Day 4 (the missing day): Building Data Import/Export Services for Your ERP System

Day 4 (the missing day): Building Data Import/Export Services for Your ERP System

Welcome back to our ERP development series! In previous days, we’ve covered the foundational architecture, database design, and core entity structures for our accounting system. Today, we’re tackling an essential but often overlooked aspect of any enterprise software: data import and export capabilities.

Why is this important? Because no enterprise system exists in isolation. Companies need to move data between systems, migrate from legacy software, or simply handle batch data operations. In this article, we’ll build robust import/export services for the Chart of Accounts, demonstrating principles you can apply to any part of your ERP system.

The Importance of Data Exchange

Before diving into the code, let’s understand why dedicated import/export functionality matters:

  1. Data Migration – When companies adopt your ERP, they need to transfer existing data
  2. System Integration – ERPs need to exchange data with other business systems
  3. Batch Processing – Accountants often prepare data in spreadsheets before importing
  4. Backup & Transfer – Provides a simple way to backup or transfer configurations
  5. User Familiarity – Many users are comfortable working with CSV files

CSV (Comma-Separated Values) is our format of choice because it’s universally supported and easily edited in spreadsheet applications like Excel, which most business users are familiar with.

Our Implementation Approach

For our Chart of Accounts module, we’ll create:

  1. A service interface defining import/export operations
  2. A concrete implementation handling CSV parsing/generation
  3. Unit tests verifying all functionality

Our goal is to maintain clean separation of concerns, robust error handling, and clear validation rules.

Defining the Interface

First, we define a clear contract for our import/export service:

/// <summary>
/// Interface for chart of accounts import/export operations
/// </summary>
public interface IAccountImportExportService
{
    /// <summary>
    /// Imports accounts from a CSV file
    /// </summary>
    /// <param name="csvContent">Content of the CSV file as a string</param>
    /// <param name="userName">User performing the operation</param>
    /// <returns>Collection of imported accounts and any validation errors</returns>
    Task<(IEnumerable<IAccount> ImportedAccounts, IEnumerable<string> Errors)> ImportFromCsvAsync(string csvContent, string userName);

    /// <summary>
    /// Exports accounts to a CSV format
    /// </summary>
    /// <param name="accounts">Accounts to export</param>
    /// <returns>CSV content as a string</returns>
    Task<string> ExportToCsvAsync(IEnumerable<IAccount> accounts);
}

Notice how we use C# tuples to return both the imported accounts and any validation errors from the import operation. This gives callers full insight into the operation’s results.

Implementing CSV Import

The import method is the more complex of the two, requiring:

  1. Parsing and validating the CSV structure
  2. Converting CSV data to domain objects
  3. Validating the created objects
  4. Reporting any errors along the way

Here’s our implementation approach:

public async Task<(IEnumerable<IAccount> ImportedAccounts, IEnumerable<string> Errors)> ImportFromCsvAsync(string csvContent, string userName)
{
    List<AccountDto> importedAccounts = new List<AccountDto>();
    List<string> errors = new List<string>();

    if (string.IsNullOrEmpty(csvContent))
    {
        errors.Add("CSV content is empty");
        return (importedAccounts, errors);
    }

    try
    {
        // Split the CSV into lines
        string[] lines = csvContent.Split(new[] { "\r\n", "\r", "\n" }, StringSplitOptions.RemoveEmptyEntries);
        
        if (lines.Length <= 1)
        {
            errors.Add("CSV file contains no data rows");
            return (importedAccounts, errors);
        }

        // Assume first line is header
        string[] headers = ParseCsvLine(lines[0]);
        
        // Validate headers
        if (!ValidateHeaders(headers, errors))
        {
            return (importedAccounts, errors);
        }

        // Process data rows
        for (int i = 1; i < lines.Length; i++)
        {
            string[] fields = ParseCsvLine(lines[i]);
            
            if (fields.Length != headers.Length)
            {
                errors.Add($"Line {i + 1}: Column count mismatch. Expected {headers.Length}, got {fields.Length}");
                continue;
            }

            var account = CreateAccountFromCsvFields(headers, fields);
            
            // Validate account
            if (!_accountValidator.ValidateAccount(account))
            {
                errors.Add($"Line {i + 1}: Account validation failed for account {account.AccountName}");
                continue;
            }

            // Set audit information
            _auditService.SetCreationAudit(account, userName);
            
            importedAccounts.Add(account);
        }

        return (importedAccounts, errors);
    }
    catch (Exception ex)
    {
        errors.Add($"Error importing CSV: {ex.Message}");
        return (importedAccounts, errors);
    }
}

Key aspects of this implementation:

  1. Early validation – We quickly detect and report basic issues like empty input
  2. Row-by-row processing – Each line is processed independently, allowing partial success
  3. Detailed error reporting – We collect specific errors with line numbers
  4. Domain validation – We apply business rules from AccountValidator
  5. Audit trail – We set audit fields for each imported account

The ParseCsvLine method handles the complexities of CSV parsing, including quoted fields that may contain commas:

private string[] ParseCsvLine(string line)
{
    List<string> fields = new List<string>();
    bool inQuotes = false;
    int startIndex = 0;
    
    for (int i = 0; i < line.Length; i++)
    {
        if (line[i] == '"')
        {
            inQuotes = !inQuotes;
        }
        else if (line[i] == ',' && !inQuotes)
        {
            fields.Add(line.Substring(startIndex, i - startIndex).Trim().TrimStart('"').TrimEnd('"'));
            startIndex = i + 1;
        }
    }
    
    // Add the last field
    fields.Add(line.Substring(startIndex).Trim().TrimStart('"').TrimEnd('"'));
    
    return fields.ToArray();
}

Implementing CSV Export

The export method is simpler, converting domain objects to CSV format:

public Task<string> ExportToCsvAsync(IEnumerable<IAccount> accounts)
{
    if (accounts == null || !accounts.Any())
    {
        return Task.FromResult(GetCsvHeader());
    }

    StringBuilder csvBuilder = new StringBuilder();
    
    // Add header
    csvBuilder.AppendLine(GetCsvHeader());
    
    // Add data rows
    foreach (var account in accounts)
    {
        csvBuilder.AppendLine(GetCsvRow(account));
    }
    
    return Task.FromResult(csvBuilder.ToString());
}

We take special care to handle edge cases like null or empty collections, making the API robust against improper usage.

Testing the Implementation

Our test suite verifies both the happy paths and various error conditions:

  1. Import validation – Tests for empty content, missing headers, etc.
  2. Export formatting – Tests for proper CSV generation, handling of special characters
  3. Round-trip integrity – Tests exporting and re-importing preserves data integrity

For example, here’s a round-trip test to verify data integrity:

[Test]
public async Task RoundTrip_ExportThenImport_PreservesAccounts()
{
    // Arrange
    var originalAccounts = new List<IAccount>
    {
        new AccountDto
        {
            Id = Guid.NewGuid(),
            AccountName = "Cash",
            OfficialCode = "11000",
            AccountType = AccountType.Asset,
            // other properties...
        },
        new AccountDto
        {
            Id = Guid.NewGuid(),
            AccountName = "Accounts Receivable",
            OfficialCode = "12000",
            AccountType = AccountType.Asset,
            // other properties...
        }
    };

    // Act
    string csv = await _importExportService.ExportToCsvAsync(originalAccounts);
    var (importedAccounts, errors) = await _importExportService.ImportFromCsvAsync(csv, "Test User");

    // Assert
    Assert.That(errors, Is.Empty);
    Assert.That(importedAccounts.Count(), Is.EqualTo(originalAccounts.Count));
    
    // Check first account
    var firstOriginal = originalAccounts[0];
    var firstImported = importedAccounts.First();
    Assert.That(firstImported.AccountName, Is.EqualTo(firstOriginal.AccountName));
    Assert.That(firstImported.OfficialCode, Is.EqualTo(firstOriginal.OfficialCode));
    Assert.That(firstImported.AccountType, Is.EqualTo(firstOriginal.AccountType));
    
    // Check second account similarly...
}

Integration with the Broader System

This service isn’t meant to be used in isolation. In a complete ERP system, you’d typically:

  1. Add a controller to expose these operations via API endpoints
  2. Create UI components for file upload/download
  3. Implement progress reporting for larger imports
  4. Add transaction support to make imports atomic
  5. Include validation rules specific to your business domain

Design Patterns and Best Practices

Our implementation exemplifies several important patterns:

  1. Interface Segregation – The service has a focused, cohesive purpose
  2. Dependency Injection – We inject the IAuditService rather than creating it
  3. Early Validation – We validate input before processing
  4. Detailed Error Reporting – We collect and return specific errors
  5. Defensive Programming – We handle edge cases and exceptions gracefully

Future Extensions

This pattern can be extended to other parts of your ERP system:

  1. Customer/Vendor Data – Import/export contact information
  2. Inventory Items – Handle product catalog updates
  3. Journal Entries – Process batch financial transactions
  4. Reports – Export financial data for external analysis

Conclusion

Data import/export capabilities are a critical component of any enterprise system. They bridge the gap between systems, facilitate migration, and support batch operations. By implementing these services with careful error handling and validation, we’ve added significant value to our ERP system.

In the next article, we’ll explore building financial reporting services to generate balance sheets, income statements, and other critical financial reports from our accounting data.

Stay tuned, and happy coding!


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Building a Comprehensive Accounting System Integration Test – Day 5

Building a Comprehensive Accounting System Integration Test – Day 5

Integration testing is a critical phase in software development where individual modules are combined and tested as a group. In our accounting system, we’ve created a robust integration test that demonstrates how the Document module and Chart of Accounts module interact to form a functional accounting system. In this post, I’ll explain the components and workflow of our integration test.

The Architecture of Our Integration Test

Our integration test simulates a small retail business’s accounting operations. Let’s break down the key components:

Test Fixture Setup

The AccountingIntegrationTests class contains all our test methods and is decorated with the [TestFixture] attribute to identify it as a NUnit test fixture. The Setup method initializes our services and data structures:

[SetUp]
public async Task Setup()
{
    // Initialize services
    _auditService = new AuditService();
    _documentService = new DocumentService(_auditService);
    _transactionService = new TransactionService();
    _accountValidator = new AccountValidator();
    _accountBalanceCalculator = new AccountBalanceCalculator();
    
    // Initialize storage
    _accounts = new Dictionary<string, AccountDto>();
    _documents = new Dictionary<string, IDocument>();
    _transactions = new Dictionary<string, ITransaction>();
    
    // Create Chart of Accounts
    await SetupChartOfAccounts();
}

This method:

  1. Creates instances of our services
  2. Sets up in-memory storage for our entities
  3. Calls SetupChartOfAccounts() to create our initial chart of accounts

Chart of Accounts Setup

The SetupChartOfAccounts method creates a basic chart of accounts for our retail business:

private async Task SetupChartOfAccounts()
{
    // Clear accounts dictionary in case this method is called multiple times
    _accounts.Clear();
    
    // Assets (1xxxx)
    await CreateAccount("Cash", "10100", AccountType.Asset, "Cash on hand and in banks");
    await CreateAccount("Accounts Receivable", "11000", AccountType.Asset, "Amounts owed by customers");
    // ... more accounts
    
    // Verify all accounts are valid
    foreach (var account in _accounts.Values)
    {
        bool isValid = _accountValidator.ValidateAccount(account);
        Assert.That(isValid, Is.True, $"Account {account.AccountName} validation failed");
    }
    
    // Verify expected number of accounts
    Assert.That(_accounts.Count, Is.EqualTo(17), "Expected 17 accounts in chart of accounts");
}

This method:

  1. Creates accounts for each category (Assets, Liabilities, Equity, Revenue, and Expenses)
  2. Validates each account using our AccountValidator
  3. Ensures we have the expected number of accounts

Individual Transaction Tests

We have separate test methods for specific transaction types:

Purchase of Inventory

CanRecordPurchaseOfInventory demonstrates recording a supplier invoice:

[Test]
public async Task CanRecordPurchaseOfInventory()
{
    // Arrange - Create document
    var document = new DocumentDto { /* properties */ };
    
    // Act - Create document, transaction, and entries
    var createdDocument = await _documentService.CreateDocumentAsync(document, TEST_USER);
    // ... create transaction and entries
    
    // Validate transaction
    var isValid = await _transactionService.ValidateTransactionAsync(
        createdTransaction.Id, ledgerEntries);
        
    // Assert
    Assert.That(isValid, Is.True, "Transaction should be balanced");
}

This test:

  1. Creates a document for our inventory purchase
  2. Creates a transaction linked to that document
  3. Creates ledger entries (debiting Inventory, crediting Accounts Payable)
  4. Validates that the transaction is balanced (debits = credits)

Sale to Customer

CanRecordSaleToCustomer demonstrates recording a customer sale:

[Test]
public async Task CanRecordSaleToCustomer()
{
    // Similar pattern to inventory purchase, but with sale-specific entries
    // ...
    
    // Create ledger entries - a more complex transaction with multiple entries
    var ledgerEntries = new List<ILedgerEntry>
    {
        // Cash received
        // Sales revenue
        // Cost of goods sold
        // Reduce inventory
    };
    
    // Validate transaction
    // ...
}

This test is more complex, recording both the revenue side (debit Cash, credit Sales Revenue) and the cost side (debit Cost of Goods Sold, credit Inventory) of a sale.

Full Accounting Cycle Test

The CanExecuteFullAccountingCycle method ties everything together:

[Test]
public async Task CanExecuteFullAccountingCycle()
{
    // Run these in a defined order, with clean account setup first
    _accounts.Clear();
    _documents.Clear();
    _transactions.Clear();
    
    await SetupChartOfAccounts();
    
    // 1. Record inventory purchase
    await RecordPurchaseOfInventory();
    
    // 2. Record sale to customer
    await RecordSaleToCustomer();
    
    // 3. Record utility expense
    await RecordBusinessExpense();
    
    // 4. Create a payment to supplier
    await RecordPaymentToSupplier();
    
    // 5. Verify account balances
    await VerifyAccountBalances();
}

This test:

  1. Starts with a clean state
  2. Records a sequence of business operations
  3. Verifies the final account balances

Mock Account Balance Calculator

The MockAccountBalanceCalculator is a crucial part of our test that simulates how a real database would work:

public class MockAccountBalanceCalculator : AccountBalanceCalculator
{
    private readonly Dictionary<string, AccountDto> _accounts;
    private readonly Dictionary<Guid, List<LedgerEntryDto>> _ledgerEntriesByTransaction = new();
    private readonly Dictionary<Guid, decimal> _accountBalances = new();

    public MockAccountBalanceCalculator(
        Dictionary<string, AccountDto> accounts,
        Dictionary<string, ITransaction> transactions)
    {
        _accounts = accounts;
        
        // Create mock ledger entries for each transaction
        InitializeLedgerEntries(transactions);
        
        // Calculate account balances based on ledger entries
        CalculateAllBalances();
    }

    // Methods to initialize and calculate
    // ...
}

This class:

  1. Takes our accounts and transactions as inputs
  2. Creates a collection of ledger entries for each transaction
  3. Calculates account balances based on these entries
  4. Provides methods to query account balances and ledger entries

The InitializeLedgerEntries method creates a collection of ledger entries for each transaction:

private void InitializeLedgerEntries(Dictionary<string, ITransaction> transactions)
{
    // For inventory purchase
    if (transactions.TryGetValue("InventoryPurchase", out var inventoryPurchase))
    {
        var entries = new List<LedgerEntryDto>
        {
            // Create entries for this transaction
            // ...
        };
        _ledgerEntriesByTransaction[inventoryPurchase.Id] = entries;
    }
    
    // For other transactions
    // ...
}

The CalculateAllBalances method processes these entries to calculate account balances:

private void CalculateAllBalances()
{
    // Initialize all account balances to zero
    foreach (var account in _accounts.Values)
    {
        _accountBalances[account.Id] = 0m;
    }
    
    // Process each transaction's ledger entries
    foreach (var entries in _ledgerEntriesByTransaction.Values)
    {
        foreach (var entry in entries)
        {
            if (entry.EntryType == EntryType.Debit)
            {
                _accountBalances[entry.AccountId] += entry.Amount;
            }
            else // Credit
            {
                _accountBalances[entry.AccountId] -= entry.Amount;
            }
        }
    }
}

This approach closely mirrors how a real accounting system would work with a database:

  1. Ledger entries are stored in collections (similar to database tables)
  2. Account balances are calculated by processing all relevant entries
  3. The calculator provides methods to query this data (similar to a repository)

Balance Verification

The VerifyAccountBalances method uses our mock calculator to verify account balances:

private async Task VerifyAccountBalances()
{
    // Create mock balance calculator
    var mockBalanceCalculator = new MockAccountBalanceCalculator(_accounts, _transactions);
    
    // Verify individual account balances
    decimal cashBalance = mockBalanceCalculator.CalculateAccountBalance(
        _accounts["Cash"].Id, 
        _testDate.AddDays(15)
    );
    Assert.That(cashBalance, Is.EqualTo(-2750m), "Cash balance is incorrect");
    
    // ... verify other account balances
    
    // Also verify the accounting equation
    // ...
}

The Benefits of Our Collection-Based Approach

Our redesigned MockAccountBalanceCalculator offers several advantages:

  1. Data-Driven: All calculations are based on collections of data, not hardcoded values.
  2. Flexible: New transactions can be added easily without changing calculation logic.
  3. Maintainable: If transaction amounts change, we only need to update them in one place.
  4. Realistic: This approach closely mirrors how a real database-backed accounting system would work.
  5. Extensible: We can add support for more complex queries like filtering by date range.

The Goals of Our Integration Test

Our integration test serves several important purposes:

  1. Verify Module Integration: Ensures that the Document module and Chart of Accounts module work correctly together.
  2. Validate Business Workflows: Confirms that standard accounting workflows (purchasing, sales, expenses, payments) function as expected.
  3. Ensure Data Integrity: Verifies that all transactions maintain balance (debits = credits) and that account balances are accurate.
  4. Test Double-Entry Accounting: Confirms that our system properly implements double-entry accounting principles where every transaction affects at least two accounts.
  5. Validate Accounting Equation: Ensures that the fundamental accounting equation (Assets = Liabilities + Equity + (Revenues – Expenses)) remains balanced.

Conclusion

This integration test demonstrates the core functionality of our accounting system using a data-driven approach that closely mimics a real database. By simulating a retail business’s transactions and storing them in collections, we’ve created a realistic test environment for our double-entry accounting system.

The collection-based approach in our MockAccountBalanceCalculator allows us to test complex accounting logic without an actual database, while still ensuring that our calculations are accurate and our accounting principles are sound.

While this test uses in-memory collections rather than a database, it provides a strong foundation for testing the business logic of our accounting system in a way that would translate easily to a real-world implementation.

Repo

egarim/SivarErp: Open Source ERP

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Understanding the Document Module: Day 2 – The Foundation of a Financial Accounting System

Understanding the Document Module: Day 2 – The Foundation of a Financial Accounting System

Introduction

In financial accounting systems, the document module serves as the cornerstone upon which all other functionality is built. Just as physical documents form the basis of traditional accounting practices, the digital document module provides the foundation for recording, processing, and analyzing financial transactions. In this article, we’ll explore the structure and importance of the document module in a modern financial accounting system.

The Core Components

The document module consists of three essential components:

1. Documents

Documents represent the source records of financial events. These might include invoices, receipts, bank statements, journal entries, and various specialized financial documents like balance transfer statements and closing entries. Each document contains metadata such as:

  • Date of the document
  • Document number/reference
  • Description and comments
  • Document type classification
  • Audit information (who created/modified it and when)

Documents serve as the legal proof of financial activities and provide an audit trail that can be followed to verify the accuracy and validity of financial records.

2. Transactions

Transactions represent the financial impact of documents in the general ledger. While a document captures the business event (e.g., an invoice), the transaction represents how that event affects the company’s financial position. A single document may generate one or more transactions depending on its complexity.

Each transaction is linked to its parent document and contains:

  • Transaction date (which may differ from the document date)
  • Description
  • Reference to the parent document

Transactions bridge the gap between source documents and ledger entries, maintaining the relationship between business events and their financial representations.

3. Ledger Entries

Ledger entries are the individual debit and credit entries that make up a transaction. They represent the actual changes to account balances in the general ledger. Each ledger entry contains:

  • Reference to the parent transaction
  • Account identifier
  • Entry type (debit or credit)
  • Amount
  • Optional references to persons and cost centers for analytical purposes

Ledger entries implement the double-entry accounting principle, ensuring that for every transaction, debits equal credits.

Why This Modular Approach Matters

The document module’s structure offers several significant advantages:

1. Separation of Concerns

By separating documents, transactions, and ledger entries, the system maintains clear boundaries between:

  • Business events (documents)
  • Financial impacts (transactions)
  • Specific account changes (ledger entries)

This separation allows each layer to focus on its specific responsibilities without being overly coupled to other components.

2. Flexibility and Extensibility

The modular design allows for adding new document types without changing the core accounting logic. Whether handling standard invoices or specialized financial instruments, the same underlying structure applies, making the system highly extensible.

3. Robust Audit Trail

With documents serving as the origin of all financial records, the system maintains a complete audit trail. Every ledger entry can be traced back to its transaction and originating document, providing accountability and transparency.

4. Compliance and Reporting

The document-centric approach aligns with legal and regulatory requirements that mandate keeping original document records. This structure facilitates regulatory compliance and simplifies financial reporting.

Implementation Considerations

When implementing a document module, several design principles should be considered:

Interface-Based Design

Using interfaces like IDocument, ITransaction, and ILedgerEntry promotes flexibility and testability. Services operate against these interfaces rather than concrete implementations, following the Dependency Inversion Principle.

Immutability of Processed Documents

Once a document has been processed and its transactions recorded, changes should be restricted to prevent inconsistencies. Any modifications should follow proper accounting procedures, such as creating correction entries.

Versioning and Historical Records

The system should maintain historical versions of documents, especially when they’re modified, to preserve the accurate history of financial events.

Conclusion

The document module serves as the backbone of a financial accounting system, providing the structure and organization needed to maintain accurate financial records. By properly implementing this foundation, accounting systems can ensure data integrity, regulatory compliance, and flexible business operations.

Understanding the document module’s architecture helps developers and accountants alike appreciate the careful design considerations that go into building robust financial systems capable of handling the complexities of modern business operations.

Repo

egarim/SivarErp: Open Source ERP

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Building an Agnostic ERP System: Day 1 – Core Architecture

Building an Agnostic ERP System: Day 1 – Core Architecture

After returning home from an extended journey through the United States, Greece, and Turkey, I found myself contemplating a common challenge over my morning coffee. There are numerous recurring problems in system design and ORM (Object-Relational Mapping) implementation that developers face repeatedly.

To address these challenges, I’ve decided to tackle a system that most professionals are familiar with—an ERP (Enterprise Resource Planning) system—and develop a design that achieves three critical goals:

  1. Performance Speed: The system must be fast and responsive
  2. Technology Agnosticism: The architecture should be platform-independent
  3. Consistent Performance: The system should maintain its performance over time

Design Decisions

To achieve these goals, I’m implementing the following key design decisions:

  • Utilizing the SOLID design principles to ensure maintainability and extensibility
  • Building with C# and net9 to leverage its modern language features
  • Creating an agnostic architecture that can be reimplemented in various technologies like DevExpress XAF or Entity Framework

Day 1: Foundational Structure

In this first article, I’ll propose an initial folder structure that may evolve as the system develops. I’ll also describe a set of base classes and interfaces that will form the foundation of our system.

You can find all the source code for this solution in the designated repository.

The Core Layer

Today we’re starting with the core layer—a set of interfaces that most entities will implement. The system design follows SOLID principles to ensure it can be easily reimplemented using different technologies.

Base Interfaces

Here’s the foundation of our interface hierarchy:

  • IEntity: Core entity interface defining the Id property
  • IAuditable: Interface for entities with audit information
  • IArchivable: Interface for entities supporting soft delete
  • IVersionable: Interface for entities with effective dating
  • ITimeTrackable: Interface for entities requiring time tracking

Service Interfaces

To complement our entity interfaces, we’re also defining service interfaces:

  • IAuditService: Interface for audit-related operations
  • IArchiveService: Interface for archiving operations

 

Repo

egarim/SivarErp: Open Source ERP

Next Steps

In upcoming articles, I’ll expand on this foundation by implementing concrete classes, developing the domain layer, and demonstrating how this architecture can be applied to specific ERP modules.

The goal is to create a reference architecture that addresses the recurring challenges in system design while remaining adaptable to different technological implementations.

Stay tuned for the next installment where we’ll dive deeper into the implementation details of our core interfaces.

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This call/zoom will give you the opportunity to define the roadblocks in your current XAF solution. We can talk about performance, deployment or custom implementations. Together we will review you pain points and leave you with recommendations to get your app back in track

 

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