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Digital Accessibility for People with Special Needs:
Methodology, Conceptual Models and Innovative EcoSystems


Performance of Lambda Expressions in High Level Programming Languages

Autor(s)

Todor Todorov, Nikolay Noev

Published at

TEM Journal. Volume 12, Issue 4, Pages 2235-2240, ISSN 2217-8309, DOI: https://doi.org/10.18421/TEM124-34, November 2023

Abstract

    Functional programming is a programming paradigm that is becoming increasingly popular among software developers. This is due in part to the rise of distributed systems and the need for more robust and scalable code. In the paper is presented an overview of the syntax and capabilities of Lambda expressions in three programming languages – C#, Java and Python. Performance of programming language constructions is an important research task. Some popular topics for investigation are comparison of programming languages efficiency in fields like bioinformatics or classification of Lambda expression usage and their productiveness. In the current study the performance of Lambda expressions is tested with three specific test cases and the results are compared to alternative technologies that could be used to solve similar problems. The results shows that speed performance of C# is the best from the compared languages and that List Comprehensions is the optimal method for collection filtering in Python.

Keywords

lambda expressions; programming languages; comparison of performance

Acknowledgement

    This research was funded by the National Science Fund of Bulgaria (scientific project “Digital Accessibility for People with Special Needs: Methodology, Conceptual Models and Innovative EcoSystems”), Grant Number KP06-N42/4, 08.12.2020.

Links

https://doi.org/10.18421/TEM124-34

https://www.temjournal.com/content/124/TEMJournalNovember2023_2235_2240.html

Cite as

Todorov, T.; Noev, N. (2023). Performance of Lambda Expressions in High Level Programming Languages. TEM Journal. Volume 12, Issue 4, Pages 2235-2240, ISSN 2217-8309, DOI: https://doi.org/10.18421/TEM124-34, November 20233

The publication presents research on the project