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 2019Show all

11 papers · 1 filter

cs.SE2019★ 46 cited

Some SonarQube Issues have a Significant but SmallEffect on Faults and Changes. A large-scale empirical study

Valentina Lenarduzzi, Nyyti Saarimäki, Davide Taibi

Context. Companies commonly invest effort to remove technical issues believed to impact software qualities, such as removing anti-patterns or coding styles violations. Objective. O…

cs.SE2019★ 53 cited

Continuous Architecting with Microservices and DevOps: A Systematic Mapping Study

Davide Taibi, Valentina Lenarduzzi, Claus Pahl

Context: Several companies are migrating their information systems into the Cloud. Microservices and DevOps are two of the most common adopted technologies. However, there is still…

cs.SE2019

Does Code Quality Affect Pull Request Acceptance? An empirical study

Valentina Lenarduzzi, Vili Nikkola, Nyyti Saarimäki +1

Background. Pull requests are a common practice for contributing and reviewing contributions, and are employed both in open-source and industrial contexts. One of the main goals of…

cs.SE2019★ 2 cited

Microservices Anti Patterns: A Taxonomy

Davide Taibi, Valentina Lenarduzzi, Claus Pahl

Several companies are re-architecting their monolithic information systems with microservices. However, many companies migrated without experience on microservices, mainly learning…

cs.SE2019

An Empirical Study on Technical Debt in a Finnish SME

Valentina Lenarduzzi, Teemu Orava, Nyyti Saarimäki +2

Objective. In this work, we report the experience of a Finnish SME in managing Technical Debt (TD), investigating the most common types of TD they faced in the past, their causes,…

cs.SE2019★ 77 cited

The Technical Debt Dataset

Valentina Lenarduzzi, Nyyti Saarimäki, Davide Taibi

Technical Debt analysis is increasing in popularity as nowadays researchers and industry are adopting various tools for static code analysis to evaluate the quality of their code.…

cs.SE2019★ 26 cited

Towards Surgically-Precise Technical Debt Estimation: Early Results and Research Roadmap

Valentina Lenarduzzi, Antonio Martini, Davide Taibi +1

The concept of technical debt has been explored from many perspectives but its precise estimation is still under heavy empirical and experimental inquiry. We aim to understand whet…

cs.SE2019

Are SonarQube Rules Inducing Bugs?

Valentina Lenarduzzi, Francesco Lomio, Heikki Huttunen +1

Background. The popularity of tools for analyzing Technical Debt, and particularly the popularity of SonarQube, is increasing rapidly. SonarQube proposes a set of coding rules, whi…

cs.SE2019

Are Architectural Smells Independent from Code Smells? An Empirical Study

Francesca Arcelli Fontanaa, Valentina Lenarduzzi, Riccardo Roveda +1

Background. Architectural smells and code smells are symptoms of bad code or design that can cause different quality problems, such as faults, technical debt, or difficulties with…

cs.SE2019★ 9 cited

Technical Debt Prioritization: State of the Art. A Systematic Literature Review

Valentina Lenarduzzi, Terese Besker, Davide Taibi +2

Background. Software companies need to manage and refactor Technical Debt issues. Therefore, it is necessary to understand if and when refactoring Technical Debt should be prioriti…

cs.SE2019

Does Migrate a Monolithic System to Microservices Decrease the Technical Debt?

Valentina Lenarduzzi, Francesco Lomio, Nyyti Saarimäki +1

Background. The migration from monolithic systems to microservices involves deep refactoring of the systems. Therefore, the migration usually has a big economic impact and companie…