aws-samples / amazon-kinesis-analytics-realtime-anomaly-detection
Sample for the German article "Anomalie-Erkennung f??r Echtzeit-Datenstr??me" by Constantin Gonzalez and Florian Mair published in Big Data Insider.
Summary
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| Main Code: 254 LOC (6 files) = PY (100%) Secondary code: Test: 0 LOC (0); Generated: 0 LOC (0); Build & Deploy: 11 LOC (1); Other: 132 LOC (6); |
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| File Size: 0% long (>1000 LOC), 100% short (<= 200 LOC) | |||
| Unit Size: 74% long (>100 LOC), 10% short (<= 10 LOC) | |||
| Conditional Complexity: 0% complex (McCabe index > 50), 100% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (4 components) | ||
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1 year, 1 month old
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0% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
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| Goals: Keep the system simple and easy to change (4) | |||
Latest commit date: 2022-01-13
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2
commits
(30 days)
2
contributors
(30 days) |
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