Matias Martinez

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Software Engineer, Researcher, University Teacher

Welcome to Matias Martinez website

About me:

I am researcher at the Universitat Politècnica de Catalunya-BarcelonaTech (UPC) (Spain), and a member of the inSSIDE research group. I got my PhD degree in October 2014 from University of Lille (France) and a Computer Science degree from UNICEN (Argentina). Moreover, I had teaching duties at the engineering school Telecom Lille. Previously, I worked as Associate Professor at the Université Polytechnique Hauts-de-France (France) and in the private sector as software developer (Java, Web, SOA, Mobile).
I have developed and maintained several software tools including Astor, an automated program repair framework, and Coming, a tool for mining commits from Git repositories.

News:

I appear in the second place on the ranking of Most Impactful Early-stage Software Engineering Researchers during the period 2013-2020, elaborated by the E. Wong et colleagues at A bibliometric assessment of software engineering themes, scholars and institutions (2013–2020), and in the nineteenth place on the ranking of Most Active Early-stage Software Engineering Researchers in Top-Quality journals.

I am associate editor of Springer Automated Software Engineering journal.

I have published in the French magazine ActuAI an article about AI in source code (ActuAI number 8)

Education:

Research Interests:

Tools:

I have created, build and maintain the following open-source tools:

Moreover, I have also contributed to other open-source projects such as:

Publications:

See all my publications in Google Scholar

2023

Taxonomy of Attacks on Open-Source Software Supply Chains. P. Ladisa, H. Plate, M. Martinez, O. Barais. IEEE S&P 2023 [Download Arxiv]

Hyperparameter Optimization for AST Differencing. M. Martinez, J.R. Falleri, M. Monperrus. IEEE Transactions on Software Engineering [Download Arxiv]

Learning the Relation between Code Features and Code Transforms with Structured Prediction. Z. Yu, M. Martinez, Z. Chen, T. Bissyandé, M. Monperrus. Transactions on Software Engineering (TSE) [Download Arxiv]

Journey to the Center of Software Supply Chain Attacks P. Ladisa, S. Ponta, A. Sabetta, M. Martinez, O. Barais.[Download Arxiv]

Energy Consumption of Automated Program Repair. M. Martinez, S. Martinez-Fernandez, X. Franch. [Download Arxiv]

Energy efficiency of training neural network architectures: An empirical study. Y. Xu, S. Martínez-Fernández, M. Martinez, X. Franch. HICSS-56. [Download Arxiv]

Evolution of Kotlin Apps in terms of Energy Consumption: An Exploratory Study. H. Ahmed, A. Boshchenko, N. Khan, D. Knyajev, D. Garifollina, G. Scoccia, M. Martinez, I. Malavolta. ICT4S 2023. Download

One Model to Rule Them All: On the Feasibility of Cross-Language Detection of Malicious Packages. P. Ladisa, S.Ponta, N. Ronzoni, M. Martinez, O. Barais. ACSAC 2023.

The Hitchhiker’s Guide to Malicious Third-Party Dependencies P. Ladisa, M. Sahin, S. Ponta, M. Rosa, M. Martinez, O. Barais SCORE 2023 (Workshop on Software Supply Chain Offensive Research and Ecosystem Defenses) [Download Arxiv]

2022

Neural Program Repair using Execution-based Backpropagation. Y. He, M. Martinez, M. Monperrus. International Conference on Software Engineering (ICSE 2022) (2022). DOI: https://doi.org/10.1145/3510003.3510222 [Download Arxiv]

SelfAPR: Self-supervised Program Repair with Test Execution Diagnostics. H. Ye, M. Martinez, X. Luo, T. Zhang, M. Monperrus. International Conference on Automated Software Engineering (ASE’22) [Download Arxiv]

Learning migration models for supporting incremental language migrations of software applications. Bruno Góis Mateus, Matias Martinez, Christophe Kolski. Information and Software Technology (IST) DOI: https://doi.org/10.1016/j.infsof.2022.107082 [Download Elsevier] [Download Arxiv]

Estimating the Potential of Program Repair Search Spaces with Commit Analysis. K. Etemadi, N. Tarighat, S. Yadav, M. Martinez, M. Monperrus. Journal of Systems & Software DOI: https://doi.org/10.1016/j.jss.2022.111263 [Download Elsevier] [Download Arxiv]

Is well-tested code more energy efficient?. A. Noureddine, M. Martinez, H. Kanso, N. Bru. In the 11th Workshop on the Reliability of Intelligent Environments (WoRIE’22)/(IE 2022) [Download HAL]

Test-based Patch Clustering for Automatically-Generated Patches Assessment. M. Martinez, M. Kechagia, A. Perera, J. Petke, F. Sarro, A. Aleti. (2022) [Download Arxiv]

Apprentissage automatique sur le code source (In French). Matias Martinez. ActuIA Magazine [Download ActuIA] [Download] (2022)

Towards the Detection of Malicious Java Packages P. Ladisa, H. Plate, M. Martinez, O. Barais, S. Ponta. ACM Workshop on Software Supply Chain Offensive Research and Ecosystem Defenses (SCORED ‘22) [Download Arxiv]

2021

Why did developers migrate Android Applications from Java to Kotlin? M. Martinez, B.Gois Mateus. Transactions on Software Engineering (2021). DOI: 0.1109/TSE.2021.3120367 [Download Arxiv] [Download IEEE Xplore]

E-APR: Mapping the Effectiveness of Automated Program Repair. A. Aleti and M. Martinez. Empirical Software Engineering Journal (2021). DOI: 10.1007/s10664-021-09989-x [Download Arxiv] [Download Springer]

A Comprehensive Study of Code-removal Patches in Automated Program Repair. D. Ginelli, M. Martinez, L. Mariani, M. Monperrus. Empirical Software Engineering Journal (2021). [Download Arxiv]

Patchworking: Exploring the Code Changes induced by Vulnerability Fixing Activities G. Canfora, A. Di Sorbo; S. Forootani, M. Martinez, C. A. Visaggio. Information and Software Technology (2021). DOI: 10.1016/j.infsof.2021.106745 [Download Elsevier].

Green Tests in Java, Pharo and Python: An Empirical Study. V. Aranega, J. Delplanque, M. Martinez, A. P. Black, S. Ducasse, A. Etien, C. Fuhrman, G. Polito. Empirical Software Engineering Journal (2021) DOI: 10.1007/s10664-021-10016-2 [Download Arxiv] [Download Springer]

Automated Classification of Overfitting Patches with Statically Extracted Code Features. H. Ye, J. Gu, M. Martinez, T. Durieux, M. Monperrus. Transactions on Software Engineering (TSE) (2021) DOI: 10.1109/TSE.2021.3071750 [Download Arxiv] [Download IEEE Access]

R-Hero: A Software Repair Bot based on Continual Learning. B. Baudry, Z. Chen, K. Etemadi, H. Fu, D. Ginelli, S. Kommrusch, M. Martinez, M. Monperrus, J.r Ron, H. Ye, Z. Yu. IEEE Software (2021) DOI: 10.1109/MS.2021.3070743 [Download Arxiv] [Download IEEE Xplore]

A Preliminary Study of the Impact of Code Coverage on Software Energy Consumption.. A. Noureddine, M. Martinez, H. Kanso. In the Second International Workshop on Sustainable Software Engineering (SUSTAINSE)/(ASE’21) 2021. [Download HAL] [Download IEEE Digital Library]

FLACOCO: Fault Localization for Java based on Industry-grade Coverage. A. Silva, M. Martinez, Be. Danglot, D. Ginelli, M. Monperrus.[Download Arxiv]

2020

RTj: a Java framework for detecting and refactoring rotten green test cases. M. Martinez, A. Etien, S. Ducasse, C. Fuhrman. ICSE International Conference on Software Engineering - Demonstration Track DOI: 10.1145/ 3377812.3382151 [Download Arxiv] [Download ACM]

Automated Patch Assessment for Program Repair at Scale. H. Ye, M. Martinez, M. Monperrus. Empirical Software Engineering Journal [Download Arxiv] [Download Springer]

On the adoption, usage and evolution of Kotlin Features on Android development. B. Gois Mateus, M. Martinez. Empirical Software Engineering and Measurement (ESEM 2020) DOI: 10.1145/ 3382494.3410676 [Download Arxiv] [Download ACM]

A comprehensive study of automatic program repair on the QuixBugs benchmark. H. Ye, M, Martinez, T. Durieux, M, Monperrus. Journal of Systems and Software (JSS). DOI: 10.1016/j.jss.2020.110825. [Download Arxiv] [Download Elsevier]

An Empirical Study on Quality of Android Applications written in Kotlin language. B. Gois Mateus, M. Martinez. ICSE International Conference on Software Engineering -Journal First- 2020 DOI: 10.1007/s10664-019-09727-4 [Download Arxiv]

2019

Empirical Review of Program Repair Tools: A Large-Scale Experiment on 2 141 Bugs and 23 551 Repair Attempts. T. Durieux, F. Madeiral, M. Martinez, R. Abreu. ESEC/FSE Foundations of Software Engineering (2019) doi: 10.1145/ 3338906.3338911. [Download Arxiv]. News: ACM SIGSOFT Distinguished Paper Award at ESEC/FSE 2019

An Empirical Study on Quality of Android Applications written in Kotlin language. B. Gois Mateus, M. Martinez. Empirical Software Engineering Journal (2019) doi: 10.1007/s10664-019-09727-4 [Download Arxiv]

Coming: a tool for mining change pattern instances from git commits. M. Martinez and M. Monperrus. 2019. International Conference on Software Engineering (ICSE Demonstration Track). doi: 10.1109/ICSE-Companion.2019.00043 [Download Arxiv]

Repairnator patches programs automatically. M. Monperrus, S. Urli, T. Durieux, M. Martinez, Benoit Baudry, L. Seinturier. Ubiquity, Association for Computing Machinery (2019) doi: 10.1145/ 3349589 [Download Arxiv]

Sorting and Transforming Program Repair Ingredients via Deep Learning Code Similarities. M. White, M. Tufano, M. Martinez, M. Monperrus, D. Poshyvanyk. In Proceedings of SANER 2019. doi: 10.1109/SANER.2019.8668043 [Download Arxiv]

Alleviating Patch Overfitting with Automatic Test Generation: A Study of Feasibility and Effectiveness for the Nopol Repair System. Z. Yu, M. Martinez, B. Danglot, T. Durieux, M. Monperrus. ICSE 2019 Journal First (2019) doi: 10.1007/s10664-018-9619-4 [Download Arxiv]

A Comprehensive Study of Automatic Program Repair on the QuixBugs Benchmark H. Ye, M. Martinez,T. Durieux, M. Monperrus. International Workshop on Intelligent Bug Fixing (IBF 2019) co-located with SANER 2019. doi: 10.1109/IBF.2019.8665475 Best paper award [Download Arxiv].

Program Repair at Arbitrary Fault Depth. B. Khaireddine, M. Martinez, A. Mili. IEEE Conference on Software Testing (ICST) (2019) DOI:10.1109/ICST.2019.00056 [Download Arxiv].

Astor: Exploring the Design Space of Generate-and-Validate Program Repair beyond GenProg. M. Martinez, M. Monperrus. Journal of Systems and Software (JSS) and Automated Software Engineering (ASE) Journal-First Track (2019) doi: 10.1016/j.jss.2019.01.069 [Download Arxiv]

Two Datasets of Questions and Answers for Studying the Development of Cross-platform Mobile Applications using Xamarin Framework. M.Martinez International Conference on Mobile Software Engineering and Systems (MobileSoft) (2019) doi: 10.1109/MOBILESoft.2019.00032 [Download Arxiv]

2018

Alleviating patch overfitting with automatic test generation: a study of feasibility and effectiveness for the Nopol repair system. Z. Yu, M. Martinez, B. Danglot, T. Durieux, M. Monperrus. Empirical Software Engineering Journal (2018) doi: 10.1007/s10664-018-9619-4 [Download Arxiv]

Ultra-Large Repair Search Space with Automatically Mined Templates: the Cardumen Mode of Astor. M. Martinez, M. Monperrus. Symposium on Search-Based Software Engineering (2018) arXiv:1712.03854 [Download Arxiv]

2017

Towards the quality improvement of cross-platform mobile applications. M. Martinez, S. Lecomte. International Conference on Mobile Software Engineering and Systems (MOBILESoft 2017) (2017). DOI: https://doi.org/10.1109/MOBILESoft.2017.30 [Download Arxiv]

Astor repair framework. M.Martinez. Dagstuhl Seminar on automated program repair. Link

2016

Automatic repair of real bugs in java: a large-scale experiment on the defects4j dataset. M. Martinez, T. Durieux, R. Sommerard, J. Xuan, M. Monperrus. Empirical Software Engineering Journal (2016). doi: 10.1007/s10664-016-9470-4 [Download Arxiv].

Nopol: Automatic Repair of Conditional Statement Bugs in Java Programs. J. Xuan; M. Martinez; F. DeMarco; M. Clement; S. Lamelas Marcote; T. Durieux; D. Le Berre; M. Monperrus, in IEEE Transactions on Software Engineering, doi: 10.1109/TSE.2016.2560811 [Download Arxiv].

ASTOR: a program repair library for Java (demo). Matias Martinez and Martin Monperrus. 2016. In Proceedings of the 25th International Symposium on Software Testing and Analysis (ISSTA 2016). DOI: 10.1145/ 2931037.2948705 [Download Arxiv].

B-Refactoring: Automatic test code refactoring to improve dynamic analysis. J. Xuan, B. Cornu, M. Martinez, B. Baudry, L. Seinturier, M. Monperrus, Information and Software Technology, DOI: 10.1016/j.infsof.2016.04.016 [Download Arxiv].

2015

When App Stores Listen to the Crowd to Fight Bugs in the Wild. M.Gomez, M. Martinez, R. Rouvoy and M. Monperrus. In Proceedings of the 37th International Conference on Software Engineering - Volume 2 (ICSE ‘15), DOI: 10.1109/ICSE.2015.195 [Download Arxiv].

2014

Fine-grained and Accurate Source Code Differencing. J.R Falleri, F. Morandat, X. Blanc, M. Martinez, M. Monperrus. In Proceedings of the 29th ACM/IEEE international conference on Automated software engineering (ASE ‘14). DOI: 10.1145/ 2642937.264298 [Download Arxiv]

Do the Fix Ingredients Already Exist? An Empirical Inquiry into the Redundancy Assumptions of Program Repair Approaches. M. Martínez, W. Weimer and M. Monperrus. In Companion Proceedings of the 36th International Conference on Software Engineering (ICSE Companion 2014). DOI: 10.1145/ 2591062.2591114 [Download Arxiv].

ASTOR: Evolutionary Automatic Software Repair for Java. M.Martinez, M.Monperrus (Technical Report) [Download Arxiv].

Accurate Extraction of Bug Fix Pattern Occurrences using Abstract Syntax Tree Analysis. M. Martinez, L. Duchien and M. Monperrus (Technical Report) [Download Arxiv].

2013

Mining software repair models for reasoning on the search space of automated program fixing. M. Martinez and M. Monperrus. Empirical Software Engineering journal, Springer Verlag. 20: 176. doi:10.1007/s10664-013-9282-8 [Download Arxiv].

Automatically Extracting Instances of Code Change Patterns with AST Analysis. Matías Martínez, Laurence Duchien and Martin Monperrus. In Proceedings of the 2013 IEEE International Conference on Software Maintenance (ICSM ‘13). DOI: 10.1109/ICSM.2013.54 [Download Arxiv].

Probabilistic Mutational Transformations for Automatic Software Repair (ICSM’13, Doctoral Symposium Poster).

2012

Conservation and Replication with CVS-Vintage: A Dataset of CVS Repositories. M. Monperrus, M. Martínez (Technical Report) [Download Arxiv].

Mining Repair Actions for Automated Program Fixing. Matías Martínez, Martin Monperrus (GPL’12, Poster).

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https://github.com/martinezmatias/

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