Laboratory of Software Comprehension, Analytics and Mining

Welcome to LASCAM

LASCAM aims at producing knowledge on how to improve software development practice based on past experience and evidences elaborated from data recorded in software repositories. 

Recent news:

LASCAM will have a new identity: Intelligent Software Engineering Lab. We'll be gradually moving content and updating that site until this one will be eventually discontinued.

The paper "Improving the Classification of Q&A Content for Android Fragmentation using Named Entity Recognition" has been accepted at the EPIA Conference on Artificial Intelligence, 2019 with Adriano Rocha and Marcelo Maia.

Eduardo Campos has defended his PhD thesis entitled: Recommending Knowledge Available in Q&A Sites for Aiding Software Development and Debugging (in portuguese)! April 12.

The paper "Discovering Common Bug-fix Patterns: A Large-Scale Observational Study" has been accepted for publication in the Journal of Software: Evolution and Process, with Eduardo Campos and Marcelo Maia!! March 27. 

Elder Vicente Sobrinho has defended his PhD thesis entitled: Inter-relação entre smells - Uma análise de Large Class, Complex Class e Clone! March 25.

The paper "Key Classes in Object-Oriented Systems: Detection and Assessment" has been accepted at the Int'l Journal of Software Engineering and Knowledge Engineering with Liliane Vale and Marcelo Maia! March 25.

The paper "Bootstrapping Cookbooks for APIs from Crowd Knowledge on Stack Overflow" has been accepted at the Information and Software Technology, with Lucas Souza, Eduardo Campos, Fernanda Madeiral, Klérisson Paixão, Adriano Rocha and Marcelo Maia!!!! March 18.

The paper "Co-Change Patterns: A Large Scale Empirical Study" has been accepted at the Journal of Systems and Software, with Luciana Silva, Marco Túlio Valente e Marcelo Maia! March 14.

Fernanda Madeiral has defended her PhD thesis entitled: On Benchmarks of Bugs for Studies in Automatic Program Repair! March 11.

The paper Recommending Comprehensive Solutions for Programming Tasks by Mining Crowd Knowledge with Rodrigo Fernandes, Chanchal Roy, Masudur Rahman, Kevin Schneider, Klérisson Paixão, and Marcelo Maia has been accepted as *a full paper* for inclusion in the Technical Research Track of ICPC 2019 in Montreal!!!.  March 07.

Our journal-first systematic literature review on bad smells published at IEEE TSE with Elder Sobrinho, Andrea De Lucia, and Marcelo Maia has been accepted for presentation at ICSE'2019 in Montreal!!!!

Marcelo Maia has been awarded with a Productivity Scholarship from CNPq 2018... Bolsa PQ - Produtividade em Pesquisa!

Marcelo Maia has been awarded within the Programa Pesquisador Mineiro XII-2018!!!

The paper "Bears: an Extensible Java Bug Benchmark for Automatic Program Repair Studies" has been accepted at SANER'2019 in the research track, with Fernanda Madeiral, Simon Urli, Marcelo Maia and Martin Monperrus!!! 

The paper "A systematic literature review on bad smells: 5 W's: which, when, what, who, where" has been accepted at IEEE Transactions on Software Engineering - TSE with Elder Sobrinho, Andrea De Lucia, and Marcelo Maia!!!!

Marcus Adriano, former undergraduate student, presented his scientific initiation work at the National Science and Technology Week 2018 at UFU: A study on mining patches for Android fragmentation issues.

The paper Towards an automated approach for bug fix pattern detection has been awarded as the BEST PAPER at VEM'2018 with Fernanda Madeiral, Thomas Durieux, Victor Sobreira, and Marcelo Maia. September, 2018.

@Marcelo  Maia has opened VEM'2018 with the Keynote: "The promises and perils of mining...". The talk reported the history of LASCAM on the land of minng software repositories, and the related challenges to strategically organize the team on that theme. September, 2018.

@Rodrigo  Fernandes has started a internship with prof. Chanchal Roy, University of Saskatchewan, Canada. September, 2018.

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Bad Smells: Which, When, What, Who, Where

This most comprehensive systematic literature review ever on bad smells includes 351 papers ranging from 1992 to 2017. We show the prevalence of smells in studies, the chronology, the main findings, the shape of collaborations, challenges and much ...more

Bears - A Bug Benchmark for Automatic Repair Studies

The Bears-Benchmark, or just Bears, is a benchmark of bugs collected from Java open-source projects hosted on GitHub through a process that scans pairs of builds from Travis Continuous Integration and reproduces bugs (by test failure) and their patches (passing test suite). ...more

Defects4J Dissection

Defects4J Dissection presents data to help researchers and practitioners to better understand the Defects4J bug dataset. ...more

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