From b085e78140d7c0b265996ed170634ae55744657c Mon Sep 17 00:00:00 2001
From: kaustubh <kaustubh.mp007@gmail.com>
Date: Sat, 13 Jun 2026 00:19:59 +0530
Subject: [PATCH 1/4] feat: add blas/base/ndarray/dsyr

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---
 .../@stdlib/blas/base/ndarray/dsyr/README.md  | 127 +++++++++
 .../base/ndarray/dsyr/benchmark/benchmark.js  | 112 ++++++++
 .../blas/base/ndarray/dsyr/docs/repl.txt      |  36 +++
 .../base/ndarray/dsyr/docs/types/index.d.ts   |  63 +++++
 .../blas/base/ndarray/dsyr/docs/types/test.ts |  69 +++++
 .../blas/base/ndarray/dsyr/examples/index.js  |  39 +++
 .../blas/base/ndarray/dsyr/lib/index.js       |  54 ++++
 .../blas/base/ndarray/dsyr/lib/main.js        |  77 ++++++
 .../blas/base/ndarray/dsyr/package.json       |  73 +++++
 .../blas/base/ndarray/dsyr/test/test.js       | 260 ++++++++++++++++++
 10 files changed, 910 insertions(+)
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/dsyr/README.md
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/dsyr/benchmark/benchmark.js
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/repl.txt
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/index.d.ts
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/test.ts
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/dsyr/examples/index.js
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/index.js
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/dsyr/package.json
 create mode 100644 lib/node_modules/@stdlib/blas/base/ndarray/dsyr/test/test.js

diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/README.md
new file mode 100644
index 000000000000..21d4ea7fd2ea
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/README.md
@@ -0,0 +1,127 @@
+<!--
+
+@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.
+
+-->
+
+# dsyr
+
+> Perform the symmetric rank 1 operation `A = alpha*x*x^T + A`.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var dsyr = require( '@stdlib/blas/base/ndarray/dsyr' );
+```
+
+#### dsyr( arrays )
+
+Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is an `N` element ndarray, and `A` is an `N` by `N` symmetric matrix.
+
+```javascript
+var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] );
+var A = new ndarray( 'float64', new Float64Array( [ 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': 'float64'
+});
+
+var out = dsyr( [ x, A, alpha ] );
+// returns <ndarray>[ [ 3.0, 6.0, 9.0 ], [ 2.0, 9.0, 14.0 ], [ 3.0, 2.0, 19.0 ] ]
+
+var bool = ( out === A );
+// returns true
+```
+
+The function has the following parameters:
+
+-   **arrays**: array-like object containing the following ndarrays:
+
+    -   a 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 Float64Array = require( '@stdlib/array/float64' );
+var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var dsyr = require( '@stdlib/blas/base/ndarray/dsyr' );
+
+var opts = {
+    'dtype': 'float64'
+};
+
+var x = new Float64Vector( discreteUniform( 3, 0, 10, opts ) );
+var A = new ndarray( 'float64', new Float64Array( discreteUniform( 9, 0, 10, opts ) ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+var alpha = scalar2ndarray( 1.0, opts );
+
+var out = dsyr( [ x, 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/dsyr/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/benchmark/benchmark.js
new file mode 100644
index 000000000000..c9e64d514b56
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/benchmark/benchmark.js
@@ -0,0 +1,112 @@
+/**
+* @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 isnan = require( '@stdlib/math/base/assert/is-nan' );
+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 dsyr = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var alpha;
+	var x;
+	var A;
+
+	x = 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 = dsyr( [ x, A, alpha ] );
+			if ( typeof z !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		if ( isnan( 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/dsyr/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/repl.txt
new file mode 100644
index 000000000000..80839cac8ea6
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/repl.txt
@@ -0,0 +1,36 @@
+
+{{alias}}( arrays )
+    Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where
+    `alpha` is a scalar, `x` is an `N` element ndarray, and `A` is an
+    `N` by `N` symmetric matrix.
+
+    Parameters
+    ----------
+    arrays: ArrayLikeObject<ndarray>
+        Array-like object containing the following ndarrays:
+
+        - a 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/float64}}( [ 1.0, 2.0 ] );
+    > var buf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 2.0, 1.0 ] );
+    > var sh = [ 2, 2 ];
+    > var st = [ 2, 1 ];
+    > var A = new {{alias:@stdlib/ndarray/base/ctor}}( 'float64', buf, sh, st, 0, 'row-major' );
+    > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 2.0, { 'dtype': 'float64' });
+
+    > {{alias}}( [ x, A, alpha ] );
+    > A
+    <ndarray>[ [ 3.0, 6.0 ], [ 2.0, 9.0 ] ]
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/index.d.ts
new file mode 100644
index 000000000000..27444ede09d6
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/index.d.ts
@@ -0,0 +1,63 @@
+/*
+* @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 { float64ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is an `N` element ndarray, and `A` is an `N` by `N` symmetric matrix.
+*
+* ## Notes
+*
+* -   The function expects the following ndarrays:
+*
+*     -   a 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 Float64Vector = require( '@stdlib/ndarray/vector/float64' );
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] );
+* var A = new ndarray( 'float64', new Float64Array( [ 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': 'float64'
+* });
+*
+* var out = dsyr( [ x, A, alpha ] );
+* // returns <ndarray>[ [ 3.0, 6.0, 9.0 ], [ 2.0, 9.0, 14.0 ], [ 3.0, 2.0, 19.0 ] ]
+*
+* var bool = ( out === A );
+* // returns true
+*/
+declare function dsyr( arrays: [ float64ndarray, float64ndarray, float64ndarray ] ): float64ndarray;
+
+
+// EXPORTS //
+
+export = dsyr;
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/test.ts
new file mode 100644
index 000000000000..cdf38ba48ea1
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/test.ts
@@ -0,0 +1,69 @@
+/*
+* @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 dsyr = require( '@stdlib/blas/base/ndarray/dsyr' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+	const x = zeros( [ 3 ], {
+		'dtype': 'float64'
+	});
+	const A = zeros( [ 3, 3 ], {
+		'dtype': 'float64'
+	});
+	const alpha = zeros( [], {
+		'dtype': 'float64'
+	});
+
+	dsyr( [ x, A, alpha ] ); // $ExpectType float64ndarray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
+{
+	dsyr( '10' ); // $ExpectError
+	dsyr( 10 ); // $ExpectError
+	dsyr( true ); // $ExpectError
+	dsyr( false ); // $ExpectError
+	dsyr( null ); // $ExpectError
+	dsyr( undefined ); // $ExpectError
+	dsyr( [] ); // $ExpectError
+	dsyr( {} ); // $ExpectError
+	dsyr( ( 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': 'float64'
+	});
+	const A = zeros( [ 3, 3 ], {
+		'dtype': 'float64'
+	});
+	const alpha = zeros( [], {
+		'dtype': 'float64'
+	});
+
+	dsyr(); // $ExpectError
+	dsyr( [ x, A, alpha ], {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/examples/index.js
new file mode 100644
index 000000000000..bed1104fe0ac
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/examples/index.js
@@ -0,0 +1,39 @@
+/**
+* @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 Float64Array = require( '@stdlib/array/float64' );
+var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var dsyr = require( './../lib' );
+
+var opts = {
+	'dtype': 'float64'
+};
+
+var x = new Float64Vector( discreteUniform( 3, 0, 10, opts ) );
+var A = new ndarray( 'float64', new Float64Array( discreteUniform( 9, 0, 10, opts ) ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+var alpha = scalar2ndarray( 1.0, opts );
+
+var out = dsyr( [ x, A, alpha ] );
+console.log( ndarray2array( out ) );
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/index.js
new file mode 100644
index 000000000000..b624280cb5bf
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/index.js
@@ -0,0 +1,54 @@
+/**
+* @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 1 operation `A = alpha*x*x^T + A`.
+*
+* @module @stdlib/blas/base/ndarray/dsyr
+*
+* @example
+* var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var Float64Array = require( '@stdlib/array/float64' );
+* var dsyr = require( '@stdlib/blas/base/ndarray/dsyr' );
+*
+* var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] );
+* var A = new ndarray( 'float64', new Float64Array( [ 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': 'float64'
+* });
+*
+* var out = dsyr( [ x, A, alpha ] );
+* // returns <ndarray>[ [ 3.0, 6.0, 9.0 ], [ 2.0, 9.0, 14.0 ], [ 3.0, 2.0, 19.0 ] ]
+*
+* 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/dsyr/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js
new file mode 100644
index 000000000000..ba85e747d0fd
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js
@@ -0,0 +1,77 @@
+/**
+* @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/dsyr' ).ndarray;
+
+
+// MAIN //
+
+/**
+* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is an `N` element ndarray, and `A` is an `N` by `N` symmetric matrix.
+*
+* ## Notes
+*
+* -   The function expects the following ndarrays:
+*
+*     -   a 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 Float64Vector = require( '@stdlib/ndarray/vector/float64' );
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] );
+* var A = new ndarray( 'float64', new Float64Array( [ 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': 'float64'
+* });
+*
+* var out = dsyr( [ x, A, alpha ] );
+* // returns <ndarray>[ [ 3.0, 6.0, 9.0 ], [ 2.0, 9.0, 14.0 ], [ 3.0, 2.0, 19.0 ] ]
+*
+* var bool = ( out === A );
+* // returns true
+*/
+function dsyr( arrays ) {
+	var alpha = ndarraylike2scalar( arrays[ 2 ] );
+	var x = arrays[ 0 ];
+	var A = arrays[ 1 ];
+	strided( 'upper', numelDimension( A, 0 ), alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( A ), getStride( A, 0 ), getStride( A, 1 ), getOffset( A ) );
+	return A;
+}
+
+
+// EXPORTS //
+
+module.exports = dsyr;
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/package.json
new file mode 100644
index 000000000000..14159875174b
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/package.json
@@ -0,0 +1,73 @@
+{
+  "name": "@stdlib/blas/base/ndarray/dsyr",
+  "version": "0.0.0",
+  "description": "Perform the symmetric rank 1 operation `A = alpha*x*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",
+    "dsyr",
+    "linear",
+    "algebra",
+    "subroutines",
+    "symmetric",
+    "rank-1",
+    "update",
+    "vector",
+    "matrix",
+    "array",
+    "ndarray",
+    "float64",
+    "double",
+    "float64array"
+  ]
+}
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/test/test.js
new file mode 100644
index 000000000000..d77389c468d1
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/test/test.js
@@ -0,0 +1,260 @@
+/**
+* @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 isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' );
+var Float64Array = require( '@stdlib/array/float64' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var getData = require( '@stdlib/ndarray/data-buffer' );
+var dsyr = 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( 'float64', 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( 'float64', 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 dsyr, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function has an arity of 1', function test( t ) {
+	t.strictEqual( dsyr.length, 1, 'has expected arity' );
+	t.end();
+});
+
+tape( 'the function performs the symmetric rank 1 operation `A = alpha*x*x^T + A`', function test( t ) {
+	var expected;
+	var alpha;
+	var xbuf;
+	var Abuf;
+	var x;
+	var A;
+	var v;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0 ] );
+	Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] );
+	x = vector( xbuf, 3, 1, 0 );
+	A = matrix( Abuf, 3, 3, 1, 0 );
+	alpha = scalar2ndarray( 2.0, {
+		'dtype': 'float64'
+	});
+
+	v = dsyr( [ x, A, alpha ] );
+
+	expected = new Float64Array( [ 3.0, 6.0, 9.0, 2.0, 9.0, 14.0, 3.0, 2.0, 19.0 ] );
+	t.strictEqual( v, A, 'returns expected value' );
+	t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' );
+
+	xbuf = new Float64Array( [ 1.0, 1.0, 1.0 ] );
+	Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] );
+	x = vector( xbuf, 3, 1, 0 );
+	A = matrix( Abuf, 3, 1, 3, 0 );
+	alpha = scalar2ndarray( 2.0, {
+		'dtype': 'float64'
+	});
+
+	v = dsyr( [ x, A, alpha ] );
+
+	expected = new Float64Array( [ 3.0, 2.0, 3.0, 4.0, 3.0, 2.0, 5.0, 4.0, 3.0 ] );
+	t.strictEqual( v, A, 'returns expected value' );
+	t.strictEqual( isSameFloat64Array( 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 Abuf;
+	var x;
+	var A;
+	var v;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0 ] );
+	Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] );
+	x = vector( xbuf, 3, 1, 0 );
+	A = matrix( Abuf, 3, 3, 1, 0 );
+	alpha = scalar2ndarray( 0.0, {
+		'dtype': 'float64'
+	});
+
+	v = dsyr( [ x, A, alpha ] );
+
+	expected = new Float64Array( [ 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( isSameFloat64Array( 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 Abuf;
+	var x;
+	var A;
+	var v;
+
+	xbuf = new Float64Array([
+		1.0, // 0
+		0.0,
+		2.0, // 1
+		0.0,
+		3.0  // 2
+	]);
+	x = vector( xbuf, 3, 2, 0 );
+
+	Abuf = new Float64Array( [ 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': 'float64'
+	});
+
+	v = dsyr( [ x, A, alpha ] );
+
+	expected = new Float64Array( [ 2.0, 4.0, 6.0, 0.0, 8.0, 12.0, 0.0, 0.0, 18.0 ] );
+	t.strictEqual( v, A, 'returns expected value' );
+	t.strictEqual( isSameFloat64Array( 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 Abuf;
+	var x;
+	var A;
+	var v;
+
+	xbuf = new Float64Array([
+		3.0, // 2
+		2.0, // 1
+		1.0  // 0
+	]);
+	x = vector( xbuf, 3, -1, 2 );
+
+	Abuf = new Float64Array( [ 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': 'float64'
+	});
+
+	v = dsyr( [ x, A, alpha ] );
+
+	expected = new Float64Array( [ 2.0, 4.0, 6.0, 0.0, 8.0, 12.0, 0.0, 0.0, 18.0 ] );
+	t.strictEqual( v, A, 'returns expected value' );
+	t.strictEqual( isSameFloat64Array( 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 Abuf;
+	var x;
+	var A;
+	var v;
+
+	xbuf = new Float64Array([
+		0.0,
+		1.0, // 0
+		0.0,
+		2.0, // 1
+		0.0,
+		3.0  // 2
+	]);
+	x = vector( xbuf, 3, 2, 1 );
+
+	Abuf = new Float64Array([
+		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': 'float64'
+	});
+
+	v = dsyr( [ x, A, alpha ] );
+
+	expected = new Float64Array([
+		999.0,
+		999.0,
+		2.0,
+		4.0,
+		6.0,
+		0.0,
+		8.0,
+		12.0,
+		0.0,
+		0.0,
+		18.0
+	]);
+	t.strictEqual( v, A, 'returns expected value' );
+	t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' );
+	t.end();
+});

From 6edabcebe0c2d122503adde1ee6a13335416e525 Mon Sep 17 00:00:00 2001
From: kaustubh <kaustubh.mp007@gmail.com>
Date: Fri, 10 Jul 2026 11:07:12 +0530
Subject: [PATCH 2/4] feat: add Float64Matrix 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: na
  - 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
  - task: lint_r
    status: na
  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: passed
  - task: lint_typescript_tests
    status: passed
  - task: lint_license_headers
    status: passed
---
---
 .../@stdlib/blas/base/ndarray/dsyr/README.md  |  39 ++++--
 .../base/ndarray/dsyr/benchmark/benchmark.js  |   7 +-
 .../blas/base/ndarray/dsyr/docs/repl.txt      |  33 +++--
 .../base/ndarray/dsyr/docs/types/index.d.ts   |  30 ++--
 .../blas/base/ndarray/dsyr/docs/types/test.ts |  10 +-
 .../blas/base/ndarray/dsyr/examples/index.js  |  11 +-
 .../blas/base/ndarray/dsyr/lib/index.js       |  17 ++-
 .../blas/base/ndarray/dsyr/lib/main.js        |  52 ++++---
 .../blas/base/ndarray/dsyr/test/test.js       | 131 +++++++++++++-----
 9 files changed, 224 insertions(+), 106 deletions(-)

diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/README.md
index 21d4ea7fd2ea..75a145b26a1d 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/README.md
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/README.md
@@ -38,25 +38,29 @@ var dsyr = require( '@stdlib/blas/base/ndarray/dsyr' );
 
 #### dsyr( arrays )
 
-Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is an `N` element ndarray, and `A` is an `N` by `N` symmetric matrix.
+Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix.
 
 ```javascript
+/* eslint-disable max-len */
+var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' );
 var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
 var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
-var ndarray = require( '@stdlib/ndarray/base/ctor' );
-var Float64Array = require( '@stdlib/array/float64' );
+var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
 
 var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] );
-var A = new ndarray( 'float64', new Float64Array( [ 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 Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] );
 
-var alpha = scalar2ndarray( 2.0, {
+var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+    'dtype': 'int8'
+});
+var alpha = scalar2ndarray( 1.0, {
     'dtype': 'float64'
 });
 
-var out = dsyr( [ x, A, alpha ] );
-// returns <ndarray>[ [ 3.0, 6.0, 9.0 ], [ 2.0, 9.0, 14.0 ], [ 3.0, 2.0, 19.0 ] ]
+var y = dsyr( [ x, A, uplo, alpha ] );
+// returns <ndarray>[ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ]
 
-var bool = ( out === A );
+var bool = ( y === A );
 // returns true
 ```
 
@@ -64,9 +68,10 @@ The function has the following parameters:
 
 -   **arrays**: array-like object containing the following ndarrays:
 
-    -   a 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 two-dimensional input/output ndarray corresponding to `A`.
+    -   a zero-dimensional ndarray specifying whether the upper or lower triangular part of `A` should be referenced.
+    -   a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`.
 
 </section>
 
@@ -85,11 +90,12 @@ 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 Float64Array = require( '@stdlib/array/float64' );
+var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' );
 var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
 var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
 var ndarray2array = require( '@stdlib/ndarray/to-array' );
 var dsyr = require( '@stdlib/blas/base/ndarray/dsyr' );
 
@@ -98,11 +104,14 @@ var opts = {
 };
 
 var x = new Float64Vector( discreteUniform( 3, 0, 10, opts ) );
-var A = new ndarray( 'float64', new Float64Array( discreteUniform( 9, 0, 10, opts ) ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
+var A = new Float64Matrix( discreteUniform( 9, 0, 10, opts ).buffer, 0, [ 3, 3 ] );
 
+var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+    'dtype': 'int8'
+});
 var alpha = scalar2ndarray( 1.0, opts );
 
-var out = dsyr( [ x, A, alpha ] );
+var out = dsyr( [ x, A, uplo, alpha ] );
 console.log( ndarray2array( out ) );
 ```
 
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/benchmark/benchmark.js
index c9e64d514b56..d23f6ac32f59 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/benchmark/benchmark.js
@@ -25,6 +25,7 @@ var uniform = require( '@stdlib/random/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 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 dsyr = require( './../lib' );
@@ -48,6 +49,7 @@ var options = {
 */
 function createBenchmark( len ) {
 	var alpha;
+	var uplo;
 	var x;
 	var A;
 
@@ -55,6 +57,9 @@ 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;
 
@@ -70,7 +75,7 @@ function createBenchmark( len ) {
 
 		b.tic();
 		for ( i = 0; i < b.iterations; i++ ) {
-			z = dsyr( [ x, A, alpha ] );
+			z = dsyr( [ x, A, uplo, alpha ] );
 			if ( typeof z !== 'object' ) {
 				b.fail( 'should return an ndarray' );
 			}
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/repl.txt
index 80839cac8ea6..508f50c28739 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/repl.txt
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/repl.txt
@@ -1,7 +1,7 @@
 
 {{alias}}( arrays )
     Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where
-    `alpha` is a scalar, `x` is an `N` element ndarray, and `A` is an
+    `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an
     `N` by `N` symmetric matrix.
 
     Parameters
@@ -9,9 +9,12 @@
     arrays: ArrayLikeObject<ndarray>
         Array-like object containing the following ndarrays:
 
-        - a 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 two-dimensional input/output ndarray corresponding to `A`.
+        - a zero-dimensional ndarray specifying whether the upper or lower
+        triangular part of `A` should be referenced.
+        - a zero-dimensional ndarray containing a scalar constant corresponding
+        to `alpha`.
 
     Returns
     -------
@@ -20,16 +23,20 @@
 
     Examples
     --------
-    > var x = new {{alias:@stdlib/ndarray/vector/float64}}( [ 1.0, 2.0 ] );
-    > var buf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 2.0, 1.0 ] );
-    > var sh = [ 2, 2 ];
-    > var st = [ 2, 1 ];
-    > var A = new {{alias:@stdlib/ndarray/base/ctor}}( 'float64', buf, sh, st, 0, 'row-major' );
-    > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 2.0, { 'dtype': 'float64' });
-
-    > {{alias}}( [ x, A, alpha ] );
+    > var xbuf = [ 1.0, 2.0, 3.0 ];
+    > var x = new {{alias:@stdlib/ndarray/vector/float64}}( xbuf );
+
+    > 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/float64}}( abuf );
+
+    > var opts = { 'dtype': 'float64' };
+    > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts );
+
+    > var uplo = {{alias:@stdlib/ndarray/from-scalar}}( 'upper' );
+
+    > {{alias}}( [ x, A, uplo, alpha ] );
     > A
-    <ndarray>[ [ 3.0, 6.0 ], [ 2.0, 9.0 ] ]
+    <ndarray>[ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ]
 
     See Also
     --------
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/index.d.ts
index 27444ede09d6..704e3e5fd12b 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/index.d.ts
@@ -20,42 +20,46 @@
 
 /// <reference types="@stdlib/types"/>
 
-import { float64ndarray } from '@stdlib/types/ndarray';
+import { float64ndarray, ndarray } from '@stdlib/types/ndarray';
 
 /**
-* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is an `N` element ndarray, and `A` is an `N` by `N` symmetric matrix.
+* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix.
 *
 * ## Notes
 *
 * -   The function expects the following ndarrays:
 *
-*     -   a 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 two-dimensional input/output ndarray corresponding to `A`.
+*     -   a zero-dimensional ndarray specifying whether the upper or lower triangular part of `A` should be referenced.
+*     -   a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`.
 *
 * @param arrays - array-like object containing ndarrays
 * @returns output ndarray
 *
 * @example
+* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' );
 * var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
 * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
-* var ndarray = require( '@stdlib/ndarray/base/ctor' );
-* var Float64Array = require( '@stdlib/array/float64' );
+* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
 *
 * var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] );
-* var A = new ndarray( 'float64', new Float64Array( [ 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 Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] );
 *
-* var alpha = scalar2ndarray( 2.0, {
+* var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+*     'dtype': 'int8'
+* });
+* var alpha = scalar2ndarray( 1.0, {
 *     'dtype': 'float64'
 * });
 *
-* var out = dsyr( [ x, A, alpha ] );
-* // returns <ndarray>[ [ 3.0, 6.0, 9.0 ], [ 2.0, 9.0, 14.0 ], [ 3.0, 2.0, 19.0 ] ]
+* var y = dsyr( [ x, A, uplo, alpha ] );
+* // returns <ndarray>[ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ]
 *
-* var bool = ( out === A );
+* var bool = ( y === A );
 * // returns true
 */
-declare function dsyr( arrays: [ float64ndarray, float64ndarray, float64ndarray ] ): float64ndarray;
+declare function dsyr( arrays: [ float64ndarray, float64ndarray, ndarray, float64ndarray ] ): float64ndarray;
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/test.ts
index cdf38ba48ea1..80de4ebc4612 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/test.ts
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/test.ts
@@ -32,11 +32,14 @@ import dsyr = require( '@stdlib/blas/base/ndarray/dsyr' );
 	const A = zeros( [ 3, 3 ], {
 		'dtype': 'float64'
 	});
+	const uplo = zeros( [], {
+		'dtype': 'int8'
+	});
 	const alpha = zeros( [], {
 		'dtype': 'float64'
 	});
 
-	dsyr( [ x, A, alpha ] ); // $ExpectType float64ndarray
+	dsyr( [ x, A, uplo, alpha ] ); // $ExpectType float64ndarray
 }
 
 // The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
@@ -60,10 +63,13 @@ import dsyr = require( '@stdlib/blas/base/ndarray/dsyr' );
 	const A = zeros( [ 3, 3 ], {
 		'dtype': 'float64'
 	});
+	const uplo = zeros( [], {
+		'dtype': 'int8'
+	});
 	const alpha = zeros( [], {
 		'dtype': 'float64'
 	});
 
 	dsyr(); // $ExpectError
-	dsyr( [ x, A, alpha ], {} ); // $ExpectError
+	dsyr( [ x, A, uplo, alpha ], {} ); // $ExpectError
 }
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/examples/index.js
index bed1104fe0ac..4b240dbb57a7 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/examples/index.js
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/examples/index.js
@@ -19,10 +19,10 @@
 'use strict';
 
 var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
-var ndarray = require( '@stdlib/ndarray/base/ctor' );
-var Float64Array = require( '@stdlib/array/float64' );
+var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' );
 var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
 var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
 var ndarray2array = require( '@stdlib/ndarray/to-array' );
 var dsyr = require( './../lib' );
 
@@ -31,9 +31,12 @@ var opts = {
 };
 
 var x = new Float64Vector( discreteUniform( 3, 0, 10, opts ) );
-var A = new ndarray( 'float64', new Float64Array( discreteUniform( 9, 0, 10, opts ) ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
+var A = new Float64Matrix( discreteUniform( 9, 0, 10, opts ).buffer, 0, [ 3, 3 ] );
 
+var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+	'dtype': 'int8'
+});
 var alpha = scalar2ndarray( 1.0, opts );
 
-var out = dsyr( [ x, A, alpha ] );
+var out = dsyr( [ x, A, uplo, alpha ] );
 console.log( ndarray2array( out ) );
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/index.js
index b624280cb5bf..c91fee16e1cd 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/index.js
@@ -24,23 +24,26 @@
 * @module @stdlib/blas/base/ndarray/dsyr
 *
 * @example
+* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' );
 * var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
 * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
-* var ndarray = require( '@stdlib/ndarray/base/ctor' );
-* var Float64Array = require( '@stdlib/array/float64' );
+* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
 * var dsyr = require( '@stdlib/blas/base/ndarray/dsyr' );
 *
 * var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] );
-* var A = new ndarray( 'float64', new Float64Array( [ 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 Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] );
 *
-* var alpha = scalar2ndarray( 2.0, {
+* var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+*     'dtype': 'int8'
+* });
+* var alpha = scalar2ndarray( 1.0, {
 *     'dtype': 'float64'
 * });
 *
-* var out = dsyr( [ x, A, alpha ] );
-* // returns <ndarray>[ [ 3.0, 6.0, 9.0 ], [ 2.0, 9.0, 14.0 ], [ 3.0, 2.0, 19.0 ] ]
+* var y = dsyr( [ x, A, uplo, alpha ] );
+* // returns <ndarray>[ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ]
 *
-* var bool = ( out === A );
+* var bool = ( y === A );
 * // returns true
 */
 
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js
index ba85e747d0fd..75da3afb7ac8 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js
@@ -20,54 +20,74 @@
 
 // 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 ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' );
+var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' );
 var strided = require( '@stdlib/blas/base/dsyr' ).ndarray;
 
 
 // MAIN //
 
 /**
-* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is an `N` element ndarray, and `A` is an `N` by `N` symmetric matrix.
+* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix.
 *
 * ## Notes
 *
 * -   The function expects the following ndarrays:
 *
-*     -   a 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 two-dimensional input/output ndarray corresponding to `A`.
+*     -   a zero-dimensional ndarray specifying whether the upper or lower triangular part of `A` should be referenced.
+*     -   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 Float64Matrix = require( '@stdlib/ndarray/matrix/float64' );
 * var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
 * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
-* var ndarray = require( '@stdlib/ndarray/base/ctor' );
-* var Float64Array = require( '@stdlib/array/float64' );
+* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' );
 *
 * var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] );
-* var A = new ndarray( 'float64', new Float64Array( [ 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 Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] );
 *
-* var alpha = scalar2ndarray( 2.0, {
+* var uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+*     'dtype': 'int8'
+* });
+* var alpha = scalar2ndarray( 1.0, {
 *     'dtype': 'float64'
 * });
 *
-* var out = dsyr( [ x, A, alpha ] );
-* // returns <ndarray>[ [ 3.0, 6.0, 9.0 ], [ 2.0, 9.0, 14.0 ], [ 3.0, 2.0, 19.0 ] ]
+* var y = dsyr( [ x, A, uplo, alpha ] );
+* // returns <ndarray>[ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ]
 *
-* var bool = ( out === A );
+* var bool = ( y === A );
 * // returns true
 */
 function dsyr( arrays ) {
-	var alpha = ndarraylike2scalar( arrays[ 2 ] );
-	var x = arrays[ 0 ];
-	var A = arrays[ 1 ];
-	strided( 'upper', numelDimension( A, 0 ), alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( A ), getStride( A, 0 ), getStride( A, 1 ), getOffset( A ) );
+	var alpha;
+	var uplo;
+	var sh;
+	var st;
+	var x;
+	var A;
+
+	x = arrays[ 0 ];
+	A = arrays[ 1 ];
+
+	uplo = resolveStr( ndarraylike2scalar( arrays[ 2 ] ) );
+	alpha = ndarraylike2scalar( arrays[ 3 ] );
+
+	sh = getShape( A, false );
+	st = getStrides( A, false );
+
+	strided( uplo, sh[ 0 ], alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( A ), st[ 0 ], st[ 1 ], getOffset( A ) );
+
 	return A;
 }
 
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/test/test.js
index d77389c468d1..7c2a088ce89f 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/test/test.js
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/test/test.js
@@ -24,6 +24,7 @@ var tape = require( 'tape' );
 var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' );
 var Float64Array = require( '@stdlib/array/float64' );
 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 dsyr = require( './../lib' );
@@ -74,11 +75,12 @@ tape( 'the function has an arity of 1', function test( t ) {
 	t.end();
 });
 
-tape( 'the function performs the symmetric rank 1 operation `A = alpha*x*x^T + A`', function test( t ) {
+tape( 'the function performs the symmetric rank 1 operation `A = alpha*x*x^T + A` (upper)', function test( t ) {
 	var expected;
 	var alpha;
 	var xbuf;
 	var Abuf;
+	var uplo;
 	var x;
 	var A;
 	var v;
@@ -87,13 +89,17 @@ tape( 'the function performs the symmetric rank 1 operation `A = alpha*x*x^T + A
 	Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] );
 	x = vector( xbuf, 3, 1, 0 );
 	A = matrix( Abuf, 3, 3, 1, 0 );
-	alpha = scalar2ndarray( 2.0, {
+	alpha = scalar2ndarray( 1.0, {
 		'dtype': 'float64'
 	});
 
-	v = dsyr( [ x, A, alpha ] );
+	uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+		'dtype': 'int8'
+	});
+
+	v = dsyr( [ x, A, uplo, alpha ] );
 
-	expected = new Float64Array( [ 3.0, 6.0, 9.0, 2.0, 9.0, 14.0, 3.0, 2.0, 19.0 ] );
+	expected = new Float64Array( [ 2.0, 4.0, 6.0, 2.0, 5.0, 8.0, 3.0, 2.0, 10.0 ] );
 	t.strictEqual( v, A, 'returns expected value' );
 	t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' );
 
@@ -101,13 +107,48 @@ tape( 'the function performs the symmetric rank 1 operation `A = alpha*x*x^T + A
 	Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] );
 	x = vector( xbuf, 3, 1, 0 );
 	A = matrix( Abuf, 3, 1, 3, 0 );
-	alpha = scalar2ndarray( 2.0, {
+	alpha = scalar2ndarray( 1.0, {
 		'dtype': 'float64'
 	});
 
-	v = dsyr( [ x, A, alpha ] );
+	uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+		'dtype': 'int8'
+	});
+
+	v = dsyr( [ x, A, uplo, alpha ] );
+
+	expected = new Float64Array( [ 2.0, 2.0, 3.0, 3.0, 2.0, 2.0, 4.0, 3.0, 2.0 ] );
+	t.strictEqual( v, A, 'returns expected value' );
+	t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function performs the symmetric rank 1 operation `A = alpha*x*x^T + A` (lower)', function test( t ) {
+	var expected;
+	var alpha;
+	var xbuf;
+	var Abuf;
+	var uplo;
+	var x;
+	var A;
+	var v;
+
+	xbuf = new Float64Array( [ 1.0, 2.0, 3.0 ] );
+	Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] );
+	x = vector( xbuf, 3, 1, 0 );
+	A = matrix( Abuf, 3, 3, 1, 0 );
+	alpha = scalar2ndarray( 1.0, {
+		'dtype': 'float64'
+	});
+
+	uplo = scalar2ndarray( resolveEnum( 'lower' ), {
+		'dtype': 'int8'
+	});
+
+	v = dsyr( [ x, A, uplo, alpha ] );
 
-	expected = new Float64Array( [ 3.0, 2.0, 3.0, 4.0, 3.0, 2.0, 5.0, 4.0, 3.0 ] );
+	expected = new Float64Array( [ 2.0, 2.0, 3.0, 4.0, 5.0, 2.0, 6.0, 8.0, 10.0 ] );
 	t.strictEqual( v, A, 'returns expected value' );
 	t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' );
 
@@ -119,6 +160,7 @@ tape( 'if `alpha` is `0`, the function returns `A` unchanged', function test( t
 	var alpha;
 	var xbuf;
 	var Abuf;
+	var uplo;
 	var x;
 	var A;
 	var v;
@@ -131,7 +173,11 @@ tape( 'if `alpha` is `0`, the function returns `A` unchanged', function test( t
 		'dtype': 'float64'
 	});
 
-	v = dsyr( [ x, A, alpha ] );
+	uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+		'dtype': 'int8'
+	});
+
+	v = dsyr( [ x, A, uplo, alpha ] );
 
 	expected = new Float64Array( [ 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' );
@@ -145,6 +191,7 @@ tape( 'the function supports ndarrays having non-unit strides', function test( t
 	var alpha;
 	var xbuf;
 	var Abuf;
+	var uplo;
 	var x;
 	var A;
 	var v;
@@ -160,13 +207,17 @@ tape( 'the function supports ndarrays having non-unit strides', function test( t
 
 	Abuf = new Float64Array( [ 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, {
+	alpha = scalar2ndarray( 1.0, {
 		'dtype': 'float64'
 	});
 
-	v = dsyr( [ x, A, alpha ] );
+	uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+		'dtype': 'int8'
+	});
+
+	v = dsyr( [ x, A, uplo, alpha ] );
 
-	expected = new Float64Array( [ 2.0, 4.0, 6.0, 0.0, 8.0, 12.0, 0.0, 0.0, 18.0 ] );
+	expected = new Float64Array( [ 1.0, 2.0, 3.0, 0.0, 4.0, 6.0, 0.0, 0.0, 9.0 ] );
 	t.strictEqual( v, A, 'returns expected value' );
 	t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' );
 	t.end();
@@ -177,6 +228,7 @@ tape( 'the function supports ndarrays having negative strides', function test( t
 	var alpha;
 	var xbuf;
 	var Abuf;
+	var uplo;
 	var x;
 	var A;
 	var v;
@@ -190,13 +242,17 @@ tape( 'the function supports ndarrays having negative strides', function test( t
 
 	Abuf = new Float64Array( [ 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, {
+	alpha = scalar2ndarray( 1.0, {
 		'dtype': 'float64'
 	});
 
-	v = dsyr( [ x, A, alpha ] );
+	uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+		'dtype': 'int8'
+	});
 
-	expected = new Float64Array( [ 2.0, 4.0, 6.0, 0.0, 8.0, 12.0, 0.0, 0.0, 18.0 ] );
+	v = dsyr( [ x, A, uplo, alpha ] );
+
+	expected = new Float64Array( [ 1.0, 2.0, 3.0, 0.0, 4.0, 6.0, 0.0, 0.0, 9.0 ] );
 	t.strictEqual( v, A, 'returns expected value' );
 	t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' );
 	t.end();
@@ -207,6 +263,7 @@ tape( 'the function supports ndarrays having non-zero offsets', function test( t
 	var alpha;
 	var xbuf;
 	var Abuf;
+	var uplo;
 	var x;
 	var A;
 	var v;
@@ -222,37 +279,41 @@ tape( 'the function supports ndarrays having non-zero offsets', function test( t
 	x = vector( xbuf, 3, 2, 1 );
 
 	Abuf = new Float64Array([
-		999.0,
-		999.0,
-		0.0,
-		0.0,
-		0.0,
-		0.0,
-		0.0,
-		0.0,
-		0.0,
-		0.0,
-		0.0
+		1.0,
+		2.0,
+		3.0,
+		4.0,
+		5.0,
+		6.0,
+		7.0,
+		8.0,
+		9.0,
+		10.0,
+		11.0
 	]);
 	A = matrix( Abuf, 3, 3, 1, 2 );
 	alpha = scalar2ndarray( 2.0, {
 		'dtype': 'float64'
 	});
 
-	v = dsyr( [ x, A, alpha ] );
+	uplo = scalar2ndarray( resolveEnum( 'upper' ), {
+		'dtype': 'int8'
+	});
+
+	v = dsyr( [ x, A, uplo, alpha ] );
 
 	expected = new Float64Array([
-		999.0,
-		999.0,
+		1.0,
 		2.0,
-		4.0,
-		6.0,
-		0.0,
+		5.0,
 		8.0,
-		12.0,
-		0.0,
-		0.0,
-		18.0
+		11.0,
+		6.0,
+		15.0,
+		20.0,
+		9.0,
+		10.0,
+		29.0
 	]);
 	t.strictEqual( v, A, 'returns expected value' );
 	t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' );

From 5bd3ef4042419dd050da07a578f82a47bdad129e Mon Sep 17 00:00:00 2001
From: Kaustubh Patange <kaustubh.mp007@gmail.com>
Date: Fri, 10 Jul 2026 11:20:13 +0530
Subject: [PATCH 3/4] Update
 lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js

Signed-off-by: Kaustubh Patange <kaustubh.mp007@gmail.com>
---
 lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js
index 75da3afb7ac8..9f4d7145abbc 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js
@@ -80,7 +80,7 @@ function dsyr( arrays ) {
 	x = arrays[ 0 ];
 	A = arrays[ 1 ];
 
-	uplo = resolveStr( ndarraylike2scalar( arrays[ 2 ] ) );
+	uplo = ndarraylike2scalar( arrays[ 2 ] );
 	alpha = ndarraylike2scalar( arrays[ 3 ] );
 
 	sh = getShape( A, false );

From 770def1490ef266d2fdf87228859e3eabe693c7f Mon Sep 17 00:00:00 2001
From: Kaustubh Patange <kaustubh.mp007@gmail.com>
Date: Fri, 10 Jul 2026 11:38:14 +0530
Subject: [PATCH 4/4] Apply suggestion from @MeKaustubh07

Signed-off-by: Kaustubh Patange <kaustubh.mp007@gmail.com>
---
 lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js | 1 -
 1 file changed, 1 deletion(-)

diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js
index 9f4d7145abbc..126c4b634a83 100644
--- a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js
@@ -26,7 +26,6 @@ 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 resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' );
 var strided = require( '@stdlib/blas/base/dsyr' ).ndarray;