Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
This report presents the forensic synthetic code analysis of donnemartin/system-design-primer, a Python project with 357,528 GitHub stars. SynthScan v2.0 examined 14,345 lines of code across 52 source files, recording 66 pattern matches distributed across 4 syntactic categories. The overall adjusted score of 10.7 places this repository in the Low AI signal 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 66 distinct pattern matches across 4 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 |
|---|---|---|---|---|
| HIGH | solutions/system_design/query_cache/README.md | 0 | get the stored query result from the cache. accessing a node updates its position to the front of the lru list. | STRING |
| HIGH | …ions/system_design/query_cache/query_cache_snippets.py | 0 | get the stored query result from the cache. accessing a node updates its position to the front of the lru list. | STRING |
| HIGH | solutions/object_oriented_design/lru_cache/lru_cache.py | 0 | get the stored query result from the cache. accessing a node updates its position to the front of the lru list. | STRING |
| HIGH | solutions/system_design/query_cache/README.md | 0 | set the result for the given query key in the cache. when updating an entry, updates its position to the front of the lr | STRING |
| HIGH | …ions/system_design/query_cache/query_cache_snippets.py | 0 | set the result for the given query key in the cache. when updating an entry, updates its position to the front of the lr | STRING |
| HIGH | solutions/object_oriented_design/lru_cache/lru_cache.py | 0 | set the result for the given query key in the cache. when updating an entry, updates its position to the front of the lr | STRING |
| HIGH | solutions/system_design/mint/README.md | 0 | return the year and month portions of the timestamp. | STRING |
| HIGH | solutions/system_design/mint/mint_mapreduce.py | 0 | return the year and month portions of the timestamp. | STRING |
| HIGH | solutions/system_design/pastebin/pastebin.py | 0 | return the year and month portions of the timestamp. | STRING |
| HIGH | solutions/system_design/pastebin/README.md | 0 | return the year and month portions of the timestamp. | STRING |
| HIGH | solutions/system_design/pastebin/README-zh-Hans.md | 0 | return the year and month portions of the timestamp. | STRING |
| HIGH | solutions/system_design/pastebin/pastebin.py | 0 | parse each log line, extract and transform relevant lines. emit key value pairs of the form: (2016-01, url0), 1 (2016-01 | STRING |
| HIGH | solutions/system_design/pastebin/README.md | 0 | parse each log line, extract and transform relevant lines. emit key value pairs of the form: (2016-01, url0), 1 (2016-01 | STRING |
| HIGH | solutions/system_design/pastebin/README-zh-Hans.md | 0 | parse each log line, extract and transform relevant lines. emit key value pairs of the form: (2016-01, url0), 1 (2016-01 | STRING |
| HIGH | solutions/system_design/pastebin/pastebin.py | 0 | sum values for each key. (2016-01, url0), 2 (2016-01, url1), 1 | STRING |
| HIGH | solutions/system_design/pastebin/README.md | 0 | sum values for each key. (2016-01, url0), 2 (2016-01, url1), 1 | STRING |
| HIGH | solutions/system_design/pastebin/README-zh-Hans.md | 0 | sum values for each key. (2016-01, url0), 2 (2016-01, url1), 1 | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | README.md | 226 | ### Step 1: Outline use cases, constraints, and assumptions | COMMENT |
| LOW | README.md | 239 | ### Step 2: Create a high level design | COMMENT |
| LOW | README.md | 246 | ### Step 3: Design core components | COMMENT |
| LOW | README.md | 259 | ### Step 4: Scale the design | COMMENT |
| LOW | README.md | 378 | ### Step 1: Review the scalability video lecture | COMMENT |
| LOW | README.md | 390 | ### Step 2: Review the scalability article | COMMENT |
| LOW | solutions/system_design/twitter/README.md | 7 | ## Step 1: Outline use cases and constraints | COMMENT |
| LOW | solutions/system_design/twitter/README.md | 92 | ## Step 2: Create a high level design | COMMENT |
| LOW | solutions/system_design/twitter/README.md | 98 | ## Step 3: Design core components | COMMENT |
| LOW | solutions/system_design/twitter/README.md | 222 | ## Step 4: Scale the design | COMMENT |
| LOW | solutions/system_design/query_cache/README.md | 5 | ## Step 1: Outline use cases and constraints | COMMENT |
| LOW | solutions/system_design/query_cache/README.md | 57 | ## Step 2: Create a high level design | COMMENT |
| LOW | solutions/system_design/query_cache/README.md | 63 | ## Step 3: Design core components | COMMENT |
| LOW | solutions/system_design/query_cache/README.md | 211 | ## Step 4: Scale the design | COMMENT |
| LOW | solutions/system_design/mint/README.md | 5 | ## Step 1: Outline use cases and constraints | COMMENT |
| LOW | solutions/system_design/mint/README.md | 79 | ## Step 2: Create a high level design | COMMENT |
| LOW | solutions/system_design/mint/README.md | 85 | ## Step 3: Design core components | COMMENT |
| LOW | solutions/system_design/mint/README.md | 326 | ## Step 4: Scale the design | COMMENT |
| LOW | solutions/system_design/web_crawler/README.md | 5 | ## Step 1: Outline use cases and constraints | COMMENT |
| LOW | solutions/system_design/web_crawler/README.md | 68 | ## Step 2: Create a high level design | COMMENT |
| LOW | solutions/system_design/web_crawler/README.md | 74 | ## Step 3: Design core components | COMMENT |
| LOW | solutions/system_design/web_crawler/README.md | 255 | ## Step 4: Scale the design | COMMENT |
| LOW | solutions/system_design/pastebin/README.md | 7 | ## Step 1: Outline use cases and constraints | COMMENT |
| LOW | solutions/system_design/pastebin/README.md | 78 | ## Step 2: Create a high level design | COMMENT |
| LOW | solutions/system_design/pastebin/README.md | 84 | ## Step 3: Design core components | COMMENT |
| LOW | solutions/system_design/pastebin/README.md | 234 | ## Step 4: Scale the design | COMMENT |
| LOW | solutions/system_design/sales_rank/README.md | 5 | ## Step 1: Outline use cases and constraints | COMMENT |
| LOW | solutions/system_design/sales_rank/README.md | 69 | ## Step 2: Create a high level design | COMMENT |
| LOW | solutions/system_design/sales_rank/README.md | 75 | ## Step 3: Design core components | COMMENT |
| LOW | solutions/system_design/sales_rank/README.md | 238 | ## Step 4: Scale the design | COMMENT |
| LOW | solutions/system_design/scaling_aws/README.md | 5 | ## Step 1: Outline use cases and constraints | COMMENT |
| LOW | solutions/system_design/scaling_aws/README.md | 63 | ## Step 2: Create a high level design | COMMENT |
| LOW | solutions/system_design/scaling_aws/README.md | 69 | ## Step 3: Design core components | COMMENT |
| LOW | solutions/system_design/scaling_aws/README.md | 136 | ## Step 4: Scale the design | COMMENT |
| LOW | solutions/system_design/social_graph/README.md | 5 | ## Step 1: Outline use cases and constraints | COMMENT |
| LOW | solutions/system_design/social_graph/README.md | 49 | ## Step 2: Create a high level design | COMMENT |
| LOW | solutions/system_design/social_graph/README.md | 55 | ## Step 3: Design core components | COMMENT |
| LOW | solutions/system_design/social_graph/README.md | 249 | ## Step 4: Scale the design | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | solutions/system_design/mint/README.md | 292 | def handle_budget_notifications(self, key, total): | CODE |
| LOW | solutions/system_design/mint/mint_mapreduce.py | 20 | def handle_budget_notifications(self, key, total): | CODE |
| LOW | solutions/system_design/mint/README-zh-Hans.md | 293 | def handle_budget_notifications(self, key, total): | CODE |
| LOW | …ions/system_design/web_crawler/web_crawler_snippets.py | 18 | def reduce_priority_link_to_crawl(self, url): | CODE |
| LOW | …ions/system_design/web_crawler/web_crawler_snippets.py | 22 | def extract_max_priority_page(self): | CODE |
| LOW | solutions/system_design/web_crawler/README.md | 118 | def reduce_priority_link_to_crawl(self, url) | CODE |
| LOW | solutions/system_design/web_crawler/README.md | 122 | def extract_max_priority_page(self): | CODE |
| LOW | solutions/system_design/web_crawler/README-zh-Hans.md | 116 | def reduce_priority_link_to_crawl(self, url) | CODE |
| LOW | solutions/system_design/web_crawler/README-zh-Hans.md | 120 | def extract_max_priority_page(self): | CODE |
| LOW | …ions/object_oriented_design/call_center/call_center.py | 121 | def dispatch_queued_call_to_newly_freed_employee(self, call, employee): | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | generate-epub.sh | 37 | # Check if dependencies exist | COMMENT |