From a02e4d5452db7509670e3421bcbba48d2d8ceedf Mon Sep 17 00:00:00 2001
From: "Quentin Dauprat, PhD" <heziode@protonmail.com>
Date: Mon, 1 Dec 2025 12:08:29 +0100
Subject: [PATCH] distance 0.1.0 (via `alr publish`) (#1691)

---
 index/di/distance/distance-0.1.0.toml | 64 +++++++++++++++++++++++++++
 1 file changed, 64 insertions(+)
 create mode 100644 index/di/distance/distance-0.1.0.toml

diff --git a/index/di/distance/distance-0.1.0.toml b/index/di/distance/distance-0.1.0.toml
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+name = "distance"
+description = "A formally verified library for calculating numeric, text distances"
+version = "0.1.0"
+
+authors = ["Heziode"]
+maintainers = ["Heziode <heziode@protonmail.com>"]
+maintainers-logins = ["heziode"]
+licenses = "Apache-2.0 WITH LLVM-exception"
+website = ""
+tags = ["ada", "spark", "distance", "metrics", "algorithms", "mathematics", "string", "similarity", "levenshtein", "geospatial", "high-integrity", "alire", "data-science"]
+
+long-description = """
+# Distance
+
+A formally verified Ada/SPARK library for computing distance and similarity metrics.
+
+## Features
+
+- **Numeric Distances**: Euclidean, Manhattan, Minkowski, Chebyshev, Canberra
+- **Statistical Measures**: Cosine Similarity
+- **Text Distances**: Levenshtein, Damerau-Levenshtein, Hamming, Jaro-Winkler, Sørensen-Dice
+
+## Highlights
+
+- Pure Ada 2012 with SPARK annotations
+- Generic implementations for flexible type support
+- No external dependencies (test suite uses AUnit)
+- Comprehensive preconditions and postconditions
+
+## Usage
+
+```ada
+with Ada.Numerics.Elementary_Functions;
+with Distance.Numeric.Signatures;
+with Distance.Numeric.Euclidean_Generic;
+
+procedure Example is
+   type Float_Vector is array (Positive range <>) of Float;
+
+   package Float_Math is new Ada.Numerics.Elementary_Functions (Float);
+   package Float_Sig is new Distance.Numeric.Signatures
+     (Element_Type => Float,
+      Zero         => 0.0,
+      One          => 1.0,
+      Sqrt         => Float_Math.Sqrt,
+      "**"         => Float_Math."**",
+      Max_Element  => Float'Last);
+
+   function Euclidean is new Distance.Numeric.Euclidean_Generic
+     (Numeric_Ops => Float_Sig, Index_Type => Positive, Vector => Float_Vector);
+
+   D : Float := Euclidean ((0.0, 0.0), (3.0, 4.0));  --  D = 5.0
+begin
+   null;
+end Example;
+```
+
+For fixed-point and integer types, you can use [Spark_Math](https://github.com/adarium-labs/spark_math) to provide the required operations.
+"""
+
+[origin]
+commit = "e265e32656db1284ef750cbd473db95424e5b215"
+url = "git+https://github.com/adarium-labs/distance.git"
+