Matteo Vaccargiu

Matteo Vaccargiu, Riccardo Lai, Maria Ilaria Lunesu et al.

We study how bots contribute to open-source discussions in the Ethereum ecosystem and whether they influence developers' emotional tone. Our dataset covers 36,875 accounts across ten repositories with 105 validated bots (0.28%). Human participation follows a U-shaped pattern, while bots engage in uniform (pull requests) or late-stage (issues) activity. Bots respond faster than humans in pull requests but play slower maintenance roles in issues. Using a model trained on 27 emotion categories, we find bots are more neutral, yet their interventions are followed by reduced neutrality in human comments, with shifts toward gratitude, admiration, and optimism and away from confusion. These findings indicate that even a small number of bots are associated with changes in both timing and emotional dynamics of developer communication.

Matteo Vaccargiu, Sabrina Aufiero, Silvia Bartolucci et al.

Labels on platforms such as GitHub support triage and coordination, yet little is known about how well they align with code modifications or how such alignment affects collaboration across contributor experience levels. We present a case study of the Kubernetes project, introducing label-diff congruence - the alignment between pull request labels and modified files - and examining its prevalence, stability, behavioral validation, and relationship to collaboration outcomes across contributor tiers. We analyse 18,020 pull requests (2014--2025) with area labels and complete file diffs, validate alignment through analysis of over one million review comments and label corrections, and test associations with time-to-merge and discussion characteristics using quantile regression and negative binomial models stratified by contributor experience. Congruence is prevalent (46.6\% perfect alignment), stable over years, and routinely maintained (9.2\% of PRs corrected during review). It does not predict merge speed but shapes discussion: among core developers (81\% of the sample), higher congruence predicts quieter reviews (18\% fewer participants), whereas among one-time contributors it predicts more engagement (28\% more participants). Label-diff congruence influences how collaboration unfolds during review, supporting efficiency for experienced developers and visibility for newcomers. For projects with similar labeling conventions, monitoring alignment can help detect coordination friction and provide guidance when labels and code diverge.

Matteo Vaccargiu, Andrea Pinna, Maria Ilaria Lunesu et al.

Smart contract vulnerabilities have caused billions in financial losses, raising questions about whether programming language paradigms can reduce security overhead. While imperative languages like Solidity require developers to manually implement security checks, resource-oriented languages like Move encode safety guarantees in type systems. We present a preliminary mixed-methods study analyzing 12 functionally-equivalent contract pairs implemented in both Solidity and Move by the same development team, complemented by a survey of 11 developers experienced in both languages. Quantitative analysis reveals that Move reduces explicit security overhead by 60\% (security check density: 6.7% vs. 16.8%, p=0.002, Cohen's d=-1.75) at the cost of 47% larger code size (p=0.002, d=1.90), while maintaining identical cyclomatic complexity. Developer surveys show moderate learning difficulty but higher safety confidence in Move (Median=6/7, 10 of 11 above neutral), with 55% preferring Move for security-critical applications despite ecosystem maturity gaps. These preliminary findings suggest resource-oriented paradigms shift security from runtime validation to compile-time guarantees, though adoption requires investment in learning and tooling. The controlled comparison provides initial evidence for paradigm effects on smart contract development, informing language selection decisions and identifying opportunities for improved developer resources.