diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/README.md
new file mode 100644
index 000000000000..58604a52da26
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/README.md
@@ -0,0 +1,128 @@
+
+
+# gsyr
+
+> Perform the symmetric rank 1 operation `A = alpha*x*x^T + A`.
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var gsyr = require( '@stdlib/blas/base/ndarray/gsyr' );
+```
+
+#### gsyr( 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 vector = require( '@stdlib/ndarray/vector/ctor' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+
+var x = vector( [ 1.0, 2.0, 3.0 ], 'generic' );
+var A = new ndarray( 'generic', [ 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': 'generic'
+});
+
+var out = gsyr( [ x, A, alpha ] );
+// returns [ [ 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 ndarray.
+ - a zero-dimensional ndarray containing a scalar constant.
+
+
+
+
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var vector = require( '@stdlib/ndarray/vector/ctor' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var gsyr = require( '@stdlib/blas/base/ndarray/gsyr' );
+
+var opts = {
+ 'dtype': 'generic'
+};
+
+var x = vector( discreteUniform( 3, 0, 10, opts ), 'generic' );
+console.log( ndarray2array( x ) );
+
+var A = new ndarray( 'generic', discreteUniform( 9, 0, 10, opts ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
+console.log( ndarray2array( A ) );
+
+var alpha = scalar2ndarray( 1.0, opts );
+
+var out = gsyr( [ x, A, alpha ] );
+console.log( ndarray2array( out ) );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/benchmark/benchmark.js
new file mode 100644
index 000000000000..3b5bd108f753
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/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 gsyr = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'generic'
+};
+
+
+// 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 = gsyr( [ 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/gsyr/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/docs/repl.txt
new file mode 100644
index 000000000000..b0d761d4cf3b
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/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
+ Array-like object containing the following ndarrays:
+
+ - a one-dimensional input ndarray.
+ - a two-dimensional input ndarray.
+ - a zero-dimensional ndarray containing a scalar constant.
+
+ Returns
+ -------
+ out: ndarray
+ Output ndarray.
+
+ Examples
+ --------
+ > var x = {{alias:@stdlib/ndarray/vector/ctor}}( [ 1.0, 2.0 ], 'generic' );
+ > var buf = [ 1.0, 2.0, 2.0, 1.0 ];
+ > var sh = [ 2, 2 ];
+ > var st = [ 2, 1 ];
+ > var A = new {{alias:@stdlib/ndarray/base/ctor}}( 'generic', buf, sh, st, 0, 'row-major' );
+ > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 2.0, { 'dtype': 'generic' });
+
+ > {{alias}}( [ x, A, alpha ] );
+ > A
+ [ [ 3.0, 6.0 ], [ 2.0, 9.0 ] ]
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/docs/types/index.d.ts
new file mode 100644
index 000000000000..1e6fb5051772
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/docs/types/index.d.ts
@@ -0,0 +1,62 @@
+/*
+* @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
+
+///
+
+import { typedndarray } 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 ndarray.
+* - a zero-dimensional ndarray containing a scalar constant.
+*
+* @param arrays - array-like object containing ndarrays
+* @returns output ndarray
+*
+* @example
+* var vector = require( '@stdlib/ndarray/vector/ctor' );
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var x = vector( [ 1.0, 2.0, 3.0 ], 'generic' );
+* var A = new ndarray( 'generic', [ 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': 'generic'
+* });
+*
+* var out = gsyr( [ x, A, alpha ] );
+* // returns [ [ 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 gsyr = typedndarray, U extends typedndarray = typedndarray>( arrays: [ T, U, typedndarray ] ): U;
+
+
+// EXPORTS //
+
+export = gsyr;
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/docs/types/test.ts
new file mode 100644
index 000000000000..67364c589f54
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/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 gsyr = require( '@stdlib/blas/base/ndarray/gsyr' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+ const x = zeros( [ 3 ], {
+ 'dtype': 'generic'
+ });
+ const A = zeros( [ 3, 3 ], {
+ 'dtype': 'generic'
+ });
+ const alpha = zeros( [], {
+ 'dtype': 'generic'
+ });
+
+ gsyr( [ x, A, alpha ] ); // $ExpectType genericndarray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
+{
+ gsyr( '10' ); // $ExpectError
+ gsyr( 10 ); // $ExpectError
+ gsyr( true ); // $ExpectError
+ gsyr( false ); // $ExpectError
+ gsyr( null ); // $ExpectError
+ gsyr( undefined ); // $ExpectError
+ gsyr( [] ); // $ExpectError
+ gsyr( {} ); // $ExpectError
+ gsyr( ( 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': 'generic'
+ });
+ const A = zeros( [ 3, 3 ], {
+ 'dtype': 'generic'
+ });
+ const alpha = zeros( [], {
+ 'dtype': 'generic'
+ });
+
+ gsyr(); // $ExpectError
+ gsyr( [ x, A, alpha ], {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/examples/index.js
new file mode 100644
index 000000000000..3ea924d84f8c
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/examples/index.js
@@ -0,0 +1,41 @@
+/**
+* @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 vector = require( '@stdlib/ndarray/vector/ctor' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var gsyr = require( './../lib' );
+
+var opts = {
+ 'dtype': 'generic'
+};
+
+var x = vector( discreteUniform( 3, 0, 10, opts ), 'generic' );
+console.log( ndarray2array( x ) );
+
+var A = new ndarray( 'generic', discreteUniform( 9, 0, 10, opts ), [ 3, 3 ], [ 3, 1 ], 0, 'row-major' );
+console.log( ndarray2array( A ) );
+
+var alpha = scalar2ndarray( 1.0, opts );
+
+var out = gsyr( [ x, A, alpha ] );
+console.log( ndarray2array( out ) );
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/lib/index.js
new file mode 100644
index 000000000000..4a2fe6a77f14
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/lib/index.js
@@ -0,0 +1,53 @@
+/**
+* @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/gsyr
+*
+* @example
+* var vector = require( '@stdlib/ndarray/vector/ctor' );
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var gsyr = require( '@stdlib/blas/base/ndarray/gsyr' );
+*
+* var x = vector( [ 1.0, 2.0, 3.0 ], 'generic' );
+* var A = new ndarray( 'generic', [ 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': 'generic'
+* });
+*
+* var out = gsyr( [ x, A, alpha ] );
+* // returns [ [ 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/gsyr/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/lib/main.js
new file mode 100644
index 000000000000..fe62254cc8d2
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/lib/main.js
@@ -0,0 +1,76 @@
+/**
+* @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/gsyr' ).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 ndarray.
+* - a zero-dimensional ndarray containing a scalar constant.
+*
+* @param {ArrayLikeObject