Towards the most robust way of assigning numerical degrees to ordered labels, with possible applications to dark matter and dark energy

Kosheleva, Olga; Kreinovich, Vladik; Escobar, Martha Osegueda; Kato, Kimberly

doi:10.1109/nafips.2016.7851617

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Main Idea Behind the New Empirically Successful Code Quality1

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“…, c n ) that satisfy the property (2). This mean value is known (see, e.g., [1,2,4,6,7]), and it is equal to c i = i n + 1 .…”

Section: Main Idea Behind the New Empirically Successful Code Qualitymentioning

confidence: 99%

Theoretical Explanation of Recent Empirically Successful Code Quality Metrics

Kreinovich¹,

Masmali²,

Nguyen³

et al. 2020

JACIII

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Millions of lines of code are written every day, and it is not practically possible to perfectly thoroughly test all this code on all possible situations. In practice, we need to be able to separate codes which are more probable to contain bugs – and which thus need to be tested more thoroughly – from codes which are less probable to contain flaws. Several numerical characteristics – known as code quality metrics – have been proposed for this separation. Recently, a new efficient class of code quality metrics have been proposed, based on the idea to assign consequent integers to different levels of complexity and vulnerability: we assign 1 to the simplest level, 2 to the next simplest level, etc. The resulting numbers are then combined – if needed, with appropriate weights. In this paper, we provide a theoretical explanation for the above idea.

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“…, c n ) that satisfy the property (2). This mean value is known (see, e.g., [1,2,4,6,7]), and it is equal to c i = i n + 1 .…”

Section: Main Idea Behind the New Empirically Successful Code Qualitymentioning

confidence: 99%