C# Code Analyzer Tool - How to build your own
C# Script that will summarize a given C# script in plain English. It should be a GUI and asks for path. Assume D:\ as default, but provide a browser. User can then browse to the script they want analyzed and summarized, Present output as a web page with search
To create a C# application that can summarize a given C# script in plain English and display the results in a GUI, follow these steps:
Install Visual Studio (if you haven't already) and create a new C# Windows Forms Application project.
Install Roslyn, the .NET Compiler Platform, to analyze the C# code. Add the following NuGet packages to your project:
Microsoft.CodeAnalysis.CSharp
Microsoft.CodeAnalysis.CSharp.Workspaces
Design the GUI in the Windows Forms designer:
Add a Label to prompt the user to enter the file path.
Add a TextBox to display the file path.
Add a Button with the text "Browse" to allow the user to select the file.
Add a Button with the text "Analyze" to start the code analysis.
Add a WebBrowser control to display the results as a web page.
Double-click the "Browse" button to create an event handler, and add the following code to open a File Dialog and update the TextBox with the selected file path:
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private void browseButton_Click(object sender, EventArgs e)
{
OpenFileDialog openFileDialog = new OpenFileDialog();
openFileDialog.Filter = "C# Files (*.cs)|*.cs";
openFileDialog.InitialDirectory = @"D:\";
if (openFileDialog.ShowDialog() == DialogResult.OK)
{
filePathTextBox.Text = openFileDialog.FileName;
}
}
Double-click the "Analyze" button to create an event handler, and add the following code to analyze the C# script and display the summary in the WebBrowser control:
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private async void analyzeButton_Click(object sender, EventArgs e)
{
string filePath = filePathTextBox.Text;
if (File.Exists(filePath))
{
string code = File.ReadAllText(filePath);
string summary = await SummarizeCode(code);
DisplaySummary(summary);
}
else
{
MessageBox.Show("File not found. Please enter a valid file path.");
}
}
Add the SummarizeCode method to analyze the C# code using Roslyn and generate the plain English summary:
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private async Task<string> SummarizeCode(string code)
{
StringBuilder summary = new StringBuilder();
// Add your code analysis and summarization logic here.
// Use the Roslyn API to analyze the C# code and generate a plain English summary.
return summary.ToString();
}
Add the DisplaySummary method to display the summary in the WebBrowser control as a formatted HTML page:
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private void DisplaySummary(string summary)
{
StringBuilder html = new StringBuilder();
html.Append("<html><head><style>body {font-family: Arial, sans-serif;} h1 {color: #5a9;} ul {list-style-type: none;} li {margin-bottom: 5px;}</style></head><body>");
html.Append("<h1>Code Summary</h1>");
html.Append("<ul>");
// Convert the summary to an HTML list.
string[] lines = summary.Split(new[] { Environment.NewLine }, StringSplitOptions.RemoveEmptyEntries);
foreach (string line in lines)
{
html.Append("<li>" + HttpUtility.HtmlEncode(line) + "</li>");
}
html.Append("</ul></body></html>");
webBrowser.DocumentText = html.ToString();
}
This code sets up the basic structure of the application. You'll need to implement the actual code analysis and summarization logic in the SummarizeCode method using the Roslyn API. The API provides rich functionality to analyze C# code and extract useful information such as classes, methods, properties, etc., which
User:
To get started with Roslyn, you can follow the official documentation and tutorials:
https://docs.microsoft.com/en-us/dotnet/csharp/roslyn-sdk/get-started
https://github.com/dotnet/roslyn/wiki/Getting-Started-C%23-Syntax-Analysis
Here's a simple example of how you can use Roslyn to analyze a C# script and extract class and method information:
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private async Task<string> SummarizeCode(string code)
{
StringBuilder summary = new StringBuilder();
SyntaxTree tree = CSharpSyntaxTree.ParseText(code);
CompilationUnitSyntax root = tree.GetCompilationUnitRoot();
IEnumerable<ClassDeclarationSyntax> classDeclarations = root.DescendantNodes().OfType<ClassDeclarationSyntax>();
foreach (var classDeclaration in classDeclarations)
{
summary.AppendLine($"Class: {classDeclaration.Identifier}");
IEnumerable<MethodDeclarationSyntax> methodDeclarations = classDeclaration.DescendantNodes().OfType<MethodDeclarationSyntax>();
foreach (var methodDeclaration in methodDeclarations)
{
summary.AppendLine($"\tMethod: {methodDeclaration.Identifier}");
}
}
return summary.ToString();
}
This example simply extracts class and method names from the given C# script, but you can extend this logic to provide a more detailed summary that includes properties, events, and other relevant information. Additionally, you can implement more advanced code analysis techniques, such as control flow and data flow analysis, to provide a more comprehensive and informative summary of the code.
Once you have implemented the desired code analysis and summarization logic in the SummarizeCode method, your application should be ready to run. When a user selects a C# script and clicks "Analyze," the application will display a plain English summary of the code in the WebBrowser control, formatted as an HTML page with search functionality.
User:
Can you do this in a similar way that GPT4 does it when user pastes in some code, but still let user point to the file to analyze as per above.
While I cannot directly integrate GPT-4 into your application, you can achieve a similar result by using OpenAI's API to analyze and summarize the C# script. First, you need to sign up for an API key on the OpenAI platform (https://beta.openai.com/signup/).
Once you have an API key, you can create a method that sends an API request with the C# script to the OpenAI API for analysis and summarization. To make API calls from C#, you will need to add the Newtonsoft.Json NuGet package to handle JSON data and the System.Net.Http NuGet package to handle HTTP requests.
Install the Newtonsoft.Json NuGet package:
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Install-Package Newtonsoft.Json
Install the System.Net.Http NuGet package:
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Install-Package System.Net.Http
Replace the SummarizeCode method with the following implementation:
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private async Task<string> SummarizeCode(string code)
{
string prompt = $"Summarize the following C# code in plain English:\n\n{code}";
return await GenerateTextFromGPT4(prompt);
}
private async Task<string> GenerateTextFromGPT4(string prompt)
{
using (HttpClient client = new HttpClient())
{
string apiKey = "your_openai_api_key"; // Replace with your actual API key
string apiUrl = "https://api.openai.com/v1/engines/davinci-codex/completions"; // Replace with the GPT-4 API URL when it's available
client.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", apiKey);
client.DefaultRequestHeaders.Accept.Add(new MediaTypeWithQualityHeaderValue("application/json"));
JObject requestBody = new JObject
{
{ "prompt", prompt },
{ "max_tokens", 100 },
{ "n", 1 },
{ "stop", null },
{ "temperature", 0.5 }
};
StringContent content = new StringContent(requestBody.ToString(), Encoding.UTF8, "application/json");
HttpResponseMessage response = await client.PostAsync(apiUrl, content);
if (response.IsSuccessStatusCode)
{
string responseJson = await response.Content.ReadAsStringAsync();
JObject responseObject = JObject.Parse(responseJson);
return responseObject["choices"][0]["text"].ToString().Trim();
}
else
{
throw new Exception($"OpenAI API request failed: {response.StatusCode}");
}
}
}
Remember to replace "your_openai_api_key" with your actual OpenAI API key. The GenerateTextFromGPT4 method sends a request to the OpenAI API with the given prompt, which should include the C# code to be summarized. When the GPT-4 API becomes available, replace the apiUrl value with the appropriate GPT-4 API URL.
With this setup, when a user selects a C# script and clicks "Analyze," the application will send the script to the OpenAI API for analysis and summarization, and then display the plain English summary in the WebBrowser control, formatted as an HTML page with search functionality.
Conclusion
Here's a comparison of the two methods, the Roslyn method, and the GPT API method, in a table format:
| Aspect | Roslyn Method | GPT API Method |
|---|---|---|
| Summary | Analyzes C# code using Roslyn, a .NET Compiler Platform. | Summarizes C# code using the OpenAI GPT API. |
| Pros | - Accurate code analysis | - High-level understanding of code |
| - In-depth and precise summaries | - Natural language summaries | |
| - No reliance on external services | - Minimal implementation effort | |
| - No API key or usage limits | ||
| Cons | - Requires implementation of | - Relies on external API service |
| code analysis and summarization logic | - Requires API key | |
| - May require frequent updates to | - API usage limits and costs | |
| support new language features | - May not be as precise as Roslyn in code analysis | |
| - May not provide natural language-like summaries | - Limited to GPT's understanding of programming languages |
The Roslyn method provides accurate code analysis and in-depth summaries, as it's specifically designed for the C# language. It doesn't rely on external services and doesn't require an API key or have usage limits. However, it requires more implementation effort, as you need to develop the code analysis and summarization logic yourself, and it may require frequent updates to support new language features. Additionally, the summaries might not be as natural-sounding as those generated by the GPT API method.
On the other hand, the GPT API method offers high-level understanding of the code, natural language summaries, and minimal implementation effort. However, it relies on an external API service, requires an API key, and has usage limits and costs associated with it. Furthermore, it might not be as precise as the Roslyn method in code analysis and is limited to GPT's understanding of programming languages.
Each method has its advantages and disadvantages, and the best choice depends on your specific requirements and constraints, such as the desired level of code analysis, summarization quality, natural language output, and reliance on external services.
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