From 71a1980fbcb1979b5b232309e9865629ce938994 Mon Sep 17 00:00:00 2001
From: kaustubh <kaustubh.mp007@gmail.com>
Date: Sat, 13 Jun 2026 12:53:41 +0530
Subject: [PATCH 1/3] feat: add blas/base/ndarray/ssyr2

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description: Results of running static analysis checks when committing changes.
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---
---
 .../@stdlib/blas/base/ndarray/ssyr2/README.md | 130 ++++++++
 .../base/ndarray/ssyr2/benchmark/benchmark.js | 114 +++++++
 .../blas/base/ndarray/ssyr2/docs/repl.txt     |  38 +++
 .../base/ndarray/ssyr2/docs/types/index.d.ts  |  65 ++++
 .../base/ndarray/ssyr2/docs/types/test.ts     |  75 +++++
 .../blas/base/ndarray/ssyr2/examples/index.js |  40 +++
 .../blas/base/ndarray/ssyr2/lib/index.js      |  55 ++++
 .../blas/base/ndarray/ssyr2/lib/main.js       |  80 +++++
 .../blas/base/ndarray/ssyr2/package.json      |  73 +++++
 .../blas/base/ndarray/ssyr2/test/test.js      | 302 ++++++++++++++++++
 10 files changed, 972 insertions(+)
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/README.md
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/benchmark/benchmark.js
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/repl.txt
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/index.d.ts
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/test.ts
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/examples/index.js
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/index.js
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/main.js
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/package.json
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/test/test.js

diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/README.md
new file mode 100644
index 000000000000..79cbf8a61ddd
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/README.md
@@ -0,0 +1,130 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2026 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# ssyr2
+
+> Perform the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' );
+```
+
+#### ssyr2( arrays )
+
+Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are `N` element ndarrays, and `A` is an `N` by `N` symmetric matrix.
+
+```javascript
+var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var Float32Array = require( '@stdlib/array/float32' );
+
+var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] );
+var y = new Float32Vector( [ 2.0, 1.0, 3.0 ] );
+var A = new ndarray( 'float32', new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+var alpha = scalar2ndarray( 2.0, {
+    'dtype': 'float32'
+});
+
+var out = ssyr2( [ x, y, A, alpha ] );
+// returns <ndarray>[ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ]
+
+var bool = ( out === A );
+// returns true
+```
+
+The function has the following parameters:
+
+-   **arrays**: array-like object containing the following ndarrays:
+
+    -   first one-dimensional input ndarray.
+    -   second one-dimensional input ndarray.
+    -   a two-dimensional input/output ndarray.
+    -   a zero-dimensional ndarray containing a scalar constant.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var Float32Array = require( '@stdlib/array/float32' );
+var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' );
+
+var opts = {
+    'dtype': 'float32'
+};
+
+var x = new Float32Vector( discreteUniform( 3, 0, 10, opts ) );
+var y = new Float32Vector( discreteUniform( 3, 0, 10, opts ) );
+var A = new ndarray( 'float32', new Float32Array( discreteUniform( 9, 0, 10, opts ) ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+var alpha = scalar2ndarray( 1.0, opts );
+
+var out = ssyr2( [ x, y, A, alpha ] );
+console.log( ndarray2array( out ) );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/benchmark/benchmark.js
new file mode 100644
index 000000000000..477eb2ee2329
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/benchmark/benchmark.js
@@ -0,0 +1,114 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/uniform' );
+var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var ssyr2 = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var alpha;
+	var x;
+	var y;
+	var A;
+
+	x = uniform( [ len ], -100.0, 100.0, options );
+	y = uniform( [ len ], -100.0, 100.0, options );
+	A = uniform( [ len, len ], -100.0, 100.0, options );
+
+	alpha = scalar2ndarray( 1.0, options );
+
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var z;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			z = ssyr2( [ x, y, A, alpha ] );
+			if ( typeof z !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		if ( isnanf( z.get( 0, i%len ) ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 3; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( format( '%s:len=%d', pkg, len ), f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/repl.txt
new file mode 100644
index 000000000000..0575737d93f0
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/repl.txt
@@ -0,0 +1,38 @@
+
+{{alias}}( arrays )
+    Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`,
+    where `alpha` is a scalar, `x` and `y` are `N` element ndarrays, and `A` is
+    an `N` by `N` symmetric matrix.
+
+    Parameters
+    ----------
+    arrays: ArrayLikeObject<ndarray>
+        Array-like object containing the following ndarrays:
+
+        - first one-dimensional input ndarray.
+        - second one-dimensional input ndarray.
+        - a two-dimensional input/output ndarray.
+        - a zero-dimensional ndarray containing a scalar constant.
+
+    Returns
+    -------
+    out: ndarray
+        Output ndarray.
+
+    Examples
+    --------
+    > var x = new {{alias:@stdlib/ndarray/vector/float32}}( [ 1.0, 2.0 ] );
+    > var y = new {{alias:@stdlib/ndarray/vector/float32}}( [ 3.0, 4.0 ] );
+    > var buf = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 2.0, 1.0 ] );
+    > var sh = [ 2, 2 ];
+    > var st = [ 2, 1 ];
+    > var A = new {{alias:@stdlib/ndarray/base/ctor}}( 'float32', buf, sh, st, 0, 'row-major' );
+    > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 2.0, { 'dtype': 'float32' });
+
+    > {{alias}}( [ x, y, A, alpha ] );
+    > A
+    <ndarray>[ [ 13.0, 22.0 ], [ 2.0, 33.0 ] ]
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/index.d.ts
new file mode 100644
index 000000000000..592df1696903
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/index.d.ts
@@ -0,0 +1,65 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+import { float32ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are `N` element ndarrays, and `A` is an `N` by `N` symmetric matrix.
+*
+* ## Notes
+*
+* -   The function expects the following ndarrays:
+*
+*     -   first one-dimensional input ndarray.
+*     -   second one-dimensional input ndarray.
+*     -   a two-dimensional input/output ndarray.
+*     -   a zero-dimensional ndarray containing a scalar constant.
+*
+* @param arrays - array-like object containing ndarrays
+* @returns output ndarray
+*
+* @example
+* var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var Float32Array = require( '@stdlib/array/float32' );
+*
+* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] );
+* var y = new Float32Vector( [ 2.0, 1.0, 3.0 ] );
+* var A = new ndarray( 'float32', new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
+*
+* var alpha = scalar2ndarray( 2.0, {
+*     'dtype': 'float32'
+* });
+*
+* var out = ssyr2( [ x, y, A, alpha ] );
+* // returns <ndarray>[ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ]
+*
+* var bool = ( out === A );
+* // returns true
+*/
+declare function ssyr2( arrays: [ float32ndarray, float32ndarray, float32ndarray, float32ndarray ] ): float32ndarray;
+
+
+// EXPORTS //
+
+export = ssyr2;
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/test.ts
new file mode 100644
index 000000000000..f767fff09812
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/test.ts
@@ -0,0 +1,75 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable space-in-parens */
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+	const x = zeros( [ 3 ], {
+		'dtype': 'float32'
+	});
+	const y = zeros( [ 3 ], {
+		'dtype': 'float32'
+	});
+	const A = zeros( [ 3, 3 ], {
+		'dtype': 'float32'
+	});
+	const alpha = zeros( [], {
+		'dtype': 'float32'
+	});
+
+	ssyr2( [ x, y, A, alpha ] ); // $ExpectType float32ndarray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
+{
+	ssyr2( '10' ); // $ExpectError
+	ssyr2( 10 ); // $ExpectError
+	ssyr2( true ); // $ExpectError
+	ssyr2( false ); // $ExpectError
+	ssyr2( null ); // $ExpectError
+	ssyr2( undefined ); // $ExpectError
+	ssyr2( [] ); // $ExpectError
+	ssyr2( {} ); // $ExpectError
+	ssyr2( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+	const x = zeros( [ 3 ], {
+		'dtype': 'float32'
+	});
+	const y = zeros( [ 3 ], {
+		'dtype': 'float32'
+	});
+	const A = zeros( [ 3, 3 ], {
+		'dtype': 'float32'
+	});
+	const alpha = zeros( [], {
+		'dtype': 'float32'
+	});
+
+	ssyr2(); // $ExpectError
+	ssyr2( [ x, y, A, alpha ], {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/examples/index.js
new file mode 100644
index 000000000000..4f511314b978
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/examples/index.js
@@ -0,0 +1,40 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var Float32Array = require( '@stdlib/array/float32' );
+var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var ssyr2 = require( './../lib' );
+
+var opts = {
+	'dtype': 'float32'
+};
+
+var x = new Float32Vector( discreteUniform( 3, 0, 10, opts ) );
+var y = new Float32Vector( discreteUniform( 3, 0, 10, opts ) );
+var A = new ndarray( 'float32', new Float32Array( discreteUniform( 9, 0, 10, opts ) ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+var alpha = scalar2ndarray( 1.0, opts );
+
+var out = ssyr2( [ x, y, A, alpha ] );
+console.log( ndarray2array( out ) );
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/index.js
new file mode 100644
index 000000000000..df8724e211fa
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/index.js
@@ -0,0 +1,55 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* BLAS level 2 routine to perform the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`.
+*
+* @module @stdlib/blas/base/ndarray/ssyr2
+*
+* @example
+* var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var Float32Array = require( '@stdlib/array/float32' );
+* var ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' );
+*
+* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] );
+* var y = new Float32Vector( [ 2.0, 1.0, 3.0 ] );
+* var A = new ndarray( 'float32', new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
+*
+* var alpha = scalar2ndarray( 2.0, {
+*     'dtype': 'float32'
+* });
+*
+* var out = ssyr2( [ x, y, A, alpha ] );
+* // returns <ndarray>[ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ]
+*
+* var bool = ( out === A );
+* // returns true
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/main.js
new file mode 100644
index 000000000000..9cb116519d8c
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/main.js
@@ -0,0 +1,80 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
+var getStride = require( '@stdlib/ndarray/base/stride' );
+var getOffset = require( '@stdlib/ndarray/base/offset' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' );
+var strided = require( '@stdlib/blas/base/ssyr2' ).ndarray;
+
+
+// MAIN //
+
+/**
+* Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are `N` element ndarrays, and `A` is an `N` by `N` symmetric matrix.
+*
+* ## Notes
+*
+* -   The function expects the following ndarrays:
+*
+*     -   first one-dimensional input ndarray.
+*     -   second one-dimensional input ndarray.
+*     -   a two-dimensional input/output ndarray.
+*     -   a zero-dimensional ndarray containing a scalar constant.
+*
+* @param {ArrayLikeObject<Object>} arrays - array-like object containing ndarrays
+* @returns {Object} output ndarray
+*
+* @example
+* var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var Float32Array = require( '@stdlib/array/float32' );
+*
+* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] );
+* var y = new Float32Vector( [ 2.0, 1.0, 3.0 ] );
+* var A = new ndarray( 'float32', new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
+*
+* var alpha = scalar2ndarray( 2.0, {
+*     'dtype': 'float32'
+* });
+*
+* var out = ssyr2( [ x, y, A, alpha ] );
+* // returns <ndarray>[ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ]
+*
+* var bool = ( out === A );
+* // returns true
+*/
+function ssyr2( arrays ) {
+	var alpha = ndarraylike2scalar( arrays[ 3 ] );
+	var x = arrays[ 0 ];
+	var y = arrays[ 1 ];
+	var A = arrays[ 2 ];
+	strided( 'upper', numelDimension( A, 0 ), alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ), getData( A ), getStride( A, 0 ), getStride( A, 1 ), getOffset( A ) );
+	return A;
+}
+
+
+// EXPORTS //
+
+module.exports = ssyr2;
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/package.json
new file mode 100644
index 000000000000..094a63371320
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/package.json
@@ -0,0 +1,73 @@
+{
+  "name": "@stdlib/blas/base/ndarray/ssyr2",
+  "version": "0.0.0",
+  "description": "Perform the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "mathematics",
+    "math",
+    "blas",
+    "level 2",
+    "ssyr2",
+    "linear",
+    "algebra",
+    "subroutines",
+    "symmetric",
+    "rank-2",
+    "update",
+    "vector",
+    "matrix",
+    "array",
+    "ndarray",
+    "float32",
+    "single",
+    "float32array"
+  ]
+}
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/test/test.js
new file mode 100644
index 000000000000..09b83cc25a3e
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/test/test.js
@@ -0,0 +1,302 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' );
+var Float32Array = require( '@stdlib/array/float32' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var getData = require( '@stdlib/ndarray/data-buffer' );
+var ssyr2 = require( './../lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Returns a one-dimensional ndarray.
+*
+* @private
+* @param {Collection} buffer - underlying data buffer
+* @param {NonNegativeInteger} length - number of indexed elements
+* @param {integer} stride - stride length
+* @param {NonNegativeInteger} offset - index offset
+* @returns {ndarray} one-dimensional ndarray
+*/
+function vector( buffer, length, stride, offset ) {
+	return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' );
+}
+
+/**
+* Returns a two-dimensional ndarray.
+*
+* @private
+* @param {Collection} buffer - underlying data buffer
+* @param {NonNegativeInteger} N - number of rows and columns
+* @param {integer} stride0 - stride of the first dimension
+* @param {integer} stride1 - stride of the second dimension
+* @param {NonNegativeInteger} offset - index offset
+* @returns {ndarray} two-dimensional ndarray
+*/
+function matrix( buffer, N, stride0, stride1, offset ) {
+	return new ndarray( 'float32', buffer, [ N, N ], [ stride0, stride1 ], offset, 'row-major' );
+}
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof ssyr2, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function has an arity of 1', function test( t ) {
+	t.strictEqual( ssyr2.length, 1, 'has expected arity' );
+	t.end();
+});
+
+tape( 'the function performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`', function test( t ) {
+	var expected;
+	var alpha;
+	var xbuf;
+	var ybuf;
+	var Abuf;
+	var x;
+	var y;
+	var A;
+	var v;
+
+	xbuf = new Float32Array( [ 1.0, 2.0, 3.0 ] );
+	ybuf = new Float32Array( [ 2.0, 1.0, 3.0 ] );
+	Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] );
+	x = vector( xbuf, 3, 1, 0 );
+	y = vector( ybuf, 3, 1, 0 );
+	A = matrix( Abuf, 3, 3, 1, 0 );
+	alpha = scalar2ndarray( 2.0, {
+		'dtype': 'float32'
+	});
+
+	v = ssyr2( [ x, y, A, alpha ] );
+
+	expected = new Float32Array( [ 9.0, 12.0, 21.0, 2.0, 9.0, 20.0, 3.0, 2.0, 37.0 ] );
+	t.strictEqual( v, A, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+
+	xbuf = new Float32Array( [ 1.0, 1.0, 1.0 ] );
+	ybuf = new Float32Array( [ 1.0, 1.0, 1.0 ] );
+	Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] );
+	x = vector( xbuf, 3, 1, 0 );
+	y = vector( ybuf, 3, 1, 0 );
+	A = matrix( Abuf, 3, 1, 3, 0 );
+	alpha = scalar2ndarray( 2.0, {
+		'dtype': 'float32'
+	});
+
+	v = ssyr2( [ x, y, A, alpha ] );
+
+	expected = new Float32Array( [ 5.0, 2.0, 3.0, 6.0, 5.0, 2.0, 7.0, 6.0, 5.0 ] );
+	t.strictEqual( v, A, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if `alpha` is `0`, the function returns `A` unchanged', function test( t ) {
+	var expected;
+	var alpha;
+	var xbuf;
+	var ybuf;
+	var Abuf;
+	var x;
+	var y;
+	var A;
+	var v;
+
+	xbuf = new Float32Array( [ 1.0, 2.0, 3.0 ] );
+	ybuf = new Float32Array( [ 2.0, 1.0, 3.0 ] );
+	Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] );
+	x = vector( xbuf, 3, 1, 0 );
+	y = vector( ybuf, 3, 1, 0 );
+	A = matrix( Abuf, 3, 3, 1, 0 );
+	alpha = scalar2ndarray( 0.0, {
+		'dtype': 'float32'
+	});
+
+	v = ssyr2( [ x, y, A, alpha ] );
+
+	expected = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] );
+	t.strictEqual( v, A, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports ndarrays having non-unit strides', function test( t ) {
+	var expected;
+	var alpha;
+	var xbuf;
+	var ybuf;
+	var Abuf;
+	var x;
+	var y;
+	var A;
+	var v;
+
+	xbuf = new Float32Array([
+		1.0, // 0
+		0.0,
+		2.0, // 1
+		0.0,
+		3.0  // 2
+	]);
+	x = vector( xbuf, 3, 2, 0 );
+
+	ybuf = new Float32Array([
+		2.0, // 0
+		0.0,
+		1.0, // 1
+		0.0,
+		3.0  // 2
+	]);
+	y = vector( ybuf, 3, 2, 0 );
+
+	Abuf = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+	A = matrix( Abuf, 3, 3, 1, 0 );
+	alpha = scalar2ndarray( 2.0, {
+		'dtype': 'float32'
+	});
+
+	v = ssyr2( [ x, y, A, alpha ] );
+
+	expected = new Float32Array( [ 8.0, 10.0, 18.0, 0.0, 8.0, 18.0, 0.0, 0.0, 36.0 ] );
+	t.strictEqual( v, A, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports ndarrays having negative strides', function test( t ) {
+	var expected;
+	var alpha;
+	var xbuf;
+	var ybuf;
+	var Abuf;
+	var x;
+	var y;
+	var A;
+	var v;
+
+	xbuf = new Float32Array([
+		3.0, // 2
+		2.0, // 1
+		1.0  // 0
+	]);
+	x = vector( xbuf, 3, -1, 2 );
+
+	ybuf = new Float32Array([
+		3.0, // 2
+		1.0, // 1
+		2.0  // 0
+	]);
+	y = vector( ybuf, 3, -1, 2 );
+
+	Abuf = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+	A = matrix( Abuf, 3, 3, 1, 0 );
+	alpha = scalar2ndarray( 2.0, {
+		'dtype': 'float32'
+	});
+
+	v = ssyr2( [ x, y, A, alpha ] );
+
+	expected = new Float32Array( [ 8.0, 10.0, 18.0, 0.0, 8.0, 18.0, 0.0, 0.0, 36.0 ] );
+	t.strictEqual( v, A, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports ndarrays having non-zero offsets', function test( t ) {
+	var expected;
+	var alpha;
+	var xbuf;
+	var ybuf;
+	var Abuf;
+	var x;
+	var y;
+	var A;
+	var v;
+
+	xbuf = new Float32Array([
+		0.0,
+		1.0, // 0
+		0.0,
+		2.0, // 1
+		0.0,
+		3.0  // 2
+	]);
+	x = vector( xbuf, 3, 2, 1 );
+
+	ybuf = new Float32Array([
+		0.0,
+		2.0, // 0
+		0.0,
+		1.0, // 1
+		0.0,
+		3.0  // 2
+	]);
+	y = vector( ybuf, 3, 2, 1 );
+
+	Abuf = new Float32Array([
+		999.0,
+		999.0,
+		0.0,
+		0.0,
+		0.0,
+		0.0,
+		0.0,
+		0.0,
+		0.0,
+		0.0,
+		0.0
+	]);
+	A = matrix( Abuf, 3, 3, 1, 2 );
+	alpha = scalar2ndarray( 2.0, {
+		'dtype': 'float32'
+	});
+
+	v = ssyr2( [ x, y, A, alpha ] );
+
+	expected = new Float32Array([
+		999.0,
+		999.0,
+		8.0,
+		10.0,
+		18.0,
+		0.0,
+		8.0,
+		18.0,
+		0.0,
+		0.0,
+		36.0
+	]);
+	t.strictEqual( v, A, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+	t.end();
+});

From 8258e6db8932597fe171b36d2beca990840e69de Mon Sep 17 00:00:00 2001
From: kaustubh <kaustubh.mp007@gmail.com>
Date: Mon, 13 Jul 2026 11:51:32 +0530
Subject: [PATCH 2/3] feat: add Float32Matrix and cleanup

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown_pkg_readmes
    status: passed
  - task: lint_markdown_docs
    status: na
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: passed
  - task: lint_repl_help
    status: passed
  - task: lint_javascript_src
    status: passed
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: passed
  - task: lint_javascript_tests
    status: passed
  - task: lint_javascript_benchmarks
    status: passed
  - task: lint_python
    status: na
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    status: na
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    status: na
  - task: lint_c_examples
    status: na
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    status: na
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    status: na
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    status: na
  - task: lint_typescript_declarations
    status: passed
  - task: lint_typescript_tests
    status: passed
  - task: lint_license_headers
    status: passed
---
---
 .../@stdlib/blas/base/ndarray/ssyr2/README.md | 39 ++++++----
 .../base/ndarray/ssyr2/benchmark/benchmark.js |  7 +-
 .../blas/base/ndarray/ssyr2/docs/repl.txt     | 41 ++++++-----
 .../base/ndarray/ssyr2/docs/types/index.d.ts  | 28 ++++----
 .../base/ndarray/ssyr2/docs/types/test.ts     | 10 ++-
 .../blas/base/ndarray/ssyr2/examples/index.js | 11 +--
 .../blas/base/ndarray/ssyr2/lib/index.js      | 11 +--
 .../blas/base/ndarray/ssyr2/lib/main.js       | 55 +++++++++-----
 .../blas/base/ndarray/ssyr2/package.json      |  2 +-
 .../blas/base/ndarray/ssyr2/test/test.js      | 72 +++++++++++++++++--
 10 files changed, 196 insertions(+), 80 deletions(-)

diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/README.md
index 79cbf8a61ddd..94acf7795c3d 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/README.md
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/README.md
@@ -20,7 +20,7 @@ limitations under the License.
 
 # ssyr2
 
-> Perform the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`.
+> Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`.
 
 <section class="intro">
 
@@ -38,26 +38,30 @@ var ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' );
 
 #### ssyr2( arrays )
 
-Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are `N` element ndarrays, and `A` is an `N` by `N` symmetric matrix.
+Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `N` by `N` symmetric matrix.
 
 ```javascript
+/* eslint-disable max-len */
+var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' );
 var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
 var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
-var ndarray = require( '@stdlib/ndarray/base/ctor' );
-var Float32Array = require( '@stdlib/array/float32' );
 
+var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] );
 var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] );
 var y = new Float32Vector( [ 2.0, 1.0, 3.0 ] );
-var A = new ndarray( 'float32', new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
 
+var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+    'dtype': 'int8'
+});
 var alpha = scalar2ndarray( 2.0, {
     'dtype': 'float32'
 });
 
-var out = ssyr2( [ x, y, A, alpha ] );
+var z = ssyr2( [ x, y, A, uplo, alpha ] );
 // returns <ndarray>[ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ]
 
-var bool = ( out === A );
+var bool = ( z === A );
 // returns true
 ```
 
@@ -65,10 +69,11 @@ The function has the following parameters:
 
 -   **arrays**: array-like object containing the following ndarrays:
 
-    -   first one-dimensional input ndarray.
-    -   second one-dimensional input ndarray.
-    -   a two-dimensional input/output ndarray.
-    -   a zero-dimensional ndarray containing a scalar constant.
+    -   a one-dimensional input ndarray corresponding to `x`.
+    -   a one-dimensional input ndarray corresponding to `y`.
+    -   a two-dimensional input/output ndarray corresponding to `A`.
+    -   a zero-dimensional ndarray specifying whether `A` should be referenced as an upper or lower triangular matrix.
+    -   a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`.
 
 </section>
 
@@ -87,10 +92,11 @@ The function has the following parameters:
 <!-- eslint no-undef: "error" -->
 
 ```javascript
+/* eslint-disable max-len */
 var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
-var ndarray = require( '@stdlib/ndarray/base/ctor' );
-var Float32Array = require( '@stdlib/array/float32' );
+var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' );
 var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
 var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
 var ndarray2array = require( '@stdlib/ndarray/to-array' );
 var ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' );
@@ -101,11 +107,14 @@ var opts = {
 
 var x = new Float32Vector( discreteUniform( 3, 0, 10, opts ) );
 var y = new Float32Vector( discreteUniform( 3, 0, 10, opts ) );
-var A = new ndarray( 'float32', new Float32Array( discreteUniform( 9, 0, 10, opts ) ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
+var A = new Float32Matrix( discreteUniform( 9, 0, 10, opts ).buffer, 0, [ 3, 3 ] );
 
+var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+    'dtype': 'int8'
+});
 var alpha = scalar2ndarray( 1.0, opts );
 
-var out = ssyr2( [ x, y, A, alpha ] );
+var out = ssyr2( [ x, y, A, uplo, alpha ] );
 console.log( ndarray2array( out ) );
 ```
 
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/benchmark/benchmark.js
index 477eb2ee2329..1d553e56ef8e 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/benchmark/benchmark.js
@@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/uniform' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
 var format = require( '@stdlib/string/format' );
 var pkg = require( './../package.json' ).name;
 var ssyr2 = require( './../lib' );
@@ -48,6 +49,7 @@ var options = {
 */
 function createBenchmark( len ) {
 	var alpha;
+	var uplo;
 	var x;
 	var y;
 	var A;
@@ -57,6 +59,9 @@ function createBenchmark( len ) {
 	A = uniform( [ len, len ], -100.0, 100.0, options );
 
 	alpha = scalar2ndarray( 1.0, options );
+	uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+		'dtype': 'int8'
+	});
 
 	return benchmark;
 
@@ -72,7 +77,7 @@ function createBenchmark( len ) {
 
 		b.tic();
 		for ( i = 0; i < b.iterations; i++ ) {
-			z = ssyr2( [ x, y, A, alpha ] );
+			z = ssyr2( [ x, y, A, uplo, alpha ] );
 			if ( typeof z !== 'object' ) {
 				b.fail( 'should return an ndarray' );
 			}
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/repl.txt
index 0575737d93f0..5eb758bc91ee 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/repl.txt
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/repl.txt
@@ -1,18 +1,21 @@
 
 {{alias}}( arrays )
     Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`,
-    where `alpha` is a scalar, `x` and `y` are `N` element ndarrays, and `A` is
-    an `N` by `N` symmetric matrix.
+    where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and
+    `A` is an `N` by `N` symmetric matrix.
 
     Parameters
     ----------
     arrays: ArrayLikeObject<ndarray>
         Array-like object containing the following ndarrays:
 
-        - first one-dimensional input ndarray.
-        - second one-dimensional input ndarray.
-        - a two-dimensional input/output ndarray.
-        - a zero-dimensional ndarray containing a scalar constant.
+        - a one-dimensional input ndarray corresponding to `x`.
+        - a one-dimensional input ndarray corresponding to `y`.
+        - a two-dimensional input/output ndarray corresponding to `A`.
+        - a zero-dimensional ndarray specifying whether `A` should be
+        referenced as an upper or lower triangular matrix.
+        - a zero-dimensional ndarray containing a scalar constant corresponding
+        to `alpha`.
 
     Returns
     -------
@@ -21,17 +24,23 @@
 
     Examples
     --------
-    > var x = new {{alias:@stdlib/ndarray/vector/float32}}( [ 1.0, 2.0 ] );
-    > var y = new {{alias:@stdlib/ndarray/vector/float32}}( [ 3.0, 4.0 ] );
-    > var buf = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 2.0, 1.0 ] );
-    > var sh = [ 2, 2 ];
-    > var st = [ 2, 1 ];
-    > var A = new {{alias:@stdlib/ndarray/base/ctor}}( 'float32', buf, sh, st, 0, 'row-major' );
-    > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 2.0, { 'dtype': 'float32' });
-
-    > {{alias}}( [ x, y, A, alpha ] );
+    > var xbuf = [ 1.0, 2.0, 3.0 ];
+    > var x = new {{alias:@stdlib/ndarray/vector/float32}}( xbuf );
+
+    > var ybuf = [ 2.0, 1.0, 3.0 ];
+    > var y = new {{alias:@stdlib/ndarray/vector/float32}}( ybuf );
+
+    > var abuf = [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ];
+    > var A = new {{alias:@stdlib/ndarray/matrix/float32}}( abuf );
+
+    > var uplo = {{alias:@stdlib/ndarray/from-scalar}}( 'upper' );
+
+    > var opts = { 'dtype': 'float32' };
+    > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 2.0, opts );
+
+    > {{alias}}( [ x, y, A, uplo, alpha ] );
     > A
-    <ndarray>[ [ 13.0, 22.0 ], [ 2.0, 33.0 ] ]
+    <ndarray>[ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ]
 
     See Also
     --------
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/index.d.ts
index 592df1696903..3fcd0c35e758 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/index.d.ts
@@ -20,44 +20,48 @@
 
 /// <reference types="@stdlib/types"/>
 
-import { float32ndarray } from '@stdlib/types/ndarray';
+import { float32ndarray, ndarray } from '@stdlib/types/ndarray';
 
 /**
-* Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are `N` element ndarrays, and `A` is an `N` by `N` symmetric matrix.
+* Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `N` by `N` symmetric matrix.
 *
 * ## Notes
 *
 * -   The function expects the following ndarrays:
 *
-*     -   first one-dimensional input ndarray.
-*     -   second one-dimensional input ndarray.
-*     -   a two-dimensional input/output ndarray.
-*     -   a zero-dimensional ndarray containing a scalar constant.
+*     -   a one-dimensional input ndarray corresponding to `x`.
+*     -   a one-dimensional input ndarray corresponding to `y`.
+*     -   a two-dimensional input/output ndarray corresponding to `A`.
+*     -   a zero-dimensional ndarray specifying whether `A` should be referenced as an upper or lower triangular matrix.
+*     -   a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`.
 *
 * @param arrays - array-like object containing ndarrays
 * @returns output ndarray
 *
 * @example
+* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' );
 * var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
 * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
-* var ndarray = require( '@stdlib/ndarray/base/ctor' );
-* var Float32Array = require( '@stdlib/array/float32' );
 *
+* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] );
 * var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] );
 * var y = new Float32Vector( [ 2.0, 1.0, 3.0 ] );
-* var A = new ndarray( 'float32', new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
 *
+* var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+*     'dtype': 'int8'
+* });
 * var alpha = scalar2ndarray( 2.0, {
 *     'dtype': 'float32'
 * });
 *
-* var out = ssyr2( [ x, y, A, alpha ] );
+* var z = ssyr2( [ x, y, A, uplo, alpha ] );
 * // returns <ndarray>[ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ]
 *
-* var bool = ( out === A );
+* var bool = ( z === A );
 * // returns true
 */
-declare function ssyr2( arrays: [ float32ndarray, float32ndarray, float32ndarray, float32ndarray ] ): float32ndarray;
+declare function ssyr2( arrays: [ float32ndarray, float32ndarray, float32ndarray, ndarray, float32ndarray ] ): float32ndarray;
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/test.ts
index f767fff09812..212e68837338 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/test.ts
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/test.ts
@@ -35,11 +35,14 @@ import ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' );
 	const A = zeros( [ 3, 3 ], {
 		'dtype': 'float32'
 	});
+	const uplo = zeros( [], {
+		'dtype': 'float32'
+	});
 	const alpha = zeros( [], {
 		'dtype': 'float32'
 	});
 
-	ssyr2( [ x, y, A, alpha ] ); // $ExpectType float32ndarray
+	ssyr2( [ x, y, A, uplo, alpha ] ); // $ExpectType float32ndarray
 }
 
 // The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
@@ -66,10 +69,13 @@ import ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' );
 	const A = zeros( [ 3, 3 ], {
 		'dtype': 'float32'
 	});
+	const uplo = zeros( [], {
+		'dtype': 'float32'
+	});
 	const alpha = zeros( [], {
 		'dtype': 'float32'
 	});
 
 	ssyr2(); // $ExpectError
-	ssyr2( [ x, y, A, alpha ], {} ); // $ExpectError
+	ssyr2( [ x, y, A, uplo, alpha ], {} ); // $ExpectError
 }
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/examples/index.js
index 4f511314b978..28cea18ed4d6 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/examples/index.js
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/examples/index.js
@@ -19,9 +19,9 @@
 'use strict';
 
 var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
-var ndarray = require( '@stdlib/ndarray/base/ctor' );
-var Float32Array = require( '@stdlib/array/float32' );
+var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' );
 var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
 var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
 var ndarray2array = require( '@stdlib/ndarray/to-array' );
 var ssyr2 = require( './../lib' );
@@ -32,9 +32,12 @@ var opts = {
 
 var x = new Float32Vector( discreteUniform( 3, 0, 10, opts ) );
 var y = new Float32Vector( discreteUniform( 3, 0, 10, opts ) );
-var A = new ndarray( 'float32', new Float32Array( discreteUniform( 9, 0, 10, opts ) ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
+var A = new Float32Matrix( discreteUniform( 9, 0, 10, opts ).buffer, 0, [ 3, 3 ] );
 
+var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+	'dtype': 'int8'
+});
 var alpha = scalar2ndarray( 1.0, opts );
 
-var out = ssyr2( [ x, y, A, alpha ] );
+var out = ssyr2( [ x, y, A, uplo, alpha ] );
 console.log( ndarray2array( out ) );
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/index.js
index df8724e211fa..39d32f448497 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/index.js
@@ -24,21 +24,24 @@
 * @module @stdlib/blas/base/ndarray/ssyr2
 *
 * @example
+* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' );
 * var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
 * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
-* var ndarray = require( '@stdlib/ndarray/base/ctor' );
-* var Float32Array = require( '@stdlib/array/float32' );
 * var ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' );
 *
 * var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] );
 * var y = new Float32Vector( [ 2.0, 1.0, 3.0 ] );
-* var A = new ndarray( 'float32', new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
+* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] );
 *
 * var alpha = scalar2ndarray( 2.0, {
 *     'dtype': 'float32'
 * });
 *
-* var out = ssyr2( [ x, y, A, alpha ] );
+* var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+*     'dtype': 'int8'
+* });
+* var out = ssyr2( [ x, y, A, uplo, alpha ] );
 * // returns <ndarray>[ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ]
 *
 * var bool = ( out === A );
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/main.js
index 9cb116519d8c..dbfee65b3777 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/main.js
@@ -20,10 +20,12 @@
 
 // MODULES //
 
-var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
+var getShape = require( '@stdlib/ndarray/base/shape' );
+var getStrides = require( '@stdlib/ndarray/base/strides' );
 var getStride = require( '@stdlib/ndarray/base/stride' );
 var getOffset = require( '@stdlib/ndarray/base/offset' );
 var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' );
 var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' );
 var strided = require( '@stdlib/blas/base/ssyr2' ).ndarray;
 
@@ -31,46 +33,63 @@ var strided = require( '@stdlib/blas/base/ssyr2' ).ndarray;
 // MAIN //
 
 /**
-* Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are `N` element ndarrays, and `A` is an `N` by `N` symmetric matrix.
+* Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `N` by `N` symmetric matrix.
 *
 * ## Notes
 *
 * -   The function expects the following ndarrays:
-*
-*     -   first one-dimensional input ndarray.
-*     -   second one-dimensional input ndarray.
-*     -   a two-dimensional input/output ndarray.
-*     -   a zero-dimensional ndarray containing a scalar constant.
+*     -   a one-dimensional input ndarray corresponding to `x`.
+*     -   a one-dimensional input ndarray corresponding to `y`.
+*     -   a two-dimensional input/output ndarray corresponding to `A`.
+*     -   a zero-dimensional ndarray specifying whether `A` should be referenced as an upper or lower triangular matrix.
+*     -   a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`.
 *
 * @param {ArrayLikeObject<Object>} arrays - array-like object containing ndarrays
 * @returns {Object} output ndarray
 *
-* @example
+* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' );
 * var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
 * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
-* var ndarray = require( '@stdlib/ndarray/base/ctor' );
-* var Float32Array = require( '@stdlib/array/float32' );
 *
+* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] );
 * var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] );
 * var y = new Float32Vector( [ 2.0, 1.0, 3.0 ] );
-* var A = new ndarray( 'float32', new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
 *
+* var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+*     'dtype': 'int8'
+* });
 * var alpha = scalar2ndarray( 2.0, {
 *     'dtype': 'float32'
 * });
 *
-* var out = ssyr2( [ x, y, A, alpha ] );
+* var z = ssyr2( [ x, y, A, uplo, alpha ] );
 * // returns <ndarray>[ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ]
 *
-* var bool = ( out === A );
+* var bool = ( z === A );
 * // returns true
 */
 function ssyr2( arrays ) {
-	var alpha = ndarraylike2scalar( arrays[ 3 ] );
-	var x = arrays[ 0 ];
-	var y = arrays[ 1 ];
-	var A = arrays[ 2 ];
-	strided( 'upper', numelDimension( A, 0 ), alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ), getData( A ), getStride( A, 0 ), getStride( A, 1 ), getOffset( A ) );
+	var alpha;
+	var uplo;
+	var sh;
+	var st;
+	var A;
+	var x;
+	var y;
+
+	x = arrays[ 0 ];
+	y = arrays[ 1 ];
+	A = arrays[ 2 ];
+
+	uplo = resolveStr( ndarraylike2scalar( arrays[ 3 ] ) );
+	alpha = ndarraylike2scalar( arrays[ 4 ] );
+
+	sh = getShape( A, false );
+	st = getStrides( A, false );
+
+	strided( uplo, sh[ 0 ], alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ), getData( A ), st[ 0 ], st[ 1 ], getOffset( A ) );
+
 	return A;
 }
 
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/package.json
index 094a63371320..50528550dfc9 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/package.json
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/package.json
@@ -1,7 +1,7 @@
 {
   "name": "@stdlib/blas/base/ndarray/ssyr2",
   "version": "0.0.0",
-  "description": "Perform the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`.",
+  "description": "Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`.",
   "license": "Apache-2.0",
   "author": {
     "name": "The Stdlib Authors",
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/test/test.js
index 09b83cc25a3e..5ff9dac5db21 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/test/test.js
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/test/test.js
@@ -24,6 +24,7 @@ var tape = require( 'tape' );
 var isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' );
 var Float32Array = require( '@stdlib/array/float32' );
 var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
 var ndarray = require( '@stdlib/ndarray/base/ctor' );
 var getData = require( '@stdlib/ndarray/data-buffer' );
 var ssyr2 = require( './../lib' );
@@ -74,12 +75,13 @@ tape( 'the function has an arity of 1', function test( t ) {
 	t.end();
 });
 
-tape( 'the function performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`', function test( t ) {
+tape( 'the function performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A` (upper)', function test( t ) {
 	var expected;
 	var alpha;
 	var xbuf;
 	var ybuf;
 	var Abuf;
+	var uplo;
 	var x;
 	var y;
 	var A;
@@ -95,7 +97,10 @@ tape( 'the function performs the symmetric rank 2 operation `A = alpha*x*y^T + a
 		'dtype': 'float32'
 	});
 
-	v = ssyr2( [ x, y, A, alpha ] );
+	uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+		'dtype': 'int8'
+	});
+	v = ssyr2( [ x, y, A, uplo, alpha ] );
 
 	expected = new Float32Array( [ 9.0, 12.0, 21.0, 2.0, 9.0, 20.0, 3.0, 2.0, 37.0 ] );
 	t.strictEqual( v, A, 'returns expected value' );
@@ -111,7 +116,10 @@ tape( 'the function performs the symmetric rank 2 operation `A = alpha*x*y^T + a
 		'dtype': 'float32'
 	});
 
-	v = ssyr2( [ x, y, A, alpha ] );
+	uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+		'dtype': 'int8'
+	});
+	v = ssyr2( [ x, y, A, uplo, alpha ] );
 
 	expected = new Float32Array( [ 5.0, 2.0, 3.0, 6.0, 5.0, 2.0, 7.0, 6.0, 5.0 ] );
 	t.strictEqual( v, A, 'returns expected value' );
@@ -120,12 +128,47 @@ tape( 'the function performs the symmetric rank 2 operation `A = alpha*x*y^T + a
 	t.end();
 });
 
+tape( 'the function performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A` (lower)', function test( t ) {
+	var expected;
+	var alpha;
+	var xbuf;
+	var ybuf;
+	var Abuf;
+	var uplo;
+	var x;
+	var y;
+	var A;
+	var v;
+
+	xbuf = new Float32Array( [ 1.0, 2.0, 3.0 ] );
+	ybuf = new Float32Array( [ 2.0, 1.0, 3.0 ] );
+	Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] );
+	x = vector( xbuf, 3, 1, 0 );
+	y = vector( ybuf, 3, 1, 0 );
+	A = matrix( Abuf, 3, 3, 1, 0 );
+	alpha = scalar2ndarray( 2.0, {
+		'dtype': 'float32'
+	});
+
+	uplo = scalar2ndarray( resolveEnum( 'lower' ), {
+		'dtype': 'int8'
+	});
+	v = ssyr2( [ x, y, A, uplo, alpha ] );
+
+	expected = new Float32Array( [ 9.0, 2.0, 3.0, 12.0, 9.0, 2.0, 21.0, 20.0, 37.0 ] );
+	t.strictEqual( v, A, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+
+	t.end();
+});
+
 tape( 'if `alpha` is `0`, the function returns `A` unchanged', function test( t ) {
 	var expected;
 	var alpha;
 	var xbuf;
 	var ybuf;
 	var Abuf;
+	var uplo;
 	var x;
 	var y;
 	var A;
@@ -141,7 +184,10 @@ tape( 'if `alpha` is `0`, the function returns `A` unchanged', function test( t
 		'dtype': 'float32'
 	});
 
-	v = ssyr2( [ x, y, A, alpha ] );
+	uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+		'dtype': 'int8'
+	});
+	v = ssyr2( [ x, y, A, uplo, alpha ] );
 
 	expected = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] );
 	t.strictEqual( v, A, 'returns expected value' );
@@ -156,6 +202,7 @@ tape( 'the function supports ndarrays having non-unit strides', function test( t
 	var xbuf;
 	var ybuf;
 	var Abuf;
+	var uplo;
 	var x;
 	var y;
 	var A;
@@ -185,7 +232,10 @@ tape( 'the function supports ndarrays having non-unit strides', function test( t
 		'dtype': 'float32'
 	});
 
-	v = ssyr2( [ x, y, A, alpha ] );
+	uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+		'dtype': 'int8'
+	});
+	v = ssyr2( [ x, y, A, uplo, alpha ] );
 
 	expected = new Float32Array( [ 8.0, 10.0, 18.0, 0.0, 8.0, 18.0, 0.0, 0.0, 36.0 ] );
 	t.strictEqual( v, A, 'returns expected value' );
@@ -199,6 +249,7 @@ tape( 'the function supports ndarrays having negative strides', function test( t
 	var xbuf;
 	var ybuf;
 	var Abuf;
+	var uplo;
 	var x;
 	var y;
 	var A;
@@ -224,7 +275,10 @@ tape( 'the function supports ndarrays having negative strides', function test( t
 		'dtype': 'float32'
 	});
 
-	v = ssyr2( [ x, y, A, alpha ] );
+	uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+		'dtype': 'int8'
+	});
+	v = ssyr2( [ x, y, A, uplo, alpha ] );
 
 	expected = new Float32Array( [ 8.0, 10.0, 18.0, 0.0, 8.0, 18.0, 0.0, 0.0, 36.0 ] );
 	t.strictEqual( v, A, 'returns expected value' );
@@ -238,6 +292,7 @@ tape( 'the function supports ndarrays having non-zero offsets', function test( t
 	var xbuf;
 	var ybuf;
 	var Abuf;
+	var uplo;
 	var x;
 	var y;
 	var A;
@@ -281,7 +336,10 @@ tape( 'the function supports ndarrays having non-zero offsets', function test( t
 		'dtype': 'float32'
 	});
 
-	v = ssyr2( [ x, y, A, alpha ] );
+	uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+		'dtype': 'int8'
+	});
+	v = ssyr2( [ x, y, A, uplo, alpha ] );
 
 	expected = new Float32Array([
 		999.0,

From c01e89bcb2703944a7ca990b7aeb446fb97969c3 Mon Sep 17 00:00:00 2001
From: Kaustubh Patange <kaustubh.mp007@gmail.com>
Date: Tue, 14 Jul 2026 11:53:32 +0530
Subject: [PATCH 3/3] Apply suggestions from code review

Co-authored-by: Kaustubh Patange <kaustubh.mp007@gmail.com>
Signed-off-by: Kaustubh Patange <kaustubh.mp007@gmail.com>
---
 .../@stdlib/blas/base/ndarray/ssyr2/README.md    | 16 ++++++++--------
 .../blas/base/ndarray/ssyr2/examples/index.js    | 10 ++++------
 .../@stdlib/blas/base/ndarray/ssyr2/lib/main.js  |  3 +--
 3 files changed, 13 insertions(+), 16 deletions(-)

diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/README.md
index 94acf7795c3d..49e4e4b4ed3e 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/README.md
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/README.md
@@ -40,8 +40,9 @@ var ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' );
 
 Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `N` by `N` symmetric matrix.
 
+<!-- eslint-disable max-len -->
+
 ```javascript
-/* eslint-disable max-len */
 var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' );
 var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
 var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
@@ -89,13 +90,12 @@ The function has the following parameters:
 
 ## Examples
 
+<!-- eslint-disable max-len -->
+
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-/* eslint-disable max-len */
-var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
-var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' );
-var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+var discreteUniform = require( '@stdlib/random/discrete-uniform' );
 var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
 var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
 var ndarray2array = require( '@stdlib/ndarray/to-array' );
@@ -105,9 +105,9 @@ var opts = {
     'dtype': 'float32'
 };
 
-var x = new Float32Vector( discreteUniform( 3, 0, 10, opts ) );
-var y = new Float32Vector( discreteUniform( 3, 0, 10, opts ) );
-var A = new Float32Matrix( discreteUniform( 9, 0, 10, opts ).buffer, 0, [ 3, 3 ] );
+var x = discreteUniform( [ 3 ], 0, 10, opts );
+var y = discreteUniform( [ 3 ], 0, 10, opts );
+var A = discreteUniform( [ 3, 3 ], 0, 10, opts );
 
 var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
     'dtype': 'int8'
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/examples/index.js
index 28cea18ed4d6..c1a14308e102 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/examples/index.js
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/examples/index.js
@@ -18,9 +18,7 @@
 
 'use strict';
 
-var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
-var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' );
-var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
+var discreteUniform = require( '@stdlib/random/discrete-uniform' );
 var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
 var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
 var ndarray2array = require( '@stdlib/ndarray/to-array' );
@@ -30,9 +28,9 @@ var opts = {
 	'dtype': 'float32'
 };
 
-var x = new Float32Vector( discreteUniform( 3, 0, 10, opts ) );
-var y = new Float32Vector( discreteUniform( 3, 0, 10, opts ) );
-var A = new Float32Matrix( discreteUniform( 9, 0, 10, opts ).buffer, 0, [ 3, 3 ] );
+var x = discreteUniform( [ 3 ], 0, 10, opts );
+var y = discreteUniform( [ 3 ], 0, 10, opts );
+var A = discreteUniform( [ 3, 3 ], 0, 10, opts );
 
 var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
 	'dtype': 'int8'
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/main.js
index dbfee65b3777..497b54c369c4 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/main.js
@@ -25,7 +25,6 @@ var getStrides = require( '@stdlib/ndarray/base/strides' );
 var getStride = require( '@stdlib/ndarray/base/stride' );
 var getOffset = require( '@stdlib/ndarray/base/offset' );
 var getData = require( '@stdlib/ndarray/base/data-buffer' );
-var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' );
 var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' );
 var strided = require( '@stdlib/blas/base/ssyr2' ).ndarray;
 
@@ -82,7 +81,7 @@ function ssyr2( arrays ) {
 	y = arrays[ 1 ];
 	A = arrays[ 2 ];
 
-	uplo = resolveStr( ndarraylike2scalar( arrays[ 3 ] ) );
+	uplo = ndarraylike2scalar( arrays[ 3 ] );
 	alpha = ndarraylike2scalar( arrays[ 4 ] );
 
 	sh = getShape( A, false );