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Small changes sometimes make a huge difference. Learn these 6 tips to improve the performance of your application just by handling strings correctly.

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Sometimes, just a minor change makes a huge difference. Maybe you won’t notice it when performing the same operation a few times. Still, the improvement is significant when repeating the operation thousands of times.

In this article, we will learn five simple tricks to improve the performance of your application when dealing with strings.

Note: this article is part of C# Advent Calendar 2023, organized by Matthew D. Groves: it’s maybe the only Christmas tradition I like (yes, I’m kind of a Grinch 😂).

Benchmark structure, with dependencies

Before jumping to the benchmarks, I want to spend a few words on the tools I used for this article.

The project is a .NET 8 class library running on a laptop with an i5 processor.

Running benchmarks with BenchmarkDotNet

I’m using BenchmarkDotNet to create benchmarks for my code. BenchmarkDotNet is a library that runs your methods several times, captures some metrics, and generates a report of the executions. If you follow my blog, you might know I’ve used it several times – for example, in my old article “Enum.HasFlag performance with BenchmarkDotNet”.

All the benchmarks I created follow the same structure:

[MemoryDiagnoser]
public class BenchmarkName()
{
    [Params(1, 5, 10)] // clearly, I won't use these values
    public int Size;

    public string[] AllStrings { get; set; }

    [IterationSetup]
    public void Setup()
    {
        AllStrings = StringArrayGenerator.Generate(Size, "hello!", "HELLO!");
    }

    [Benchmark(Baseline=true)]
    public void FirstMethod()
    {
        //omitted
    }

    [Benchmark]
    public void SecondMethod()
    {
        //omitted
    }
}

In short:

• the class is marked with the [MemoryDiagnoser] attribute: the benchmark will retrieve info for both time and memory usage;
• there is a property named Size with the attribute [Params]: this attribute lists the possible values for the Size property;
• there is a method marked as [IterationSetup]: this method runs before every single execution, takes the value from the Size property, and initializes the AllStrings array;
• the methods that are parts of the benchmark are marked with the [Benchmark] attribute.

Generating strings with Bogus

I relied on Bogus to create dummy values. This NuGet library allows you to generate realistic values for your objects with a great level of customization.

The string array generation strategy is shared across all the benchmarks, so I moved it to a static method:

 public static class StringArrayGenerator
 {
     public static string[] Generate(int size, params string[] additionalStrings)
     {
         string[] array = new string[size];
         Faker faker = new Faker();

         List<string> fixedValues = [
             string.Empty,
             "   ",
             "\n  \t",
             null
         ];

         if (additionalStrings != null)
             fixedValues.AddRange(additionalStrings);

         for (int i = 0; i < array.Length; i++)
         {
             if (Random.Shared.Next() % 4 == 0)
             {
                 array[i] = Random.Shared.GetItems<string>(fixedValues.ToArray(), 1).First();
             }
             else
             {
                 array[i] = faker.Lorem.Word();
             }
         }

         return array;
     }
 }

Here I have a default set of predefined values ([string.Empty, " ", "\n \t", null]), which can be expanded with the values coming from the additionalStrings array. These values are then placed in random positions of the array.

In most cases, though, the value of the string is defined by Bogus.

Generating plots with chartbenchmark.net

To generate the plots you will see in this article, I relied on chartbenchmark.net, a fantastic tool that transforms the output generated by BenchmarkDotNet on the console in a dynamic, customizable plot. This tool created by Carlos Villegas is available on GitHub, and it surely deserves a star!

Please note that all the plots in this article have a Log10 scale: this scale allows me to show you the performance values of all the executions in the same plot. If I used the Linear scale, you would be able to see only the biggest values.

We are ready. It’s time to run some benchmarks!

Tip #1: StringBuilder is (almost always) better than String Concatenation

Let’s start with a simple trick: if you need to concatenate strings, using a StringBuilder is generally more efficient than concatenating string.

[MemoryDiagnoser]
public class StringBuilderVsConcatenation()
{
    [Params(4, 100, 10_000, 100_000)]
    public int Size;

    public string[] AllStrings { get; set; }

    [IterationSetup]
    public void Setup()
    {
        AllStrings = StringArrayGenerator.Generate(Size, "hello!", "HELLO!");
    }

    [Benchmark]
    public void WithStringBuilder()
    {
        StringBuilder sb = new StringBuilder();

        foreach (string s in AllStrings)
        {
            sb.Append(s);
        }

        var finalString = sb.ToString();
    }

    [Benchmark]
    public void WithConcatenation()
    {
        string finalString = "";
        foreach (string s in AllStrings)
        {
            finalString += s;
        }
    }
}

Whenever you concatenate strings with the + sign, you create a new instance of a string. This operation takes some time and allocates memory for every operation.

On the contrary, using a StringBuilder object, you can add the strings in memory and generate the final string using a performance-wise method.

Here’s the result table:

Let’s see it as a plot.

Beware of the scale in the diagram!: it’s a Log10 scale, so you’d better have a look at the value displayed on the Y-axis.

As you can see, there is a considerable performance improvement.

There are some remarkable points:

1. When there are just a few strings to concatenate, the + operator is more performant, both on timing and allocated memory;
2. When you need to concatenate 100000 strings, the concatenation is ~7000 times slower than the string builder.

In conclusion, use the StringBuilder to concatenate more than 5 or 6 strings. Use the string concatenation for smaller operations.

Edit 2024-01-08: turn out that string.Concat has an overload that accepts an array of strings. string.Concat(string[]) is actually faster than using the StringBuilder. Read more this article by Robin Choffardet.

Tip #2: EndsWith(string) vs EndsWith(char): pick the right overload

One simple improvement can be made if you use StartsWith or EndsWith, passing a single character.

There are two similar overloads: one that accepts a string, and one that accepts a char.

[MemoryDiagnoser]
public class EndsWithStringVsChar()
{
    [Params(100, 1000, 10_000, 100_000, 1_000_000)]
    public int Size;

    public string[] AllStrings { get; set; }

    [IterationSetup]
    public void Setup()
    {
        AllStrings = StringArrayGenerator.Generate(Size);
    }

    [Benchmark(Baseline = true)]
    public void EndsWithChar()
    {
    foreach (string s in AllStrings)
    {
        _ = s?.EndsWith('e');
    }
    }

    [Benchmark]
    public void EndsWithString()
    {
    foreach (string s in AllStrings)
    {
        _ = s?.EndsWith("e");
    }
    }
}

We have the following results:

Again, let’s generate the plot using the Log10 scale:

They appear to be almost identical, but look closely: based on this benchmark, when we have 10000, using EndsWith(string) is 10x slower than EndsWith(char).

Also, here, the duration ratio on the 1.000.000-items array is ~3.5. At first, I thought there was an error on the benchmark, but when rerunning it on the benchmark, the ratio did not change.

It looks like you have the best improvement ratio when the array has ~10.000 items.

Tip #3: IsNullOrEmpty vs IsNullOrWhitespace vs IsNullOrEmpty + Trim

As you might know, string.IsNullOrWhiteSpace performs stricter checks than string.IsNullOrEmpty.

(If you didn’t know, have a look at this quick explanation of the cases covered by these methods).

Does it affect performance?

To demonstrate it, I have created three benchmarks: one for string.IsNullOrEmpty, one for string.IsNullOrWhiteSpace, and another one that lays in between: it first calls Trim() on the string, and then calls string.IsNullOrEmpty.

[MemoryDiagnoser]
public class StringEmptyBenchmark
{
    [Params(100, 1000, 10_000, 100_000, 1_000_000)]
    public int Size;

    public string[] AllStrings { get; set; }

    [IterationSetup]
    public void Setup()
    {
        AllStrings = StringArrayGenerator.Generate(Size);
    }

    [Benchmark(Baseline = true)]
    public void StringIsNullOrEmpty()
    {
        foreach (string s in AllStrings)
        {
            _ = string.IsNullOrEmpty(s);
        }
    }

    [Benchmark]
    public void StringIsNullOrEmptyWithTrim()
    {
        foreach (string s in AllStrings)
        {
            _ = string.IsNullOrEmpty(s?.Trim());
        }
    }

    [Benchmark]
    public void StringIsNullOrWhitespace()
    {
        foreach (string s in AllStrings)
        {
            _ = string.IsNullOrWhiteSpace(s);
        }
    }
}

We have the following values:

As you can see from the Log10 table, the results are pretty similar:

On average, StringIsNullOrWhitespace is ~2 times slower than StringIsNullOrEmpty.

So, what should we do? Here’s my two cents:

1. For all the data coming from the outside (passed as input to your system, received from an API call, read from the database), use string.IsNUllOrWhiteSpace: this way you can ensure that you are not receiving unexpected data;
2. If you read data from an external API, customize your JSON deserializer to convert whitespace strings as empty values;
3. Needless to say, choose the proper method depending on the use case. If a string like “\n \n \t” is a valid value for you, use string.IsNullOrEmpty.

Tip #4: ToUpper vs ToUpperInvariant vs ToLower vs ToLowerInvariant: they look similar, but they are not

Even though they look similar, there is a difference in terms of performance between these four methods.

[MemoryDiagnoser]
public class ToUpperVsToLower()
{
    [Params(100, 1000, 10_000, 100_000, 1_000_000)]
    public int Size;

    public string[] AllStrings { get; set; }

    [IterationSetup]
    public void Setup()
    {
        AllStrings = StringArrayGenerator.Generate(Size);
    }

    [Benchmark]
    public void WithToUpper()
    {
        foreach (string s in AllStrings)
        {
            _ = s?.ToUpper();
        }
    }

    [Benchmark]
    public void WithToUpperInvariant()
    {
        foreach (string s in AllStrings)
        {
            _ = s?.ToUpperInvariant();
        }
    }

    [Benchmark]
    public void WithToLower()
    {
        foreach (string s in AllStrings)
        {
            _ = s?.ToLower();
        }
    }

    [Benchmark]
    public void WithToLowerInvariant()
    {
        foreach (string s in AllStrings)
        {
            _ = s?.ToLowerInvariant();
        }
    }
}

What will this benchmark generate?

Let’s see it as the usual Log10 plot:

We can notice a few points:

1. The ToUpper family is generally slower than the ToLower family;
2. The Invariant family is faster than the non-Invariant one; we will see more below;

So, if you have to normalize strings using the same casing, ToLowerInvariant is the best choice.

Tip #5: OrdinalIgnoreCase vs InvariantCultureIgnoreCase: logically (almost) equivalent, but with different performance

Comparing strings is trivial: the string.Compare method is all you need.

There are several modes to compare strings: you can specify the comparison rules by setting the comparisonType parameter, which accepts a StringComparison value.

[MemoryDiagnoser]
public class StringCompareOrdinalVsInvariant()
{
    [Params(100, 1000, 10_000, 100_000, 1_000_000)]
    public int Size;

    public string[] AllStrings { get; set; }

    [IterationSetup]
    public void Setup()
    {
        AllStrings = StringArrayGenerator.Generate(Size, "hello!", "HELLO!");
    }

    [Benchmark(Baseline = true)]
    public void WithOrdinalIgnoreCase()
    {
        foreach (string s in AllStrings)
        {
            _ = string.Equals(s, "hello!", StringComparison.OrdinalIgnoreCase);
        }
    }

    [Benchmark]
    public void WithInvariantCultureIgnoreCase()
    {
        foreach (string s in AllStrings)
        {
            _ = string.Equals(s, "hello!", StringComparison.InvariantCultureIgnoreCase);
        }
    }
}

Let’s see the results:

As you can see, there’s a HUGE difference between Ordinal and Invariant.

When dealing with 100.000 items, StringComparison.InvariantCultureIgnoreCase is 12 times slower than StringComparison.OrdinalIgnoreCase!

Why? Also, why should we use one instead of the other?

Have a look at this code snippet:

var s1 = "Aa";
var s2 = "A" + new string('\u0000', 3) + "a";

string.Equals(s1, s2, StringComparison.InvariantCultureIgnoreCase); //True
string.Equals(s1, s2, StringComparison.OrdinalIgnoreCase); //False

As you can see, s1 and s2 represent equivalent, but not equal, strings. We can then deduce that OrdinalIgnoreCase checks for the exact values of the characters, while InvariantCultureIgnoreCase checks the string’s “meaning”.

So, in most cases, you might want to use OrdinalIgnoreCase (as always, it depends on your use case!)

Tip #6: Newtonsoft vs System.Text.Json: it’s a matter of memory allocation, not time

For the last benchmark, I created the exact same model used as an example in the official documentation.

This benchmark aims to see which JSON serialization library is faster: Newtonsoft or System.Text.Json?

[MemoryDiagnoser]
public class JsonSerializerComparison
{
    [Params(100, 10_000, 1_000_000)]
    public int Size;
    List<User?> Users { get; set; }

    [IterationSetup]
    public void Setup()
    {
        Users = UsersCreator.GenerateUsers(Size);
    }

    [Benchmark(Baseline = true)]
    public void WithJson()
    {
        foreach (User? user in Users)
        {
            var asString = System.Text.Json.JsonSerializer.Serialize(user);

            _ = System.Text.Json.JsonSerializer.Deserialize<User?>(asString);
        }
    }

    [Benchmark]
    public void WithNewtonsoft()
    {
        foreach (User? user in Users)
        {
            string asString = Newtonsoft.Json.JsonConvert.SerializeObject(user);
            _ = Newtonsoft.Json.JsonConvert.DeserializeObject<User?>(asString);
        }
    }
}

As you might know, the .NET team has added lots of performance improvements to the JSON Serialization functionalities, and you can really see the difference!

As you can see, Newtonsoft is 2x slower than System.Text.Json, and it allocates 3x the memory compared with the other library.

So, well, if you don’t use library-specific functionalities, I suggest you replace Newtonsoft with System.Text.Json.

Wrapping up

In this article, we learned that even tiny changes can make a difference in the long run.

Let’s recap some:

1. Using StringBuilder is generally WAY faster than using string concatenation unless you need to concatenate 2 to 4 strings;
2. Sometimes, the difference is not about execution time but memory usage;
3. EndsWith and StartsWith perform better if you look for a char instead of a string. If you think of it, it totally makes sense!
4. More often than not, string.IsNullOrWhiteSpace performs better checks than string.IsNullOrEmpty; however, there is a huge difference in terms of performance, so you should pick the correct method depending on the usage;
5. ToUpper and ToLower look similar; however, ToLower is quite faster than ToUpper;
6. Ordinal and Invariant comparison return the same value for almost every input; but Ordinal is faster than Invariant;
7. Newtonsoft performs similarly to System.Text.Json, but it allocates way more memory.

This article first appeared on Code4IT 🐧

My suggestion is always the same: take your time to explore the possibilities! Toy with your code, try to break it, benchmark it. You’ll find interesting takes!

I hope you enjoyed this article! Let’s keep in touch on Twitter or LinkedIn! 🤜🤛

Happy coding!

🐧