In a distributed system, Distributed Transaction Coordinator (DTC) can be used alongside Entity Framework to handle transaction management efficiently. DTC is a Microsoft Windows service that coordinates transactions that span multiple resource managers, ensuring the atomicity, consistency, isolation, and durability (ACID) properties of distributed transactions. It helps manage transactions across different databases or systems in a distributed environment.

Eager loading involves retrieving related data along with the main data in a single query, reducing the number of database trips. This is beneficial for large datasets as it minimizes database round-trips, enhancing performance. Lazy loading, on the other hand, delays the retrieval of related data until it's specifically requested, potentially resulting in numerous individual database calls.

The [StringLength] data annotation is used to specify the maximum length of a string property in an Entity Type in Entity Framework. This allows developers to enforce constraints on string lengths in the database schema.

Entity Framework uses Table Per Type (TPT) inheritance mapping to map each type to its own table in the database. This means that each subclass gets its own table, and the base class gets a table to hold shared properties. This approach allows for better normalization and reduces redundancy in the database schema.

In Entity Framework, Shadow Properties play a vital role in mapping properties that are not defined in the entity class. They allow mapping to database columns without corresponding properties in the entity class, useful for scenarios like auditing or data migration.

To map a property in a complex type to a specific column in the database in Entity Framework, you use the Column() method. This method lets you specify the column name for the property.

In Entity Framework, to configure a property as a primary key using Fluent API, you use the PrimaryKey() method. This method allows you to specify the primary key for the entity.

Data Annotations in Entity Framework provide a way to configure entity mapping directly within the model classes using attributes. They allow developers to specify database mappings, define relationships, and set constraints such as primary keys and indexes. While Data Annotations offer a convenient way to configure aspects of the data model, they also provide a means for validating entity properties, making them versatile tools for defining and enforcing data integrity rules in Entity Framework applications.

Complex Types in Entity Framework represent non-entity objects that don't have their own identity and lifecycle. Unlike Entity Types, Complex Types can't be mapped to tables and don't have keys. They are typically used to represent parts of an entity or to encapsulate reusable groups of properties. Understanding the differences between Entity Types and Complex Types is essential for designing efficient and maintainable data models in Entity Framework.

In Entity Framework, when an entity has a complex type property, you can use the Fluent API to specify the configuration of the complex type. This involves defining the mapping and any additional configuration such as column names, data types, and constraints. This ensures that the complex type is properly configured in the database schema.

The correct option is Option 2: CompositeKey. This method in Entity Framework's Fluent API is specifically designed to configure a composite primary key for an entity type. A composite primary key consists of more than one property that uniquely identifies a record in a table. By using CompositeKey, you can specify multiple properties to form the composite key, ensuring uniqueness across the combination of these properties.

The correct option is Option 3: IsRowVersion(). This method configures a property to be used as a concurrency token in Entity Framework. It marks the property as a row version, indicating that it should be included in concurrency checks when updating records in the database. This ensures that conflicting updates are detected and resolved appropriately, maintaining data integrity.