Understanding computation time: a critical discussion of time as a computational performance metric
D Harris-Birtill, R Harris-Birtill - Time in Variance, 2021 - brill.com
Computation time is an important performance metric that scientists and software engineers
use to determine whether an algorithm is capable of running within a reasonable time frame …
use to determine whether an algorithm is capable of running within a reasonable time frame …
Performance complexity: An execution time metric to characterize the transparency and complexity of performance
E Strohmaier - CTWatch Quarterly, 2006 - icl.utk.edu
There is a rich collection of research available on the subject of software complexity.
Complexity measures discussed include code size expressed in lines of code (LOC), which …
Complexity measures discussed include code size expressed in lines of code (LOC), which …
[PDF][PDF] ExpOse: Inferring Worst-case Time Complexity by Automatic Empirical Study.
Introduction to doubling. A useful understanding of an algorithm's efficiency, the worst-case
time complexity gives an upper bound on how an increase in the size of the input, denoted …
time complexity gives an upper bound on how an increase in the size of the input, denoted …
An empirical estimation for time and memory algorithm complexities: newly developed R package
When an algorithm or a program runs on a computer, it requires some resources. The
complexity of an algorithm is the measure of the resources, for some input. These …
complexity of an algorithm is the measure of the resources, for some input. These …
A review of methods for estimating algorithmic complexity: options, challenges, and new directions
H Zenil - Entropy, 2020 - mdpi.com
Some established and also novel techniques in the field of applications of algorithmic
(Kolmogorov) complexity currently co-exist for the first time and are here reviewed, ranging …
(Kolmogorov) complexity currently co-exist for the first time and are here reviewed, ranging …
How productivity and impact differ across computer science subareas
How productivity and impact differ across computer science subareas Page 1 AugusT 2013 |
vOL. 56 | nO. 8 | communications of thE acm 67 soMe CoMPuter sCienCe researchers believe …
vOL. 56 | nO. 8 | communications of thE acm 67 soMe CoMPuter sCienCe researchers believe …
Sorting out software complexity
RL Glass - Communications of the ACM, 2002 - dl.acm.org
Sorting out software complexity Page 1 COMMUNICATIONS OF THE ACM November 2002/Vol.
45, No. 11 19 There has been, over the years, a raging contro- versy about how complex a task …
45, No. 11 19 There has been, over the years, a raging contro- versy about how complex a task …
Early algorithm efficiency with design patterns
D Ginat - Computer Science Education, 2001 - Taylor & Francis
Algorithm efficiency is a fundamental computer science concept encapsulating the core topic
of algorithm complexity. While complexity is expressed in formal measures such as 'Big O' …
of algorithm complexity. While complexity is expressed in formal measures such as 'Big O' …
[图书][B] Measuring empirical computational complexity
SF Goldsmith - 2009 - search.proquest.com
Scalability is a fundamental problem in computer science. Computer scientists often
describe the scalability of algorithms in the language of theoretical computational …
describe the scalability of algorithms in the language of theoretical computational …
Measuring empirical computational complexity
SF Goldsmith, AS Aiken, DS Wilkerson - Proceedings of the the 6th joint …, 2007 - dl.acm.org
The standard language for describing the asymptotic behavior of algorithms is theoretical
computational complexity. We propose a method for describing the asymptotic behavior of …
computational complexity. We propose a method for describing the asymptotic behavior of …