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Researcher profile

Matteo Esposito

Matteo Esposito contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
Artificial IntelligenceSoftware Engineeringastro-ph.COhep-thInformation RetrievalMachine LearningMultiagent Systems

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Published work

3 published item(s)

preprint2026arXiv

A Defect is Being Born: How Close Are We? A Time Sensitive Forecasting Approach

Background. Defect prediction has been a highly active topic among researchers in the Empirical Software Engineering field. Previous literature has successfully achieved the most accurate prediction of an incoming fault and identified the features and anomalies that precede it through just-in-time prediction. As software systems evolve continuously, there is a growing need for time-sensitive methods capable of forecasting defects before they manifest. Aim. Our study seeks to explore the effectiveness of time-sensitive techniques for defect forecasting. Moreover, we aim to investigate the early indicators that precede the occurrence of a defect. Method. We will train multiple time-sensitive forecasting techniques to forecast the future bug density of a software project, as well as identify the early symptoms preceding the occurrence of a defect. Expected results. Our expected results are translated into empirical evidence on the effectiveness of our approach for early estimation of bug proneness.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

A Research Agenda on Agents and Software Engineering: Outcomes from the Rio A2SE Seminar

The rise of agentic AI is reshaping software engineering in two intertwined directions: agents are increasingly applied to support software engineering tasks, and Agentic AI systems themselves are complex systems that require re-thinking currently established software engineering practices. To chart a coherent research agenda covering the two directions, we organized the A2SE seminar in Rio de Janeiro, bringing together 18 experts from academia and industry. Through structured presentations, collaborative topic clustering, and focused group discussions, participants identified six thematic areas: Governance, Software Engineering for Agents, Agents for Software Architecture, Quality and Evaluation, Sustainability, and Code, and they prioritized short-term and long-term research directions for each. This paper presents the resulting community-driven, opinionated research agenda, offering the SE community a structured foundation for coordinating efforts at this critical juncture.

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preprint2022arXiv

Weighing Cosmic Structures with Clusters of Galaxies and the Intergalactic Medium

We present an analysis aimed at combining cosmological constraints from number counts of galaxy clusters identified through the Sunyaev-Zeldovich effect, obtained with the South Pole Telescope (SPT), and from Lyman-$α$ spectra obtained with the MIKE/HIRES and X-shooter spectrographs. The SPT cluster analysis relies on mass calibration based on weak lensing measurements, while the Lyman-$α$ analysis is built over a suite of hydrodynamical simulations for the extraction of mock spectra. The resulting constraints exhibit a tension ($\sim 3.3σ$) between the low $σ_8$ values preferred by the low-redshift cluster data, $σ_8=0.74 ^{+0.03}_{-0.04}$, and the higher one preferred by the high-redshift Lyman-$α$ data, $σ_8=0.91 ^{+0.03}_{-0.03}$. We present a detailed analysis in order to understand the origin of this tension and, in particular, to establish whether it arises from systematic uncertainties related to the assumptions underlying the analyses of cluster counts and/or Lyman-$α$ forest. We found this tension to be robust with respect to the choice of modeling of the IGM, even when including possible systematics from unaccounted sub-Damped Lyman-$α$ (DLA) and Lyman-limit systems (LLS) in the Lyman-$α$ data. We conclude that to solve this tension from the SPT side would require a large bias on the cluster mass estimate, or from the Lyman-$α$ side large unaccounted errors on the Lyman-$α$ mean fluxes, respectively. Our results have important implications for future analyses based on cluster number counts from future large photometric surveys (e.g. Euclid and LSST) and on larger samples of high-redshift quasar spectra (e.g. DESI and WEAVE surveys). If confirmed at the much higher statistical significance reachable by such surveys, this tension could represent a significant challenge for the standard $Λ$CDM paradigm.

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