chore: changes as per code review

---
type: pre_push_report
description: Results of running various checks prior to pushing changes.
report:
  - task: run_javascript_examples
    status: na
  - task: run_c_examples
    status: na
  - task: run_cpp_examples
    status: na
  - task: run_javascript_readme_examples
    status: failed
---

Author: 0PrashantYadav0

lib/node_modules/@stdlib/blas/ext/base/wasm/dnansum/README.md

@@ -232,7 +232,7 @@ The function has the following additional parameters:
 ## Notes
 
 -   If `N <= 0`, both `main` and `ndarray` methods return `0.0`.
--   This package implements routines using WebAssembly. When provided arrays which are not allocated on a `dnansum` module memory instance, data must be explicitly copied to module memory prior to computation. Data movement may entail a performance cost, and, thus, if you are using arrays external to module memory, you should prefer using [`@stdlib/blas/base/dnansum`][@stdlib/blas/ext/base/dnansum]. However, if working with arrays which are allocated and explicitly managed on module memory, you can achieve better performance when compared to the pure JavaScript implementations found in [`@stdlib/blas/base/dnansum`][@stdlib/blas/ext/base/dnansum]. Beware that such performance gains may come at the cost of additional complexity when having to perform manual memory management. Choosing between implementations depends heavily on the particular needs and constraints of your application, with no one choice universally better than the other.
+-   This package implements routines using WebAssembly. When provided arrays which are not allocated on a `dnansum` module memory instance, data must be explicitly copied to module memory prior to computation. Data movement may entail a performance cost, and, thus, if you are using arrays external to module memory, you should prefer using [`@stdlib/blas/ext/base/dnansum`][@stdlib/blas/ext/base/dnansum]. However, if working with arrays which are allocated and explicitly managed on module memory, you can achieve better performance when compared to the pure JavaScript implementations found in [`@stdlib/blas/ext/base/dnansum`][@stdlib/blas/ext/base/dnansum]. Beware that such performance gains may come at the cost of additional complexity when having to perform manual memory management. Choosing between implementations depends heavily on the particular needs and constraints of your application, with no one choice universally better than the other.
 
 </section>
 

lib/node_modules/@stdlib/blas/ext/base/wasm/dnansum/docs/types/index.d.ts

@@ -43,7 +43,7 @@ interface ModuleConstructor {
 	* });
 	*
 	* // Create a BLAS routine:
-	* var mod = new dapxsumkbn.Module( mem );
+	* var mod = new dnansum.Module( mem );
 	* // returns <Module>
 	*
 	* // Initialize the routine:
@@ -84,7 +84,7 @@ interface ModuleConstructor {
 	* });
 	*
 	* // Create a BLAS routine:
-	* var mod = dapxsumkbn.Module( mem );
+	* var mod = dnansum.Module( mem );
 	* // returns <Module>
 	*
 	* // Initialize the routine:
@@ -110,7 +110,7 @@ interface ModuleConstructor {
 }
 
 /**
-* Interface describing a `dapxsumkbn` WebAssembly module.
+* Interface describing a `dnansum` WebAssembly module.
 */
 interface Module extends ModuleWrapper {
 	/**
@@ -132,7 +132,7 @@ interface Module extends ModuleWrapper {
 	* });
 	*
 	* // Create a BLAS routine:
-	* var mod = new dapxsumkbn.Module( mem );
+	* var mod = new dnansum.Module( mem );
 	* // returns <Module>
 	*
 	* // Initialize the routine:
@@ -176,7 +176,7 @@ interface Module extends ModuleWrapper {
 	* });
 	*
 	* // Create a BLAS routine:
-	* var mod = new dapxsumkbn.Module( mem );
+	* var mod = new dnansum.Module( mem );
 	* // returns <Module>
 	*
 	* // Initialize the routine:
@@ -202,7 +202,7 @@ interface Module extends ModuleWrapper {
 }
 
 /**
-* Interface describing `dapxsumkbn`.
+* Interface describing `dnansum`.
 */
 interface Routine extends ModuleWrapper {
 	/**
@@ -218,7 +218,7 @@ interface Routine extends ModuleWrapper {
 	*
 	* var x = new Float64Array( [ 1.0, -2.0, NaN 2.0 ] );
 	*
-	* var out = dapxsumkbn.main( 4, x, 1 );
+	* var out = dnansum.main( 4, x, 1 );
 	* // returns 1.0
 	*/
 	main( N: number, x: Float64Array, strideX: number ): number;
@@ -237,7 +237,7 @@ interface Routine extends ModuleWrapper {
 	*
 	* var x = new Float64Array( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 	*
-	* var out = dapxsumkbn.ndarray( 4, x, 2, 1 );
+	* var out = dnansum.ndarray( 4, x, 2, 1 );
 	* // returns 5.0
 	*/
 	ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number;
@@ -259,7 +259,7 @@ interface Routine extends ModuleWrapper {
 	* });
 	*
 	* // Create a BLAS routine:
-	* var mod = new dapxsumkbn.Module( mem );
+	* var mod = new dnansum.Module( mem );
 	* // returns <Module>
 	*
 	* // Initialize the routine:
@@ -297,20 +297,20 @@ interface Routine extends ModuleWrapper {
 *
 * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
 *
-* var out = dapxsumkbn.main( 4, x, 1 );
+* var out = dnansum.main( 4, x, 1 );
 * // returns 1.0
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 *
-* var out = dapxsumkbn.ndarray( 4, x, 2, 1 );
+* var out = dnansum.ndarray( 4, x, 2, 1 );
 * // returns 25.0
 */
-declare var dapxsumkbn: Routine;
+declare var dnansum: Routine;
 
 
 // EXPORTS //
 
-export = dapxsumkbn;
+export = dnansum;

lib/node_modules/@stdlib/blas/ext/base/wasm/dnansum/package.json

@@ -1,5 +1,5 @@
 {
-  "name": "@stdlib/blas/base/ext/wasm/dnansum",
+  "name": "@stdlib/blas/ext/base/wasm/dnansum",
   "version": "0.0.0",
   "description": "Calculate the sum of double-precision floating-point strided array elements, ignoring NaN values",
   "license": "Apache-2.0",