Properties of calculus in r-Complexity 2025

๐Ÿ“… 2026-01-26
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Existing methods for algorithmic complexity analysis exhibit expressive limitations in capturing both practical performance and asymptotic behavior, and lack a systematic study of transformations and operations between complexity classes. This work proposes the first axiomatic framework for r-Complexity calculus, formally integrating complexity theory with algebraic structures. Within this framework, fundamental properties such as reflexivity and transitivity are rigorously derived, and systematic rules for inter-class transformations and arithmetic operations are established. The approach significantly enhances the expressiveness and applicability of complexity analysis, while demonstrating the theoretical advantages of r-Complexity over the traditional Bachmannโ€“Landau notation system, thereby laying a foundation for novel applications in emerging computational contexts.

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๐Ÿ“ Abstract
This paper presents a series of general properties of the r-Complexity calculus, a complexity measurement for assessing the performance and asymptotic behaviour of real-world algorithms. This research describes characteristics such as reflexivity, transitivity, or symmetry and discusses several conversion rules between different classes of r-Complexity, as well as establishing fundamental arithmetic principles. The work also examines the behaviour of the addition property within this system and compares its characteristics with those frequently used in the traditional Bachmann-Landau notation. Through utilizing these properties, this research seeks to promote the exploration and development of novel applications for r-Complexity, as well as accelerating the adoption rate of calculus in this refined complexity model.
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Research questions and friction points this paper is trying to address.

r-Complexity
calculus
algorithm complexity
asymptotic behaviour
complexity measurement
Innovation

Methods, ideas, or system contributions that make the work stand out.

r-Complexity
complexity calculus
asymptotic behavior
Bachmann-Landau notation
algorithmic complexity
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R
Rares Folea
Department of Computer Science and Engineering, Faculty for Automatic Control and Computers, National University of Science and Technology Politehnica Bucharest, Romania and Doctoral School of Engineering and Applications of Lasers and Accelerators (S.D.I.A.L.A.)
Emil Slusanschi
Emil Slusanschi
University POLITEHNICA of Bucharest
High Performance ComputingComputer Systems ArchitectureAutomatic DifferentiationWireless Sensor and Actuator Networks