics for | COMMENT |
| HIGH | …L.Transforms/PermutationFeatureImportanceExtensions.cs | 257 | /// In this implementation, PFI computes the change in all possible binary classification evaluation metrics for | COMMENT |
| HIGH | …L.Transforms/PermutationFeatureImportanceExtensions.cs | 348 | /// In this implementation, PFI computes the change in all possible multiclass classification evaluation metrics | COMMENT |
| HIGH | …L.Transforms/PermutationFeatureImportanceExtensions.cs | 411 | /// In this implementation, PFI computes the change in all possible multiclass classification evaluation metrics | COMMENT |
| HIGH | …L.Transforms/PermutationFeatureImportanceExtensions.cs | 507 | /// In this implementation, PFI computes the change in all possible ranking evaluation metrics for each feature, | COMMENT |
| HIGH | …L.Transforms/PermutationFeatureImportanceExtensions.cs | 572 | /// In this implementation, PFI computes the change in all possible ranking evaluation metrics for each feature, | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | …mon/Command/SavePipeTextLoaderWithMultilines-1-out.txt | 0 | bird 16 here is text after the empty line dog 17 this is a line with an empty animal "" 0 this is a line with an empty i | STRING |
| HIGH | …ommon/Command/SavePipeTextLoaderWithMultilines-out.txt | 0 | bird 16 here is text after the empty line dog 17 this is a line with an empty animal "" 0 this is a line with an empty i | STRING |
| HIGH | …d/linux-arm/SavePipeTextLoaderWithMultilines-1-out.txt | 0 | bird 16 here is text after the empty line dog 17 this is a line with an empty animal "" 0 this is a line with an empty i | STRING |
| HIGH | …and/linux-arm/SavePipeTextLoaderWithMultilines-out.txt | 0 | bird 16 here is text after the empty line dog 17 this is a line with an empty animal "" 0 this is a line with an empty i | STRING |
| HIGH | …linux-arm64/SavePipeTextLoaderWithMultilines-1-out.txt | 0 | bird 16 here is text after the empty line dog 17 this is a line with an empty animal "" 0 this is a line with an empty i | STRING |
| HIGH | …d/linux-arm64/SavePipeTextLoaderWithMultilines-out.txt | 0 | bird 16 here is text after the empty line dog 17 this is a line with an empty animal "" 0 this is a line with an empty i | STRING |
| HIGH | …cs/samples/Microsoft.ML.GenAI.Samples/MEAI/Llama3_1.cs | 0 | write a c# program to print the sum of two numbers. use top-level statement, put code between ```csharp and ```. | STRING |
| HIGH | docs/samples/Microsoft.ML.GenAI.Samples/MEAI/Phi3.cs | 0 | write a c# program to print the sum of two numbers. use top-level statement, put code between ```csharp and ```. | STRING |
| HIGH | …amples/Microsoft.ML.GenAI.Samples/Llama/LlamaSample.cs | 0 | write a c# program to print the sum of two numbers. use top-level statement, put code between ```csharp and ```. | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM⚡ | eng/common/core-templates/stages/renovate.yml | 1 | # -------------------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | eng/common/core-templates/stages/renovate.yml | 3 | # -------------------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | eng/common/core-templates/stages/renovate.yml | 9 | # -------------------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | eng/common/core-templates/job/renovate.yml | 1 | # -------------------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | eng/common/core-templates/job/renovate.yml | 3 | # -------------------------------------------------------------------------------------- | COMMENT |
| MEDIUM⚡ | eng/common/core-templates/job/renovate.yml | 17 | # -------------------------------------------------------------------------------------- | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | eng/common/tools.sh | 314 | # Check if the script is older than 30 days using timestamp file | COMMENT |
| LOW | eng/common/SetupNugetSources.sh | 59 | # Check if disabledPackageSources section exists | COMMENT |
| LOW | eng/common/SetupNugetSources.sh | 65 | # Check if this source name is disabled | COMMENT |
| LOW | eng/common/SetupNugetSources.sh | 85 | # Check if source already exists | COMMENT |
| LOW | eng/common/SetupNugetSources.sh | 115 | # Check if disabledPackageSources section exists | COMMENT |
| LOW | eng/common/SetupNugetSources.sh | 185 | # Check if there is no existing credential for this FeedName | COMMENT |
| LOW | eng/common/core-templates/steps/source-build.yml | 31 | # Check if AzDO substitutes in a build config from a variable, and use it if so. | COMMENT |
| LOW | eng/common/core-templates/steps/install-microbuild.yml | 64 | # Check if ESRP is disabled while SignType is real | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | eng/common/cross/install-debs.py | 35 | print(f"Error downloading {url}: {type(e).__name__} - {e}. Retrying...") | CODE |
| LOW | eng/common/cross/install-debs.py | 92 | except Exception as e: | CODE |
| MEDIUM | eng/common/cross/install-debs.py | 93 | print(f"Error fetching {url}: {e}") | CODE |
| MEDIUM | eng/common/cross/install-debs.py | 145 | print(f"Error: Package '{current}' was not found in the available packages.") | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | eng/common/native/install-dependencies.sh | 7 | # Usage: | COMMENT |
| LOW | …common/templates-official/variables/pool-providers.yml | 12 | # How to use: | COMMENT |
| LOW | eng/common/templates/variables/pool-providers.yml | 12 | # How to use: | COMMENT |
| LOW⚡ | eng/common/core-templates/job/renovate.yml | 11 | # Usage: | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | eng/common/cross/install-debs.py | 19 | CODE | |
| LOW | eng/common/cross/install-debs.py | 135 | CODE | |
| LOW | eng/common/cross/install-debs.py | 160 | CODE | |
| LOW | eng/common/cross/install-debs.py | 196 | CODE | |
| LOW | eng/common/cross/install-debs.py | 230 | CODE | |
| LOW | eng/common/cross/install-debs.py | 273 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | eng/common/cross/install-debs.py | 42 | async def download_deb_files_parallel(mirror, packages, tmp_dir): | CODE |
| LOW | eng/common/cross/install-debs.py | 58 | async def download_package_index_parallel(mirror, arch, suites): | CODE |
| LOW | …osoft.ML.Mkl.Components/SymSgdClassificationTrainer.cs | 528 | private sealed class InputDataManager : IDisposable | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | eng/common/cross/build-rootfs.sh | 665 | # Create the symlink in the same directory | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | .github/workflows/ci-scan-feedback.agent.md | 80 | The scanner's methodology lives in [`shared/ci-scan.instructions.md`](shared/ci-scan.instructions.md). Read it once at t | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | eng/common/cross/install-debs.py | 17 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | docs/samples/Microsoft.ML.Samples.OneDal/run_bench.py | 92 | CODE |