Abstract
This paper presents a new programming paradigm named Notification Oriented Paradigm (NOP) and analyses performance aspects of NOP programs by means of an experiment. NOP provides a new manner to conceive, structure, and execute software, which allows better performance, causal-knowledge organization, and entity decoupling than standard solutions based upon current paradigms. These paradigms are essentially Imperative Paradigm (IP) and Declarative Paradigm (DP). In short, DP solutions are considered easier to use than IP solutions thanks to the concept of high-level programming. However, they are considered slower to execute and lesser flexible to program than IP. Anyway, both paradigms present similar drawbacks like causal-evaluation redundancies and strongly coupled entities, which decrease software performance and processing distribution feasibility. These problems exist due to an orientation to monolithic inference mechanism based upon sequential evaluation by means of searches over passive computational entities. NOP proposes another manner to structure software and make its inferences, which is based upon small, smart, and decoupled collaborative entities whose interaction happen by means of precise notifications. This paper discusses NOP as a paradigm and presents certain comparison of NOP against IP. Actually, performance is evaluated by means of IP and NOP programs with respect to a same application, which allow demonstrating NOP superiority.
Highlights
This section mentions drawbacks from current programming paradigms, introduces Notification Oriented Paradigm as a new solution, and presents paper objectives.1.1
This paper presents a new programming paradigm named Notification Oriented Paradigm (NOP) and analyses performance aspects of NOP programs by means of an experiment
The evaluation process is based on monolithic inference-process that performs some sort of search over passive fact-bases and causal-bases, which generates a set of deficiencies
Summary
The computational processing power has grown each year and the tendency is that technology evolution contributes to the creation of still faster processing technologies [1] Even if this scenario is positive in terms of pure technology evolution, in general it does not motivate information-technology professionals to optimize the use of processing resources when they develop software [2]. The distribution is itself a problem once, under different conditions, it could entail a set of (related) problems, such as complex load balancing, communication excess, and hard fine-grained distribution [3,14,15,18] In this context, a problem raises from the fact that usual programming languages (e.g. Pascal, C/C++, and Java) present no real facilities to develop optimized and really distributable code, in terms of finegrained decoupling of code [2,3,18,19]. This happens due to the structure and execution nature imposed by their paradigm [6,8,9]
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