Repository Analysis

hyperium/hyper

An HTTP library for Rust

4.5 Likely human-written View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of hyperium/hyper, a Rust project with 16,221 GitHub stars. SynthScan v2.0 examined 30,528 lines of code across 118 source files, recording 137 pattern matches distributed across 2 syntactic categories. The overall adjusted score of 4.5 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).

4.5
Adjusted Score
4.5
Raw Score
100%
Time Factor
2026-07-13
Last Push
16.2K
Stars
Rust
Language
30.5K
Lines of Code
118
Files
137
Pattern Hits
2026-07-14
Scan Date
0.00
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

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.

Severity Breakdown

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.

CRITICAL 0HIGH 0MEDIUM 0LOW 137

Directory Score Breakdown

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.

Pattern Findings

The scanner identified 137 distinct pattern matches across 2 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.

Over-Commented Block135 hits · 135 pts
SeverityFileLineSnippetContext
LOWcapi/examples/upload.c1#include <stdlib.h>COMMENT
LOWcapi/examples/client.c1#include <stdlib.h>COMMENT
LOWtests/h1_shutdown_while_buffered.rs1// Test: Ensures poll_shutdown() is never called with buffered dataCOMMENT
LOWtests/client.rs3161 async fn h2_idle_stream_does_not_pin_connection_window() {COMMENT
LOWexamples/params.rs21static NOTNUMERIC: &[u8] = b"Number field is not numeric";COMMENT
LOWexamples/hello-http2.rs61 // .await point allows the Tokio runtime to pull the task off of the thread until the taskCOMMENT
LOWexamples/single_threaded.rs1#![deny(warnings)]COMMENT
LOWbenches/connect.rs1#![feature(test)]COMMENT
LOWbenches/connect.rs21// .expect("rt build");COMMENT
LOWsrc/upgrade.rs1//! HTTP Upgrades.COMMENT
LOWsrc/upgrade.rs21//! either the appropriate method, if wanting to `CONNECT`, or headers such asCOMMENT
LOWsrc/upgrade.rs61/// was used to speak HTTP before the upgrade. It can be used directlyCOMMENT
LOWsrc/upgrade.rs81/// HTTP state machine may have already read before completing an upgrade.COMMENT
LOWsrc/upgrade.rs301 let t = TypeId::of::<T>();COMMENT
LOWsrc/error.rs1//! Error and Result module.COMMENT
LOWsrc/error.rs21/// is unspecified. **You must not depend on it.** The wording and details mayCOMMENT
LOWsrc/error.rs141 ))]COMMENT
LOWsrc/error.rs161 /// The dispatch task is gone.COMMENT
LOWsrc/error.rs201 /// reason phrase.COMMENT
LOWsrc/error.rs221 /// `content-length` and `transfer-encoding`).COMMENT
LOWsrc/error.rs261 ///COMMENT
LOWsrc/lib.rs1#![deny(missing_docs)]COMMENT
LOWsrc/lib.rs21//!COMMENT
LOWsrc/lib.rs41//! # Optional FeaturesCOMMENT
LOWsrc/lib.rs61//! [feature flags]: https://doc.rust-lang.org/cargo/reference/manifest.html#the-features-sectionCOMMENT
LOWsrc/lib.rs81//! # StabilityCOMMENT
LOWsrc/ext/h1_reason_phrase.rs1use bytes::Bytes;COMMENT
LOWsrc/ext/h1_reason_phrase.rs21/// // Print out the non-canonical reason phrase, if it has one...COMMENT
LOWsrc/ext/informational.rs1use std::sync::Arc;COMMENT
LOWsrc/ext/mod.rs1//! Extensions for HTTP messages in Hyper.COMMENT
LOWsrc/ext/mod.rs21//! // use the extensionCOMMENT
LOWsrc/ext/mod.rs61#[cfg(all(feature = "http1", feature = "client"))]COMMENT
LOWsrc/ext/mod.rs141/// [`preserve_header_case`] was set to true and the response includedCOMMENT
LOWsrc/ext/mod.rs201#[cfg(feature = "ffi")]COMMENT
LOWsrc/ext/mod.rs261 /// # ExamplesCOMMENT
LOWsrc/ext/mod.rs281 /// h_map.append(name3, value3);COMMENT
LOWsrc/body/incoming.rs41///COMMENT
LOWsrc/body/incoming.rs81///COMMENT
LOWsrc/body/incoming.rs401 tx.send(trailers).map_err(|_| crate::Error::new_closed())COMMENT
LOWsrc/body/mod.rs1//! Streaming bodies for Requests and Responses.COMMENT
LOWsrc/server/mod.rs1//! HTTP Server.COMMENT
LOWsrc/server/conn/http2.rs21pin_project! {COMMENT
LOWsrc/server/conn/http2.rs121 }COMMENT
LOWsrc/server/conn/http2.rs141 /// See <https://rustsec.org/advisories/RUSTSEC-2024-0003.html> for more information.COMMENT
LOWsrc/server/conn/http2.rs221 /// connection alive.COMMENT
LOWsrc/server/conn/mod.rs1//! Server connection API.COMMENT
LOWsrc/server/conn/http1.rs41 whereCOMMENT
LOWsrc/server/conn/http1.rs61/// http.half_close(false);COMMENT
LOWsrc/server/conn/http1.rs81 h1_writev: Option<bool>,COMMENT
LOWsrc/server/conn/http1.rs161 /// on the underlying IO.COMMENT
LOWsrc/server/conn/http1.rs301 ///COMMENT
LOWsrc/server/conn/http1.rs321 self.h1_preserve_header_case = enabled;COMMENT
LOWsrc/server/conn/http1.rs341 }COMMENT
LOWsrc/server/conn/http1.rs361 /// but may also improve performance when an IO transport doesn'tCOMMENT
LOWsrc/server/conn/http1.rs421 /// This returns a Future that must be polled in order for HTTP to beCOMMENT
LOWsrc/server/conn/http1.rs441 /// # S::Future: Send,COMMENT
LOWsrc/rt/timer.rs1//! Provides a timer trait with timer-like functions.COMMENT
LOWsrc/rt/timer.rs21//! inner: tokio::time::sleep(duration),COMMENT
LOWsrc/rt/timer.rs41//! pub(crate) inner: tokio::time::Sleep,COMMENT
LOWsrc/rt/io.rs1use std::fmt;COMMENT
75 more matches not shown…
Slop Phrases2 hits · 3 pts
SeverityFileLineSnippetContext
LOWexamples/upgrades.rs110 // Don't forget to enable upgrades on the connection.COMMENT
LOWexamples/upgrades.rs163 // Don't forget to enable upgrades on the connection.COMMENT