How do you measure and optimize the garbage collection performance of your OOD application?

Garbage collection (GC) is the process of reclaiming memory from objects that are no longer used by your application. GC can affect the performance, responsiveness, and scalability of your object-oriented design (OOD) application, especially if you create and dispose of many objects frequently. In this article, you will learn how to measure and optimize the GC performance of your OOD application using some common tools and techniques.

1 GC Basics

GC is a feature of many programming languages, such as Java, C#, and Python, that automatically manages memory allocation and deallocation for objects. GC frees the developer from manually managing memory, but it also introduces some overhead and unpredictability. GC typically runs in the background, but it can pause the application execution when it needs to collect and compact the memory. The frequency and duration of these pauses depend on the GC algorithm, the heap size, the allocation rate, and the live set size.

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2 GC Metrics

To measure the GC performance of your OOD application, you need to collect metrics that indicate how often, how long, and how much GC is happening. These metrics include GC time, GC count, GC throughput, GC pause time, GC efficiency, and GC latency. You can utilize various tools to collect and analyze these metrics, such as Visual Studio, JConsole, GCViewer, or PerfView. Collecting these metrics will help you understand the performance of your OOD application and optimize it accordingly.

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3 GC Tuning

To optimize the GC performance of your OOD application, you need to tune parameters that affect how the GC works. Heap size is one of these parameters, which you can adjust to balance between GC frequency and pause time. A larger heap size yields less frequent GC but longer pause time, while a smaller heap size means more frequent GC but shorter pause time. Additionally, you can choose between different GC algorithms, such as serial, parallel, concurrent, or generational, depending on the characteristics of your application. Moreover, GC options are flags or settings that control the behavior of the GC algorithm. Through trial and error, benchmarking, or profiling you can find the optimal combination of these parameters for your OOD application.

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4 OOD Principles

In addition to tuning GC parameters, you can improve the GC performance of your OOD application by following certain OOD principles that reduce memory pressure and improve memory efficiency. Encapsulation hides the implementation details of an object from other objects, while inheritance reuses the common behavior and state of an object in its subclasses. Polymorphism allows an object to behave differently depending on its type or context, and abstraction simplifies the representation of an object by focusing on its essential features. You can use design patterns, refactoring, or code analysis to apply these principles to your OOD application.

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Paulo Zëmek

Software Engineer - I used talk to computers and they understood me even without AI, we just spoke the same language... now that they got smarter we are so in-sync that sometimes it feels we talk to each-other mentally!
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The principles listed (like encapsulation, inheritance, polymorphism and abstraction) have absolutely nothing to do with garbage collection. Bad encapsulation? It is easier for users to change important states of my objects and cause a crash, but good or bad encapsulation will not affect the chances of an object being collected or not. Inheritance and Polymorphism? If I literally copy the common part of a class to create two variants (instead of using inheritance and polymorphism)... the total number of objects (not classes) will be the same. Probably they would have the same object size in memory, and the need for GC will remain the same.

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5 Code Optimization

Optimizing the GC performance of your OOD application can be achieved by optimizing your code to reduce the creation and disposal of objects. To do this, use value types instead of reference types when possible, as value types are stored on the stack or embedded in other objects, and do not require GC. Reuse objects from object pools or caches instead of creating new ones, as this reduces the allocation rate and the live set size of your objects. Implement lazy initialization or deferred execution to delay the creation of objects until they are actually used, and avoid creating objects that are never used. Lastly, use weak references or soft references to hold objects that are not essential or can be recreated, so that the GC can collect them if they are not strongly reachable. Code reviews, testing, or debugging can help you identify and implement these techniques in your code.

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Paulo Zëmek

Software Engineer - I used talk to computers and they understood me even without AI, we just spoke the same language... now that they got smarter we are so in-sync that sometimes it feels we talk to each-other mentally!
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Without more explanation, the use of Weak References is actually a bad advice, especially depending on how they are used, as this might cause a situation where an object is created, used some times, then collected at the next GC... some seconds later, created again, used some times, collected again at next GC, which is exactly the kind of problem we should try to avoid.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How do you measure and optimize the garbage collection performance of your OOD application?

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1 GC Basics

2 GC Metrics

3 GC Tuning

4 OOD Principles

5 Code Optimization

6 Here’s what else to consider

Object Oriented Design

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