How to Measure Execution Time of a Method in C#

Measuring the execution time of C# methods is essential for performance optimization and identifying bottlenecks in your application.

The most straightforward approach uses the Stopwatch class from the System.Diagnostics namespace, which provides high-precision timing capabilities.

This approach is perfect for quick performance checks during development or when troubleshooting specific methods in production code.

Here's a practical example: Imagine you have a method that processes a large dataset and you want to measure its performance.

First, add using System.Diagnostics; to your imports. Then implement timing as shown below:

public void MeasurePerformance()
{
    Stopwatch stopwatch = new Stopwatch();
    
    // Start timing
    stopwatch.Start();
    
    // Call the method you want to measure
    ProcessLargeDataset();
    
    // Stop timing
    stopwatch.Stop();
    
    // Get the elapsed time
    Console.WriteLine($"Processing time: {stopwatch.ElapsedMilliseconds} ms");
    // Or use ElapsedTicks for higher precision
    Console.WriteLine($"Processing ticks: {stopwatch.ElapsedTicks}");
}

For more advanced scenarios, consider using the BenchmarkDotNet library, which offers comprehensive benchmarking with statistical analysis.

Simply install the NuGet package, decorate methods with the [Benchmark] attribute, and run BenchmarkRunner.Run<YourBenchmarkClass>() to generate detailed reports comparing different implementation strategies.

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Related

When working with URLs in C#, encoding is essential to ensure that special characters (like spaces, ?, &, and =) don’t break the URL structure. The recommended way to encode a string for a URL is by using Uri.EscapeDataString(), which converts unsafe characters into their percent-encoded equivalents.

string rawText = "hello world!";
string encodedText = Uri.EscapeDataString(rawText);

Console.WriteLine(encodedText); // Output: hello%20world%21

This method encodes spaces as %20, making it ideal for query parameters.

For ASP.NET applications, you can also use HttpUtility.UrlEncode() (from System.Web), which encodes spaces as +:

using System.Web;

string encodedText = HttpUtility.UrlEncode("hello world!");
Console.WriteLine(encodedText); // Output: hello+world%21

For .NET Core and later, Uri.EscapeDataString() is the preferred choice.

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Storing passwords as plain text is dangerous. Instead, you should hash them using a strong, slow hashing algorithm like BCrypt, which includes built-in salting and resistance to brute-force attacks.

Step 1: Install BCrypt NuGet Package

Before using BCrypt, install the BCrypt.Net-Next package:

dotnet add package BCrypt.Net-Next

or via NuGet Package Manager:

Install-Package BCrypt.Net-Next

Step 2: Hash a Password

Use BCrypt.HashPassword() to securely hash a password before storing it:

using BCrypt.Net;

string password = "mySecurePassword123";
string hashedPassword = BCrypt.HashPassword(password);

Console.WriteLine(hashedPassword); // Output: $2a$12$...

Step 3: Verify a Password

To check a user's login attempt, use BCrypt.Verify():

bool isMatch = BCrypt.Verify("mySecurePassword123", hashedPassword);
Console.WriteLine(isMatch); // Output: True

Ensuring proper hashing should be at the top of your list when it comes to building authentication systems.

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When working with SQL Server, you may often need to count the number of unique values in a specific column. This is useful for analyzing data, detecting duplicates, and understanding dataset distributions.

Using COUNT(DISTINCT column_name)

To count the number of unique values in a column, SQL Server provides the COUNT(DISTINCT column_name) function. Here’s a simple example:

SELECT COUNT(DISTINCT column_name) AS distinct_count
FROM table_name;

This query will return the number of unique values in column_name.

Counting Distinct Values Across Multiple Columns

If you need to count distinct combinations of multiple columns, you can use a subquery:

SELECT COUNT(*) AS distinct_count
FROM (SELECT DISTINCT column1, column2 FROM table_name) AS subquery;

This approach ensures that only unique pairs of column1 and column2 are counted.

Why Use COUNT DISTINCT?

  • Helps in identifying unique entries in a dataset.
  • Useful for reporting and analytics.
  • Efficient way to check for duplicates.

By leveraging COUNT(DISTINCT column_name), you can efficiently analyze your database and extract meaningful insights. Happy querying!

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