The Importance of Refactoring in Reducing Maintenance Costs and Improving Code Quality

As software products grow and evolve over time, their codebase can become increasingly complex. When new features are added without addressing the existing code's structure, a phenomenon called technical debt accumulates. Over time, this debt leads to higher maintenance costs, slower development cycles, and increased likelihood of bugs. The importance of regular refactoring—especially when adding new features—cannot be overstated. It ensures that the code remains clean, scalable, and maintainable, thus significantly reducing long-term costs and improving overall software quality.

Refactoring is an Investment:

While it might seem like refactoring requires upfront effort, it's an investment that pays off significantly in the long run. By improving code quality, you reduce future maintenance costs, increase developer productivity, and enhance the overall stability and reliability of the software.

Continuous Refactoring is Crucial:

As you mentioned, it's essential to incorporate refactoring into the development process as an ongoing activity, rather than waiting for major code overhauls. This "little and often" approach minimizes disruption and ensures that the codebase remains in a healthy state.

Case Studies of Companies Investing in Code Rewrites

Companies like eBay, Facebook, Microsoft and several others have experienced firsthand the costs of neglecting regular refactoring. eBay, for example, had to rewrite their entire codebase three times:

1. First Rewrite: eBay’s first rewrite was a response to a near-death experience, where the software failed to scale appropriately and threatened the company’s existence.
2. Second Rewrite: Recognizing the threat posed by rapid growth, eBay began rewriting its code proactively to ensure they could scale effectively as they expanded.
3. Third Rewrite: In their most significant overhaul, eBay moved to a new programming language and architecture over the course of several years. This transition allowed them to continue delivering new functionality without negatively affecting their user base.

These examples demonstrate that while refactoring may seem costly in the short term, the long-term benefits—both in terms of product stability and cost savings—are immeasurable. In fact, investing in code quality through proper refactoring can save millions of dollars by reducing ongoing maintenance expenses and avoiding the need for major rewrites down the road.

Refactoring a Reporting Application in C#: A Case Study

In a recent project, I undertook the refactoring of a reporting system that was suffering from excessive repetitive code. This refactoring led to a upto 60% reduction in repetitive code.

By applying key refactoring principles such as extracting classes, creating helper functions, and employing design patterns like the factory pattern, I was able to streamline the code significantly.

My manager did not specifically ask me to refactor the code, but upon reviewing it, I found it clearly needed improvement. Taking the initiative, I decided to refactor it myself. The most interesting part is that it didn’t take any extra time, as I was already adding new reports. This approach ensured that my changes seamlessly integrated with other reports and that all functionalities were thoroughly tested.

Before refactoring, many reports had redundant code that was difficult to maintain. These reports often involved large blocks of repetitive logic, especially in cases like the ExportFactory class, which handled different report types.

The Problem: Long Switch Cases

Initially, the ExportFactory class contained a massive switch statement with 30 cases, each creating a different type of report. This not only made the code harder to read and maintain, but it also introduced the risk of bugs and inconsistencies. Here's an excerpt from the original code: The dummy report name is being used because the original code is in production, and there could be security concerns.

public class ExportFactory 
{
    public static IExport GetExportObject(ExportType exportType)
    {
        switch (exportType)
        {
            case ExportType.ThreeDaysReportExport:
                return new ThreeDaysReportExport();
            case ExportType.WeeklyExportReport:
                return new WeeklyExportReport();
            case ExportType.WeeklyExportTaxReport:
                return new WeeklyExportTaxReport();
            // ... other cases
            default:
                return null;
        }
    }
}        

The above approach not only became cumbersome to extend (for instance, when adding a new report type) but also complicated error handling, as the default return value was null, which could easily lead to NullReferenceExceptions in the calling code.

The Solution: Refactoring with a Dictionary and Factory Pattern

To reduce this complexity, I introduced a dictionary-based mapping that associates each ExportType with its corresponding report class. This approach made the code more readable, maintainable, and extendable. It also improved error handling by throwing a descriptive exception when an invalid export type is provided.

Here’s the refactored version of the ExportFactory:

public class ExportFactory
{
    private readonly Dictionary<ExportType, Func<IExport>> _exportMappings;

    public ExportFactory()
    {
        _exportMappings = new Dictionary<ExportType, Func<IExport>>
        {
            { ExportType.ThreeDaysReportExport, () => new ThreeDaysReportExport() },
            { ExportType.WeeklyExportReport, () => new WeeklyExportReport() },
            { ExportType.WeeklyExportTaxReport, () => new WeeklyExportTaxReport() },
            // Additional mappings...
        };
    }

    public IExport GetExportObject(ExportType exportType)
    {
        if (_exportMappings.TryGetValue(exportType, out var exportCreator))
        {
            return exportCreator();
        }

        throw new InvalidOperationException($"No export object found for export type: {exportType}");
    }
}        

public class ExportHandler
{
    private readonly ExportFactory _exportFactory;

    public ExportHandler(ExportFactory exportFactory)
    {
         _exportFactory = new ExportFactory();
    }

    public void Process()
    {
        try
        {
            // Retrieve the appropriate export object based on the export type ID
            var exportHandler = _exportFactory.GetExportObject(scheduledExport.ExportTypeId);

            // Additional processing logic...
            // Example: exportHandler.ProcessExportData();

        }
        catch (Exception ex)
        {
            // Log the exception with detailed information for troubleshooting
            LogError(ex);
        }
    }

    private void LogError(Exception ex)
    {
        // Assuming there's a logging mechanism in place
        // Log the exception (details could include the stack trace, message, etc.)
        Console.WriteLine($"Error: {ex.Message}");
    }
}
        

In this refactor, the ExportFactory no longer relies on a long switch statement. Instead, it uses a dictionary where the ExportType is mapped to a Func<IExport>. This makes it easy to add new report types—simply add a new entry to the dictionary. Furthermore, error handling is more robust, as an exception is now thrown if an invalid report type is requested.

Additional Refactor: Reducing Repetitive Utility Functions

As part of the refactor, I also streamlined several utility functions that were being called by the all the reports. These functions, such as those handling file paths, environment configuration, and report generation, were centralized into a ExportUtilities class, reducing redundant code across various reports.

public static class ExportUtilities
{
    public const int DefaultMaxInstitutionNameLength = 10;
    private static int _maxInstitutionNameLength = DefaultMaxInstitutionNameLength;

    public static int MaxInstitutionNameLength 
    { 
        get => _maxInstitutionNameLength; 
        private set => _maxInstitutionNameLength = Math.Max(value, DefaultMaxInstitutionNameLength); 
    }

    public static string GetEnvironmentFolderPath(string path)
    {
        string envType = ConfigurationManager.AppSettings["FilePath"];
        if (string.IsNullOrEmpty(envType))
        {
            throw new InvalidOperationException("Environment is not configured in AppSettings.");
        }
        return path.Replace("{FilePath}", envType);
    }

        public static string GetInstitutionFolderPath(string institutionCode, string institutionName)
    {
        string institutionNameLengthSetting = ConfigurationManager.AppSettings["InstitutionNameLength"];
        if (int.TryParse(institutionNameLengthSetting, out int parsedNameLength) && parsedNameLength > 0)
        {
            MaxInstitutionNameLength = parsedNameLength; 
        }

        if (string.IsNullOrEmpty(institutionCode))
        {
            throw new ArgumentException("Institution code cannot be null or empty", nameof(institutionCode));
        }

        if (string.IsNullOrEmpty(institutionName))
        {
            throw new ArgumentException("Institution name cannot be null or empty", nameof(institutionName));
        }

        string instName = institutionName.Length > MaxInstitutionNameLength
                        ? ? institutionName.Substring(0, MaxInstitutionNameLength)
                        ? : institutionName;

        return $"{institutionCode}-{instName}".Trim();
    }
    public static void EnsureDirectoryExists(string exportPath)
    {
        if (!Directory.Exists(exportPath))
        {
            Directory.CreateDirectory(exportPath);
        }
    }

    public static string GetExportFolderPath(string baseExportPath, string taxYear)
    {
        var exportPath = Path.Combine(baseExportPath, taxYear);
        EnsureDirectoryExists(exportPath);
        return exportPath;
    }

    public static void GenerateAndSaveReportFile(string filePath, string reportName, string dataSourceName, DataTable dataTable)
    {
        var reportViewer = new ReportViewer
        {
            ProcessingMode = ProcessingMode.Local,
            SizeToReportContent = true
        };

        var rdlcPath = ConfigurationManager.AppSettings["RdlcPath"];
        reportViewer.LocalReport.ReportPath = Path.Combine(rdlcPath, reportName); 
        reportViewer.LocalReport.DataSources.Add(new ReportDataSource(dataSourceName, dataTable));
        byte[] bytes = reportViewer.LocalReport.Render(format: "PDF", deviceInfo: null);
        using (var stream = new FileStream(filePath, FileMode.Create))
        {
            stream.Write(bytes, 0, bytes.Length);
        }
    }
}

// A few more functions were extracted from the long function and used in each //report, and the try-catch blocks that were at multiple levels were removed.        

By refactoring the utilities into a separate class, each report no longer needs to handle path configuration and file management independently. This further reduces the amount of repetitive code and improves maintainability.

The Results: Cleaner Code and Improved Maintainability

After applying these refactoring techniques, each report saw a 45-50% reduction in code size. Previously, each report had 181 lines of code, and now it has 106 lines of code, with one additional feature added: splitting each report by company name. This feature did not exist in the previous version, even though there were 181 lines of code. This reduction not only made the code cleaner and more maintainable but also improved the overall developer experience.

Here are some of the key benefits:

• Improved Readability: The refactored code is much easier to read and understand. The use of a dictionary-based factory pattern eliminates the need for ugly long switch-case statements.
• Better Error Handling: Throwing exceptions for unsupported export types ensures that issues are caught early, reducing the chances of runtime errors.
• Increased Maintainability: New report types can be added with minimal changes, and the utility functions ensure that common tasks like path handling are centralized and reusable.
• Reduced Redundancy: The utility functions that were being repeatedly used across various reports are now centralized in a single class, reducing code duplication.

Conclusion: Refactoring Pays Off

As demonstrated in this refactoring effort, applying best practices such as simplifying code with design patterns, reducing redundancy with utility functions, extract new function from long function and improving error handling can drastically improve the quality of a product. The upfront investment in refactoring results in long-term savings by reducing maintenance costs, increasing the development speed, and minimizing the risk of bugs.

Regularly refactoring code, especially when working with large, complex projects, is essential for avoiding the pitfalls of technical debt and ensuring that a software product can continue to grow and evolve with ease. By embracing the principles of clean code and refactoring, we not only improve the immediate codebase but also future-proof the product, ensuring its longevity and success.

In the end, good code base will save millions of dollars in ongoing maintenance and prevent ugly user experience from the customer’s perspective, which could trigger the loss of customers and business.