Strategies for Implementing Singleton Pattern to Prevent Resource Conflicts in Engineering Applications

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The Singleton pattern is a fundamental design approach used extensively in engineering applications to ensure that a class has only one instance throughout the application’s lifecycle, providing a controlled global point of access to it. This pattern was conceived to ensure a class has only one instance throughout the lifetime of a program, providing a global point of access to that instance. In engineering contexts where resource conflicts can occur—such as managing hardware interfaces, database connections, thread pools, or shared configurations—implementing the Singleton pattern effectively helps prevent resource conflicts and ensures system stability.

Understanding the Singleton Pattern in Depth

The Singleton Pattern solves two problems at the same time: ensuring that a class has just a single instance and providing a global access point to that instance. This dual purpose makes it particularly valuable in engineering applications where coordination and resource management are critical.

Core Principles of Singleton Implementation

The Singleton pattern restricts the instantiation of a class to a single object through several key mechanisms. To implement a singleton pattern, we have a private constructor to restrict instantiation of the class from other classes, a private static variable of the same class that is the only instance of the class, and a public static method that returns the instance of the class, which is the global access point for the outer world to get the instance of the singleton class.

This architectural approach guarantees that only one instance exists throughout the application’s lifecycle, preventing the creation of duplicate objects that could lead to resource conflicts or inconsistent states. All implementations of the Singleton have these two steps in common: making the default constructor private to prevent other objects from using the new operator with the Singleton class, and creating a static creation method that acts as a constructor. Under the hood, this method calls the private constructor to create an object and saves it in a static field. All following calls to this method return the cached object.

Why Singleton Matters in Engineering Applications

The most common reason for controlling how many instances a class has is to control access to some shared resource—for example, a database or a file. In engineering applications, this becomes even more critical when dealing with hardware interfaces, sensor data streams, or communication protocols where multiple instances could create conflicts or race conditions.

Singleton pattern is used for logging, drivers objects, caching, and thread pool. These use cases are particularly common in engineering software where consistent access to shared resources is essential for system reliability and performance.

Comprehensive Strategies for Implementing Singleton Pattern

Implementing the Singleton pattern correctly requires careful consideration of various approaches, each with its own advantages and trade-offs. The choice of implementation strategy depends on factors such as thread safety requirements, initialization timing, resource consumption, and the specific needs of your engineering application.

Lazy Initialization Strategy

Lazy initialization is one of the most popular approaches for implementing the Singleton pattern. Lazy initialization method to implement the singleton pattern creates the instance in the global access method. This strategy delays the creation of the singleton instance until it is actually needed, which can significantly conserve system resources, especially when the singleton manages expensive resources like database connections or hardware interfaces.

The primary advantage of lazy initialization is resource conservation. In most of the scenarios, singleton classes are created for resources such as File System, Database connections, etc. We should avoid the instantiation unless the client calls the getInstance method. This approach ensures that if the singleton is never used during a particular execution of the application, no resources are wasted on its creation.

However, lazy initialization comes with important considerations for multi-threaded environments. When it comes to multi-threaded systems, it can cause issues if multiple threads are inside the if condition at the same time. It will destroy the singleton pattern and both threads will get different instances of the singleton class. This makes thread safety a critical concern when implementing lazy initialization.

Eager Initialization Strategy

In eager initialization, the instance of the singleton class is created at the time of class loading. The drawback to eager initialization is that the method is created even though the client application might not be using it. This approach is simpler to implement and inherently thread-safe because the instance is created before any threads can access it.

Eager initialization is most appropriate when you know the singleton will definitely be used during the application’s execution and when the resource cost of creating the instance at startup is acceptable. If your singleton class is not using a lot of resources, this is the approach to use. For engineering applications with lightweight configuration managers or logging systems, eager initialization provides simplicity without significant overhead.

Thread-Safe Singleton Implementation

In multi-threaded engineering applications, ensuring thread safety is paramount. A simple way to create a thread-safe singleton class is to make the global access method synchronized so that only one thread can execute this method at a time. However, this approach can introduce performance bottlenecks if the getInstance method is called frequently.

A more sophisticated approach is double-checked locking, which minimizes synchronization overhead while maintaining thread safety. This implementation uses the double-checked locking pattern to ensure thread safety while maintaining performance. The pattern checks if the instance is null before acquiring a lock, and then checks again after acquiring the lock to ensure only one instance is created.

For modern C# applications, using Lazy<T> for automatic thread safety is the recommended approach in modern C# and eliminates the need for manual locking or synchronization primitives. This is a fundamental best practice for Singleton pattern implementations in C#.

Enum-Based Singleton (Java)

For Java-based engineering applications, the enum approach offers unique advantages. Joshua Bloch suggests the use of enum to implement the singleton design pattern as Java ensures that any enum value is instantiated only once in a Java program. This approach provides built-in serialization support and protection against reflection attacks.

The Enum Singleton pattern is the most robust and concise way to implement a singleton in Java. Many Java experts, including Joshua Bloch, recommend Enum Singleton as the best singleton implementation in Java. However, it’s not always suitable, especially if you need to extend a class or if lazy initialization is a strict requirement.

Bill Pugh Singleton (Static Inner Class)

The Bill Pugh Singleton implementation provides a perfect balance of lazy initialization, thread safety, and performance, without the complexities of some other patterns like double-checked locking. This approach uses a static inner class to hold the singleton instance, which is not loaded until the getInstance method is called, providing lazy initialization without explicit synchronization.

This implementation strategy is particularly well-suited for engineering applications that require both thread safety and lazy initialization without the performance overhead of synchronized methods. The Java class loader mechanism ensures thread safety automatically, making this approach both elegant and efficient.

Static Block Initialization

Static block initialization is similar to eager initialization, but the instance is created in a static block. It provides the ability to handle exceptions during instance creation, which is not possible with simple eager initialization. This approach is valuable in engineering applications where initialization might fail due to hardware unavailability, configuration errors, or resource constraints.

Best Practices to Prevent Resource Conflicts in Engineering Applications

Implementing the Singleton pattern correctly is only part of the solution. To truly prevent resource conflicts in engineering applications, you must follow established best practices that address common pitfalls and ensure robust, maintainable code.

Limit Singleton Scope and Responsibility

Keep the singleton’s scope limited to where it is genuinely necessary, reducing unintended side effects and tight coupling. While powerful, the Singleton Pattern should be used judiciously. Overuse can lead to tight coupling and make unit testing more challenging. In engineering applications, this means carefully evaluating whether a class truly needs to be a singleton or whether dependency injection might be a better alternative.

Make the Singleton class final to prevent subclassing. This ensures that no one can create a derived class that might introduce additional instances. This practice is particularly important in engineering applications where system integrity depends on having exactly one instance of critical components.

Implement Proper Synchronization Mechanisms

Use appropriate synchronization mechanisms to prevent race conditions during instance creation in multi-threaded environments. Thread Safety can be designed to work correctly in multithreaded environments. The choice of synchronization mechanism depends on your programming language and specific requirements.

For engineering applications that involve real-time data processing or concurrent hardware access, thread safety is not optional—it’s essential. In multi-threaded environments, Singletons can introduce concurrency problems. Race conditions may occur if multiple threads try to access or modify the Singleton instance simultaneously.

Maintain Stateless or Immutable Singletons

Keep Singletons stateless or immutable whenever possible. This is a critical best practice for Singleton pattern implementations. Stateless singletons avoid the problems associated with shared mutable state, which can lead to difficult-to-debug issues in multi-threaded engineering applications.

When state is necessary, ensure that all state modifications are properly synchronized and that the singleton provides thread-safe access methods. This is particularly important for engineering applications that manage hardware state, sensor readings, or configuration data that might be accessed by multiple threads simultaneously.

Proper Resource Management and Cleanup

Ensure that resources managed by the singleton are properly released or reset when necessary. In engineering applications, this might include closing hardware connections, releasing file handles, or cleaning up network sockets. Managing the lifecycle of Singleton instances, especially in complex applications or frameworks, can be tricky. Initialization, destruction, and resource management need careful consideration.

Consider implementing proper cleanup methods that can be called when the application shuts down or when the singleton needs to be reset. Handle initialization errors in the constructor and provide clear error messages. Lazy<T> caches exceptions, so initialization failures are thrown on every access to Instance. Consider using factory methods or dependency injection if initialization might fail frequently.

Enable Testability Through Interfaces

Expose an interface so consumers can be tested with mocks instead of the real Singleton. This avoids relying on the actual instance in unit tests. This practice is crucial for engineering applications where unit testing is essential for ensuring system reliability and safety.

By programming to an interface rather than the concrete singleton class, you enable dependency injection in tests while still maintaining the singleton behavior in production code. Use interfaces and allow dependency injection as an alternative to the Singleton instance. This allows mocking in tests while still providing the Singleton instance for production code.

Rigorous Testing and Validation

Rigorously test singleton implementations to identify potential conflicts or race conditions. Difficult to unit test due to shared global state. Despite these challenges, thorough testing is essential for engineering applications where failures can have serious consequences.

Testing strategies should include:

  • Concurrency Testing: Verify that the singleton behaves correctly under concurrent access from multiple threads
  • Initialization Testing: Ensure that initialization succeeds under various conditions and fails gracefully when resources are unavailable
  • Resource Leak Testing: Confirm that resources are properly released and that no memory leaks occur
  • State Consistency Testing: Validate that the singleton maintains consistent state across different access patterns
  • Integration Testing: Test the singleton in the context of the larger system to identify unexpected interactions

Consider Dependency Injection as an Alternative

For new projects, prefer dependency injection with singleton lifetime over implementing the Singleton pattern directly. Dependency injection provides better testability and loose coupling while still ensuring a single instance when needed. Modern engineering applications can benefit from dependency injection frameworks that provide singleton-like behavior without the drawbacks of the traditional Singleton pattern.

This pattern involves passing dependencies (objects or services) into a class rather than the class creating or locating them itself. This approach reduces coupling and makes the code more maintainable and testable, which is particularly valuable in large-scale engineering applications.

Real-World Engineering Applications of Singleton Pattern

Understanding how the Singleton pattern is applied in real-world engineering scenarios helps illustrate its practical value and the specific problems it solves. Let’s explore several common use cases where the Singleton pattern prevents resource conflicts and ensures system stability.

Database Connection Management

Database Connection Pools help manage and reuse database connections efficiently. A Singleton can ensure that only one pool is created and used throughout the application. In engineering applications that collect sensor data, log events, or store configuration information, managing database connections efficiently is critical for performance and resource utilization.

A common example of the Singleton Pattern in action is database connection pooling. In large applications, multiple components often need to access the database. By using the Singleton Pattern, a shared connection pool is managed, ensuring that only one instance of the connection pool exists. This significantly reduces the overhead of creating and managing multiple connections, improving both performance and resource utilization.

Hardware Interface Management

In engineering applications, hardware interfaces often require exclusive access to prevent conflicts. Whether managing serial ports, USB devices, GPIO pins, or specialized instrumentation, the Singleton pattern ensures that only one instance controls the hardware resource. This prevents multiple parts of the application from attempting simultaneous access, which could lead to corrupted data, hardware errors, or system crashes.

For example, a singleton class managing a CAN bus interface in an automotive application ensures that all communication with vehicle systems goes through a single, coordinated point. This prevents message collisions and ensures proper sequencing of commands.

Logging Systems

Logging is a common real-world use case for singletons, because all objects that wish to log messages require a uniform point of access and conceptually write to a single source. In engineering applications, consistent logging is essential for debugging, monitoring system health, and analyzing performance.

Logger Classes: Many logging frameworks use the Singleton pattern to provide a global logging object. This ensures that log messages are consistently handled and written to the same output stream. This prevents issues like file corruption from concurrent writes or inconsistent log formatting across different application components.

Configuration Management

Configuration Manager: Centralizes application settings and properties. Engineering applications often have complex configuration requirements, including hardware parameters, communication settings, calibration data, and operational modes. A singleton configuration manager ensures that all components access the same configuration data and that changes are immediately visible throughout the application.

Imagine you’re developing a Configuration Manager for a distributed application. Its job is to read settings from a configuration file or database and make them available to different parts of your application. However, without a Singleton, you’re opening the door to a world of trouble: Inconsistent data: Multiple instances might read from the configuration at different times, leading to conflicting settings. Resource contention: Several instances trying to access the same file or database could create performance bottlenecks.

Thread Pool Management

Thread Pools manage a collection of worker threads. A Singleton ensures that the same pool is used throughout the application, preventing resource overuse. In engineering applications that perform parallel processing of sensor data, concurrent hardware operations, or distributed computations, proper thread pool management is essential for optimal performance and resource utilization.

A singleton thread pool prevents the creation of excessive threads, which could overwhelm the system and degrade performance. It also ensures that thread lifecycle management is centralized and consistent across the application.

Cache Management

Cache Objects: In-memory caches are often implemented as Singletons to provide a single point of access for cached data across the application. Engineering applications frequently cache sensor readings, calculation results, or frequently accessed configuration data to improve performance. A singleton cache manager ensures that all components share the same cached data, preventing memory waste from duplicate caches and ensuring cache coherency.

Device Driver Management

Device drivers in engineering applications often need to be singletons to ensure exclusive access to hardware resources. Whether controlling motors, reading sensors, or communicating with external devices, a singleton driver class prevents conflicts that could arise from multiple instances attempting to control the same hardware.

For example, a singleton driver for a stepper motor controller ensures that motion commands are properly sequenced and that the motor’s state is accurately tracked. Multiple instances could send conflicting commands, leading to erratic behavior or hardware damage.

Understanding the Drawbacks and When to Avoid Singleton

While the Singleton pattern offers significant benefits for preventing resource conflicts in engineering applications, it’s important to understand its limitations and potential drawbacks. Due to its potential drawbacks and violations of SOLID principles, the Singleton is sometimes regarded as an Anti-Pattern.

Global State and Hidden Dependencies

Singleton introduces global state into your application, which can make it difficult to manage and test. Changes to the Singleton instance affect the entire application, potentially leading to unintended consequences. This is particularly problematic in large engineering applications where understanding the flow of data and dependencies is crucial for maintenance and debugging.

Classes depending on a Singleton instance often have hidden dependencies, as they rely on global access rather than explicit dependencies through constructor injection or other patterns. This makes it harder to understand what a class actually depends on and can lead to unexpected behavior when components are reused in different contexts.

Testing Challenges

Due to their global nature, Singletons can be challenging to unit test. The shared state maintained by singletons can cause tests to interfere with each other, making it difficult to achieve proper test isolation. This is particularly problematic in engineering applications where thorough testing is essential for ensuring system reliability and safety.

This increased coupling can introduce difficulties with unit testing. Tests that depend on singletons may require complex setup and teardown procedures to ensure a clean state between test runs, increasing test complexity and maintenance burden.

Tight Coupling and Reduced Flexibility

Code that relies on Singletons can become tightly coupled with the Singleton instance. This makes it harder to replace or modify components without affecting other parts of the system. In engineering applications that evolve over time or need to support different hardware configurations, this tight coupling can significantly increase maintenance costs.

Singleton can create tight coupling since many classes depend on a global instance. This coupling makes it difficult to swap implementations, which can be problematic when you need to support different hardware variants or when migrating to new technologies.

Scalability Concerns

As the application grows, reliance on Singletons can hinder scalability. Introducing multiple instances or distributing components across different servers becomes more complicated. This is particularly relevant for engineering applications that may need to scale from single-device systems to distributed architectures.

In distributed systems, the concept of a “single instance” becomes problematic. Each process or server may need its own instance, which contradicts the fundamental principle of the Singleton pattern. This can require significant refactoring when scaling an application from a single-process to a distributed architecture.

When to Avoid Singleton Pattern

Consider avoiding the Singleton pattern in these scenarios:

  • When testability is paramount: If your engineering application requires extensive unit testing with high isolation between tests, dependency injection may be a better choice
  • When you need multiple instances in the future: If there’s any possibility that you might need multiple instances (e.g., supporting multiple hardware devices of the same type), avoid Singleton from the start
  • When the class has significant mutable state: Singletons with mutable state are difficult to manage safely in multi-threaded environments
  • When building distributed systems: The Singleton pattern doesn’t translate well to distributed architectures where multiple processes or servers are involved
  • When following strict SOLID principles: Singleton can violate the Single Responsibility Principle by managing both its business logic and its own lifecycle

Advanced Implementation Considerations for Engineering Applications

Beyond basic implementation strategies, engineering applications often require additional considerations to ensure robust and reliable singleton behavior in complex, real-world environments.

Serialization and Deserialization

Sometimes in distributed systems, we need to implement Serializable interface in the singleton class so that we can store its state in the file system and retrieve it at a later point in time. However, standard serialization can break the singleton property by creating a new instance during deserialization.

To maintain singleton behavior with serialization, implement the readResolve method to return the existing singleton instance instead of creating a new one. This ensures that deserialization doesn’t violate the single-instance guarantee, which is crucial for engineering applications that persist state across sessions or distribute state across network boundaries.

Reflection and Security Considerations

In languages that support reflection, it’s possible to bypass the private constructor and create multiple instances of a singleton class. To overcome this situation with Reflection, Joshua Bloch suggests the use of enum to implement the singleton design pattern as Java ensures that any enum value is instantiated only once in a Java program.

For engineering applications where security is a concern, consider implementing additional safeguards against reflection attacks. This might include throwing exceptions from the constructor if an instance already exists, or using enum-based implementations that are inherently protected against reflection.

Memory Management and Cleanup

Engineering applications often run for extended periods and must manage resources carefully to avoid memory leaks or resource exhaustion. Singleton instances that hold references to large data structures or external resources need proper cleanup mechanisms.

Consider implementing:

  • Explicit cleanup methods: Provide methods to release resources when they’re no longer needed
  • Weak references: For cache-like singletons, use weak references to allow garbage collection when memory is needed
  • Resource pooling: Instead of holding resources permanently, implement pooling mechanisms that can grow and shrink based on demand
  • Shutdown hooks: Register shutdown hooks to ensure proper cleanup when the application terminates

Performance Optimization

In performance-critical engineering applications, the overhead of singleton access can become significant if the getInstance method is called frequently. Consider these optimization strategies:

  • Minimize synchronization overhead: Use double-checked locking or lock-free algorithms where appropriate
  • Cache the instance reference: In hot code paths, cache the singleton reference locally rather than calling getInstance repeatedly
  • Avoid unnecessary initialization: Defer initialization of expensive resources until they’re actually needed
  • Profile and measure: Use profiling tools to identify if singleton access is actually a bottleneck before optimizing

Error Handling and Resilience

Engineering applications must handle errors gracefully, especially during singleton initialization. Consider these error handling strategies:

  • Fail-fast initialization: Detect initialization errors early and provide clear error messages
  • Retry mechanisms: For transient failures (e.g., temporary hardware unavailability), implement retry logic with exponential backoff
  • Fallback behavior: Provide degraded functionality when the singleton cannot be fully initialized
  • Health monitoring: Implement health check methods that can detect if the singleton is in a valid state

Singleton Pattern in Different Programming Languages

The implementation details of the Singleton pattern vary across programming languages due to differences in language features, threading models, and memory management. Understanding these language-specific considerations is important for engineering applications that may use multiple languages or need to port code between platforms.

Java Singleton Implementation

Singleton pattern restricts the instantiation of a class and ensures that only one instance of the class exists in the Java Virtual Machine. The singleton class must provide a global access point to get the instance of the class. Java offers several implementation approaches, each with different trade-offs.

The Bill Pugh approach using a static inner class is often considered the best balance of simplicity, thread safety, and lazy initialization for Java applications. The enum approach provides the strongest guarantees against reflection and serialization attacks, making it ideal for security-critical engineering applications.

C++ Singleton Implementation

C++ implementations must carefully manage memory and ensure proper destruction of the singleton instance. The Meyers Singleton (using a static local variable) provides thread-safe initialization in C++11 and later, with automatic destruction when the program exits.

For engineering applications in C++, consider using smart pointers to manage the singleton instance lifetime and ensure proper cleanup. Be aware of the static initialization order fiasco when singletons depend on other static objects.

C# Singleton Implementation

The most important best practice for Singleton pattern implementations in C# is using Lazy<T> for automatic thread safety. The Lazy<T> class provides built-in thread-safe lazy initialization without requiring manual synchronization code.

C# also supports static constructors, which provide a simple way to implement eager initialization with guaranteed thread safety. For engineering applications using .NET, consider leveraging dependency injection containers that provide singleton lifetime management.

Python Singleton Implementation

Python offers several approaches to implementing singletons, including metaclasses, decorators, and module-level instances. The simplest approach is often to use a module-level instance, since Python modules are singletons by nature.

For engineering applications in Python, be aware of the Global Interpreter Lock (GIL) and its implications for thread safety. While the GIL provides some protection, explicit synchronization may still be necessary for complex initialization logic.

Monitoring and Debugging Singleton Implementations

Engineering applications require robust monitoring and debugging capabilities to ensure system reliability. Singleton implementations should include features that facilitate troubleshooting and performance analysis.

Logging and Diagnostics

Implement comprehensive logging in singleton classes to track:

  • Instance creation: Log when the singleton instance is created, including timing and initialization parameters
  • Access patterns: Track how frequently the singleton is accessed and from which components
  • State changes: Log significant state changes to help diagnose unexpected behavior
  • Error conditions: Capture detailed information about initialization failures or runtime errors
  • Resource usage: Monitor memory consumption, connection counts, or other resource metrics

Performance Metrics

For performance-critical engineering applications, instrument singleton classes to collect metrics such as:

  • Initialization time: Measure how long it takes to create and initialize the singleton
  • Access latency: Track the time required to access the singleton instance
  • Contention metrics: Monitor thread contention when accessing synchronized singletons
  • Resource utilization: Track memory, CPU, or I/O resources consumed by the singleton

Debugging Tools and Techniques

Develop debugging aids specifically for singleton classes:

  • Instance verification: Provide methods to verify that only one instance exists
  • State inspection: Implement methods to dump the current state for debugging purposes
  • Thread safety validation: Use thread sanitizers or similar tools to detect race conditions
  • Dependency tracking: Maintain information about which components are using the singleton

Migration Strategies: Moving Away from Singleton

As engineering applications evolve, you may find that a singleton implementation no longer meets your needs. Perhaps you need to support multiple instances, improve testability, or reduce coupling. Migrating away from the Singleton pattern requires careful planning to avoid breaking existing functionality.

Gradual Refactoring Approach

Rather than attempting a complete rewrite, consider a gradual refactoring approach:

  1. Extract an interface: Define an interface that represents the singleton’s functionality
  2. Introduce dependency injection: Modify classes to accept the interface through constructor injection rather than accessing the singleton directly
  3. Create a factory or provider: Implement a factory that can provide either the singleton instance or alternative implementations
  4. Update call sites incrementally: Gradually update code to use dependency injection rather than direct singleton access
  5. Remove singleton behavior: Once all call sites are updated, remove the singleton enforcement and allow multiple instances

Maintaining Backward Compatibility

During migration, maintain backward compatibility by keeping the singleton access method available while introducing new dependency injection mechanisms. This allows different parts of the application to migrate at their own pace without breaking existing functionality.

Use deprecation warnings to signal that direct singleton access is discouraged, guiding developers toward the new approach while allowing time for migration.

External Resources for Further Learning

To deepen your understanding of the Singleton pattern and its application in engineering contexts, consider exploring these valuable resources:

Conclusion

The Singleton pattern remains a valuable tool for preventing resource conflicts in engineering applications when applied judiciously and implemented correctly. When managing shared resources such as database connections, a Singleton can ensure that only one instance is used, preventing resource conflicts and reducing overhead. By ensuring a single, well-managed instance of critical components, engineers can enhance system stability and reliability across various resource-critical contexts.

Success with the Singleton pattern requires careful attention to several key factors: choosing the appropriate implementation strategy for your specific use case, ensuring thread safety in multi-threaded environments, maintaining proper resource management and cleanup, enabling testability through interfaces and dependency injection, and understanding when the pattern is appropriate versus when alternatives would be better.

Always be mindful of thread safety, use lazy initialization, and consider dependency injection to enhance the flexibility and maintainability of your codebase. Modern engineering applications can often benefit from dependency injection frameworks that provide singleton-like behavior without the traditional drawbacks of the Singleton pattern.

Remember that while powerful, the Singleton Pattern should be used judiciously. Overuse can lead to tight coupling and make unit testing more challenging. Evaluate each potential use case carefully, considering whether the benefits of guaranteed single-instance behavior outweigh the costs of reduced flexibility and testability.

By following the strategies and best practices outlined in this article, you can implement robust singleton patterns that prevent resource conflicts, ensure system stability, and maintain code quality in your engineering applications. Whether managing hardware interfaces, database connections, logging systems, or configuration data, the Singleton pattern—when properly implemented—provides a proven solution for coordinating access to shared resources and preventing the conflicts that can arise from multiple instances.