activity
20182026
most citedThe Technical Debt Dataset

77 citations · 238 across the 39 of their papers we have counts for

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Showing 2023Show all

8 papers · 1 filter

cs.IR2023

Towards a Technical Debt for Recommender System

Sergio Moreschini, Ludovik Coba, Valentina Lenarduzzi

Balancing the management of technical debt within recommender systems requires effectively juggling the introduction of new features with the ongoing maintenance and enhancement of…

cs.SE2023

Ignoring Time Dependence in Software Engineering Data. A Mistake

Mikel Robredo, Nyyti Saarimaki, Rafael Penaloza +1

Researchers often delve into the connections between different factors derived from the historical data of software projects. For example, scholars have devoted their endeavors to…

cs.SE2023

One Microservice per Developer: Is This the Trend in OSS?

Dario Amoroso d'Aragona, Xiaoxhou Li, Tomas Cerny +3

When developing and managing microservice systems, practitioners suggest that each microservice should be owned by a particular team. In effect, there is only one team with the res…

cs.SE2023★ 1 cited

Does Microservices Adoption Impact the Development Velocity? A Cohort Study. A Registered Report

Nyyti Saarimaki, Mikel Robredo, Sira vegas +3

[Context] Microservices enable the decomposition of applications into small and independent services connected together. The independence between services could positively affect t…

cs.SE2023★ 2 cited

On the Empirical Evidence of Microservice Logical Coupling. A Registered Report

Dario Amoroso d Aragona, Luca Pascarella, Andrea Janes +3

[Context] Coupling is a widely discussed metric by software engineers while developing complex software systems, often referred to as a crucial factor and symptom of a poor or good…

cs.SE2023

Breaks and Code Quality: Investigating the Impact of Forgetting on Software Development. A Registered Report

Dario Amoroso d'Aragona, Luca Pascarella, Andrea Janes +3

Developers interrupting their participation in a project might slowly forget critical information about the code, such as its intended purpose, structure, the impact of external de…

cs.SE2023★ 3 cited

Toward End-to-End MLOps Tools Map: A Preliminary Study based on a Multivocal Literature Review

Sergio Moreschi, Gilberto Recupito, Valentina Lenarduzzi +3

MLOps tools enable continuous development of machine learning, following the DevOps process. Different MLOps tools have been presented on the market, however, such a number of tool…

cs.SE2023★ 3 cited

Early Career Developers' Perceptions of Code Understandability. A Study of Complexity Metrics

Matteo Esposito, Andrea Janes, Terhi Kilamo +1

Context. Code understandability is fundamental. Developers need to understand the code they are modifying clearly. A low understandability can increase the amount of coding effort,…