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20152023
most citedBears: An Extensible Java Bug Benchmark for Automatic Program Repair Studies

103 citations · 116 across the 8 of their papers we have counts for

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9 papers · 1 filter

cs.SE2023

How do Developers Improve Code Readability? An Empirical Study of Pull Requests

Carlos Eduardo C. Dantas, Adriano M. Rocha, Marcelo A. Maia

Readability models and tools have been proposed to measure the effort to read code. However, these models are not completely able to capture the quality improvements in code as per…

cs.SE20214 cited

On the Interplay of Smells Large Class, Complex Class and Duplicate Code

Elder Vicente de Paulo Sobrinho, Marcelo de Almeida Maia

Bad smells have been defined to describe potential problems in code, possibly pointing out refactoring opportunities. Several empirical studies have highlighted that smells have a…

cs.SE20212 cited

Towards a question answering assistant for software development using a transformer-based language model

Liliane do Nascimento Vale, Marcelo de Almeida Maia

Question answering platforms, such as Stack Overflow, have impacted substantially how developers search for solutions for their programming problems. The crowd knowledge content av…

cs.SE2019

Bootstrapping Cookbooks for APIs from Crowd Knowledge on Stack Overflow

Lucas B. L. Souza, Eduardo C. Campos, Fernanda Madeiral +3

Well established libraries typically have API documentation. However, they frequently lack examples and explanations, possibly making difficult their effective reuse. Stack Overflo…

cs.SE2019

Recommending Comprehensive Solutions for Programming Tasks by Mining Crowd Knowledge

Rodrigo F. G. Silva, Chanchal K. Roy, Mohammad Masudur Rahman +3

Developers often search for relevant code examples on the web for their programming tasks. Unfortunately, they face two major problems. First, the search is impaired due to a lexic…

cs.SE2019103 cited

Bears: An Extensible Java Bug Benchmark for Automatic Program Repair Studies

Fernanda Madeiral, Simon Urli, Marcelo Maia +1

Benchmarks of bugs are essential to empirically evaluate automatic program repair tools. In this paper, we present Bears, a project for collecting and storing bugs into an extensib…