Performance Comparison of Software Complexity Metrics in an Open Source Project

2007 ◽  
pp. 160-174 ◽  
Author(s):  
Min Zhang ◽  
Nathan Baddoo
Keyword(s):  
Open Source ◽  
Performance Comparison ◽  
Open Source Project ◽  
Software Complexity ◽  
Complexity Metrics

Performance Comparison of Web Backend And Database: A Case Study Of Node.JS, Golang and MySQL, MongoDB

2019 ◽  
Vol 13 ◽  
Author(s):  
Faried Effendy ◽  
Taufik ◽  
Bramantyo Adhilaksono
Keyword(s):  
Response Time ◽  
Open Source ◽  
Poisson Distribution ◽  
Mobile Application ◽  
Web Applications ◽  
Performance Comparison ◽  
Memory Usage ◽  
Data Traffic ◽  
Cpu Utilization

: Substantial research has been conducted to compare web servers or to compare databases, but very limited research combines the two. Node.js and Golang (Go) are popular platforms for both web and mobile application back-ends, whereas MySQL and Go are among the best open source databases with different characters. Using MySQL and MongoDB as databases, this study aims to compare the performance of Go and Node.js as web applications back-end regarding response time, CPU utilization, and memory usage. To simulate the actual web server workload, the flow of data traffic on the server follows the Poisson distribution. The result shows that the combination of Go and MySQL is superior in CPU utilization and memory usage, while the Node.js and MySQL combination is superior in response time.

The non-psychopath's guide to managing an open source project

2021 ◽  
Vol 64 (4) ◽  
pp. 25-27
Author(s):  
George V. Neville-Neil
Keyword(s):  
Open Source ◽  
Open Source Project

Respect your staff, learn from others, and know when to let go.

scholarly journals Metrics for evaluation of metaprogram complexity

2010 ◽  
Vol 7 (4) ◽  
pp. 769-787 ◽  
Author(s):  
Robertas Damasevicius ◽  
Vytautas Stuikys
Keyword(s):  
Measurement Techniques ◽  
Graph Algorithm ◽  
Aspect Oriented Programming ◽  
Engineering Software ◽  
Software Complexity ◽  
Complexity Management ◽  
Complexity Metrics ◽  
Cognitive Difficulty ◽  
Cognitive Dimensions

The concept of complexity is used in many areas of computer science and software engineering. Software complexity metrics can be used to evaluate and compare quality of software development and maintenance processes and their products. Complexity management and measurement is especially important in novel programming technologies and paradigms, such as aspect-oriented programming, generative programming, and metaprogramming, where complex multilanguage and multi-aspect program specifications are developed and used. This paper analyzes complexity management and measurement techniques, and proposes five complexity metrics (Relative Kolmogorov Complexity, Metalanguage Richness, Cyclomatic Complexity, Normalized Difficulty, Cognitive Difficulty) for measuring complexity of metaprograms at information, metalanguage, graph, algorithm, and cognitive dimensions.

scholarly journals From Frequency to Meaning: Vector Space Models of Semantics

2010 ◽  
Vol 37 ◽  
pp. 141-188 ◽  
Author(s):  
P. D. Turney ◽  
P. Pantel
Keyword(s):  
Vector Space ◽  
Open Source ◽  
Semantic Processing ◽  
Human Language ◽  
Open Source Project ◽  
Word Context ◽  
The Matrix ◽  
Vector Space Models ◽  
New Perspective

Computers understand very little of the meaning of human language. This profoundly limits our ability to give instructions to computers, the ability of computers to explain their actions to us, and the ability of computers to analyse and process text. Vector space models (VSMs) of semantics are beginning to address these limits. This paper surveys the use of VSMs for semantic processing of text. We organize the literature on VSMs according to the structure of the matrix in a VSM. There are currently three broad classes of VSMs, based on term-document, word-context, and pair-pattern matrices, yielding three classes of applications. We survey a broad range of applications in these three categories and we take a detailed look at a specific open source project in each category. Our goal in this survey is to show the breadth of applications of VSMs for semantics, to provide a new perspective on VSMs for those who are already familiar with the area, and to provide pointers into the literature for those who are less familiar with the field.

scholarly journals Jupyter: Thinking and Storytelling with Code and Data

2021 ◽  
Author(s):  
Brian Granger ◽  
Fernando Pérez
Keyword(s):  
Machine Learning ◽  
Open Source ◽  
Community Of Practice ◽  
Scientific Computing ◽  
Data Science ◽  
Climate Science ◽  
Three Dimensions ◽  
Open Source Project ◽  
Interactive Computing ◽  
The Impact

Project Jupyter is an open-source project for interactive computing widely used in data science, machine learning, and scientific computing. We argue that even though Jupyter helps users perform complex, technical work, Jupyter itself solves problems that are fundamentally human in nature. Namely, Jupyter helps humans to think and tell stories with code and data. We illustrate this by describing three dimensions of Jupyter: interactive computing, computational narratives, and  the idea that Jupyter is more than software. We illustrate the impact of these dimensions on a community of practice in Earth and climate science.

The Effects of Diversity in Global, Distributed Collectives: A Study of Open Source Project Success

2013 ◽  
Vol 24 (2) ◽  
pp. 312-333 ◽  
Author(s):  
Sherae Daniel ◽  
Ritu Agarwal ◽  
Katherine J. Stewart
Keyword(s):  
Open Source ◽  
Project Success ◽  
Open Source Project
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