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Researcher bias: The use of machine learning in software defect prediction
Background. The ability to predict defect-prone software components would be valuable.
Consequently, there have been many empirical studies to evaluate the performance of …
Consequently, there have been many empirical studies to evaluate the performance of …
A critical review of" automatic patch generation learned from human-written patches": Essay on the problem statement and the evaluation of automatic software repair
M Monperrus - Proceedings of the 36th International Conference on …, 2014 - dl.acm.org
At ICSE'2013, there was the first session ever dedicated to automatic program repair. In this
session, Kim et al. presented PAR, a novel template-based approach for fixing Java bugs …
session, Kim et al. presented PAR, a novel template-based approach for fixing Java bugs …
The impact of automated parameter optimization on defect prediction models
Defect prediction models-classifiers that identify defect-prone software modules-have
configurable parameters that control their characteristics (eg, the number of trees in a …
configurable parameters that control their characteristics (eg, the number of trees in a …
The promises and perils of mining github
With over 10 million git repositories, GitHub is becoming one of the most important source of
software artifacts on the Internet. Researchers are starting to mine the information stored in …
software artifacts on the Internet. Researchers are starting to mine the information stored in …
History driven program repair
Effective automated program repair techniques have great potential to reduce the costs of
debugging and maintenance. Previously proposed automated program repair (APR) …
debugging and maintenance. Previously proposed automated program repair (APR) …
Transfer defect learning
Many software defect prediction approaches have been proposed and most are effective in
within-project prediction settings. However, for new projects or projects with limited training …
within-project prediction settings. However, for new projects or projects with limited training …
Is the cure worse than the disease? overfitting in automated program repair
Automated program repair has shown promise for reducing the significant manual effort
debugging requires. This paper addresses a deficit of earlier evaluations of automated …
debugging requires. This paper addresses a deficit of earlier evaluations of automated …
An in-depth study of the promises and perils of mining GitHub
With over 10 million git repositories, GitHub is becoming one of the most important sources
of software artifacts on the Internet. Researchers mine the information stored in GitHub's …
of software artifacts on the Internet. Researchers mine the information stored in GitHub's …
Managing bias and unfairness in data for decision support: a survey of machine learning and data engineering approaches to identify and mitigate bias and …
The increasing use of data-driven decision support systems in industry and governments is
accompanied by the discovery of a plethora of bias and unfairness issues in the outputs of …
accompanied by the discovery of a plethora of bias and unfairness issues in the outputs of …
The ManyBugs and IntroClass benchmarks for automated repair of C programs
The field of automated software repair lacks a set of common benchmark problems.
Although benchmark sets are used widely throughout computer science, existing …
Although benchmark sets are used widely throughout computer science, existing …