Mikel Robredo Manero

PhD student at University of Oulu

Background in Statistical Data Analytics & Data Science

Time Series Analysis techniques in Software Quality & Technical Debt

Publications

Publications

  • ALL
  • 2023
  • 2024
  • 2025

Ignoring Time Dependence in Software Engineering Data. A Mistake

M. Robredo, N. Saarimaki, R. PeƱaloza, V. Lenarduzzi

Submitted to WSESE2024 (International Workshop on Methodological Issues with Empirical Studies in Software Engineering)

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

N. Saarimaki, M. Robredo, S. Vegas, N. Juristo, D. Taibi, V. Lenarduzzi

Submitted to International Conference on Mining Software Repositories (MSR 2024)

MEASURING THE IMPACT OF SONARQUBE ON THE DEVELOPMENT VELOCITY USING REGRESSION ANALYSIS

M. Robredo

My Resume

My Resume

Education

PhD of Statistical Data Analysis in Empirical Software Engineering

2023 - Present

University of Oulu, Oulu, Finland

Currently, I am investigating the state-of-the-art data analysis approaches adopted in the Empirical Software Engineering domain. With some scientific articles already published, I am looking forward to publishing a Systematic Literature Review based on my investigation.

Master of Science in Statistical Data Analytics

2021 - 2023

Tampere University, Tampere, Finland

Application of computational statistics within the field of Data Science. Among the disciplines learnt during these studies are Time Series Analysis, Scientific Computing in diverse programming languages, Advanced Statistical Modelling & Bayesian Analysis.

Bachelor of Economics

2016 - 2020

University of the Basque Country, Bilbao, Spain

With a major in Development and International Economics, I developed skills in Statistics, Macroeconomics, Microeconomics and Econometrics. I completed an international mobility of 6 months in the University of Milano-Bicocca, Italy.

Professional Experience

Doctoral researcher

2023 - Present

University of Oulu, Oulu, Finland

  • Investigation of the state-of-the-art data analysis approaches adopted in the Empirical Software Engineering domain.
  • Identification of data analysis issues in the Empirical Software Engineering studies.
  • Definition of time dependent statistical analysis techniques.
  • Comparison of the new approach with the traditional ones adopted by Empirical Software Engineering studies.
  • Internal Validation (application in Empirical Software Engineering do- main with a particular focus on Cohort Study).
  • Guidelines definition.

Junior research assistant

2023 (6 months)

University of Oulu, Oulu, Finland

  • Data extraction pipeline design for Mining Software Repositories (Python, GitHub REST API).
  • Application of Cohort Studies in Empirical Software Engineering with Mature Software project version control data.
  • Non-linear regression analysis applying Generalized Linear Models theory (R).
  • Scientific writing.

About Me

About Me

PhD student specialized in Statistical Data Analysis in Empirical Software Engineering

  • Name: Mikel Robredo Manero
  • Website: https://robredomikel.github.io/
  • Phone: +34 669 877 214
  • City: Oulu, Finland
  • Age: 25
  • Studies: PhD
  • Email: mikel.robredomanero@oulu.fi
  • Background: Computational statistics

Years of PhD

Papers published

Years of experience

Awards

Python 100%
R 80%
C++ 75%
Scala Spark 60%
Contact Me

Contact Me

University of Oulu | Pentti Kaiteran katu 1 | Office: AT221 | 90570, Oulu, Finland

Social Profiles

Email Me

mikel.robredomanero@oulu.fi

Call Me

+34 669 877 214

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