Principles and Implementation of Serialization and Deserialization

1. Basic Concepts and Functions
Serialization is the process of converting objects in memory into a storable or transmittable format (such as byte stream, JSON, XML), while deserialization is the reverse process of converting this format back into memory objects. Main functions include:

• Data Persistence: Saving objects to files or databases
• Network Transmission: Cross-process communication in distributed systems
• Deep Copy Implementation: Creating object copies via serialization/deserialization

2. Core Implementation Principles
(1) Metadata Collection
Systems need to collect complete object information, including:

• Structural information such as class names, field names, modifiers
• Data information such as field values and reference relationships
• Type inheritance relationships (parent class fields must also be processed)

(2) Data Conversion Strategies
Different processing methods based on field types:

• Basic types (int/string, etc.): Direct conversion to bytes or text
• Reference types: Recursive processing of the entire object graph
• Circular references: Avoid infinite recursion through reference identifiers

(3) Byte Stream Organization
Typical binary serialization format includes:

[Header metadata][Field value data][End marker]

Example: The serialized structure of a Person object might include:

• 4-byte class name length + class name bytes
• Type markers + field values for each field
• 0xFF end identifier

3. Text Serialization Implementation (Using JSON as Example)
(1) Basic Type Mapping Rules

// Serialization process
public String serialize(Object obj) {
    if (obj instanceof String) return "\"" + escape((String)obj) + "\"";
    if (obj instanceof Number) return obj.toString();
    if (obj instanceof Boolean) return obj.toString();
    if (obj instanceof List) return serializeList((List)obj);
    // Recursive processing for object types
}

(2) Object Graph Traversal Algorithm
Using depth-first traversal:

def serialize_obj(obj, visited):
    if id(obj) in visited:  # Handling circular references
        return {"$ref": visited[id(obj)]}
    
    visited[id(obj)] = generate_id()
    result = {}
    for field in get_fields(obj):
        value = get_field_value(obj, field)
        result[field] = serialize(value, visited)  # Recursive call
    return result

4. Binary Serialization Optimization Techniques
(1) Byte Alignment Optimization
Reordering fields by type length to reduce memory gaps:
Original order: boolean(1) + int(4) → May produce 3-byte padding
Optimized order: int(4) + boolean(1) → Only 1-byte padding

(2) Variable-Length Integer Encoding
Using Varint encoding for integers:

• Values less than 128: Represented with 1 byte
• Values greater than 128: Represented with multiple bytes (highest bit as continuation marker)

(3) String Encoding Optimization
Selecting encoding schemes by detecting string content:

• Pure ASCII characters: Using single-byte encoding
• Containing Unicode: UTF-8 encoding
• High-frequency strings: Establishing string pools for index reuse

5. Version Compatibility Handling
(1) Field Extension Strategy
Achieving forward compatibility through field tags:

message Person {
  required int32 id = 1;
  optional string email = 2;  // New fields set as optional
}

(2) Data Migration Solutions
When deserializing data from older versions:

• New fields: Set to default values or null
• Deprecated fields: Ignore excess data
• Type changes: Type adaptation through converters

6. Performance Optimization Practices
(1) Pre-generating Serialization Code
Replacing reflection with code generation at runtime:

// Generating serializers at compile time
public class PersonSerializer {
    public byte[] serialize(Person p) {
        ByteBuffer buf = ByteBuffer.allocate(100);
        buf.putInt(p.id);        // Direct field access
        writeString(buf, p.name); // Method inlining optimization
        return buf.array();
    }
}

(2) Memory Pool Technology
Reusing serialization buffers to avoid frequent memory allocation:

• Initialize fixed-size byte array pools
• Expand buffer size as needed
• Reset buffer after serialization completion (not release)

Through the above layered implementation, serialization systems can ensure data integrity while meeting the requirements of high-performance scenarios, serving as foundational supporting technology for modern distributed systems.