activity
20162021
most citedOn Technical Trading and Social Media Indicators in Cryptocurrencies' Price Classification Through Deep Learning

2 citations · 2 across the 2 of their papers we have counts for

collaborators

7 papers

q-fin.ST20212 cited

On Technical Trading and Social Media Indicators in Cryptocurrencies' Price Classification Through Deep Learning

Marco Ortu, Nicola Uras, Claudio Conversano +2

This work aims to analyse the predictability of price movements of cryptocurrencies on both hourly and daily data observed from January 2017 to January 2021, using deep learning al…

cs.LG2019

The Prevalence of Errors in Machine Learning Experiments

Martin Shepperd, Yuchen Guo, Ning Li +7

Context: Conducting experiments is central to research machine learning research to benchmark, evaluate and compare learning algorithms. Consequently it is important we conduct rel…

cs.SE2019

On the Relationship Between Coupling and Refactoring: An Empirical Viewpoint

Steve Counsell, Mahir Arzoky, Giuseppe Destefanis +1

[Background] Refactoring has matured over the past twenty years to become part of a developer's toolkit. However, many fundamental research questions still remain largely unexplore…

cs.SE2018

Analysing Developers Affectiveness through Markov chain Models

Giuseppe Destefanis, Marco Ortu, Steve Counsell +3

In this paper, we present an analysis of more than 500K comments from open-source repositories of software systems. Our aim is to empirically determine how developers interact with…

cs.SE2018

Smart Contracts Software Metrics: a First Study

Roberto Tonelli, Giuseppe Destefanis, Michele Marchesi +1

Smart contracts (SC) are software codes which reside and run over a blockchain. The code can be written in different languages with the common purpose of implementing various kinds…

cs.SE2017

Measuring Affectiveness and Effectiveness in Software Systems

Giuseppe Destefanis, Marco Ortu, Steve Counsell +2

The summary presented in this paper highlights the results obtained in a four-years project aiming at analyzing the development process of software artifacts from two points of vie…