These articles delves into performance optimization for collections in .NET, covering topics like looping, sorting, and utilizing different types of objects. The author identified performance variations related to the object type in the collection and recommends conducting benchmark tests. All recommendations are specific to .NET 8.
Globalization is essential for application development and should be integrated from the start, not as an afterthought. It encompasses more than just text translation, including nuances of languages, cultures, and data formats. Proper implementation enhances performance and user experience worldwide, while neglecting it can lead to significant difficulties and costs later.
The article delves into the optimization of Enum value name retrieval in .NET, comparing three approaches. It demonstrates that one of these methods is 16.13 times more efficient, with no memory allocation.
Strings in .NET can severely impact performance if not managed properly. This guide explores string performance optimization, covering issues like concatenation, formatting, and memory allocation. It provides practical solutions using tools like StringBuilder and spans, offering benchmark-driven strategies to enhance application efficiency for developers dealing with strings.
Understanding the differences between reference types (classes) and value types (structs) is crucial for optimizing .NET application performance. This content offers benchmark-driven insights on when to use each type, emphasizing the impact of choice on execution efficiency. Mastering these concepts ensures high-performance code in your applications.
The article explores the performance implications of using LINQ for collection queries, finding that a conventional foreach() loop outperforms LINQ by 1.75 times in identifying items matching a given query. The conclusion suggests benchmarking to determine the optimal approach based on the nature of the query and elements being sought.
This article explores different methods of passing parameters into methods, including conventional, in operator, and ref readonly approaches, comparing their performance. Despite differences in syntax, benchmark results demonstrate similar performance among these methods.
The article explores the performance differences between passing parameters as arrays or using the params keyword in C#. Despite similarities in speed, the author recommends using the params keyword for its ease of use during function calls.
The post discusses alternative approaches to adding items to a collection using For() or ForEach() from the Task Parallel Library.
The article discusses the potential performance improvements gained by leveraging pattern matching in .NET. It contrasts a traditional method for rounding numbers with a more refined version employing pattern matching.
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