The accurate identification of defect-inducing commits representsa key problem for researchers interested in studying the naturalness of defects and defining defect prediction models. To tacklethis problem, software engineering researchers have relied on andproposed several implementations of the well-known SliwerskiZimmermann-Zeller (SZZ) algorithm. Despite its popularity andwide usage, no open-source, publicly available, and web-accessibleimplementation of the algorithm has been proposed so far. In thispaper, we prototype and make available one such implementationfor further use by practitioners and researchers alike. The evaluation of the proposed prototype showed competitive results and laysthe foundation for future work. This paper out...
This archive file contains the dataset generated from project-KB by applying our two-phase improved ...
We present in this paper several solutions to the challenging task of clustering software defect rep...
Context: Defect prediction research is based on a small number of defect datasets and most are at cl...
Context The SZZ algorithm is the de facto standard for labeling bug fixing commits and finding indu...
In the multi-commit development model, programmers complete tasks (e.g., implementing a feature) by ...
Data from software repositories are a very useful asset to building dierent kinds of models and reco...
Two recent studies explicitly recommend labeling defective classes in releases using the affected ve...
This is the replication package for our article "Problems with SZZ and Features: An empirical study ...
Software defects are the major cause for system failures. To effectively design tools and provide su...
The goal of the PROMISE workshop is to create a set of re-producible software engineering experiment...
Software defect prediction is one of the most active research areas in software engineering. Defect ...
Abstract- There are several defect-tracking tools developed by the open source computing community, ...
The number of research papers on defect prediction has sharply increased for the last decade or so. ...
Dataset used for paper "Issues-Driven Features for Software Fault Prediction". The dataset...
The increasing complexity of today's software requires the contribution of thousands of developers. ...
This archive file contains the dataset generated from project-KB by applying our two-phase improved ...
We present in this paper several solutions to the challenging task of clustering software defect rep...
Context: Defect prediction research is based on a small number of defect datasets and most are at cl...
Context The SZZ algorithm is the de facto standard for labeling bug fixing commits and finding indu...
In the multi-commit development model, programmers complete tasks (e.g., implementing a feature) by ...
Data from software repositories are a very useful asset to building dierent kinds of models and reco...
Two recent studies explicitly recommend labeling defective classes in releases using the affected ve...
This is the replication package for our article "Problems with SZZ and Features: An empirical study ...
Software defects are the major cause for system failures. To effectively design tools and provide su...
The goal of the PROMISE workshop is to create a set of re-producible software engineering experiment...
Software defect prediction is one of the most active research areas in software engineering. Defect ...
Abstract- There are several defect-tracking tools developed by the open source computing community, ...
The number of research papers on defect prediction has sharply increased for the last decade or so. ...
Dataset used for paper "Issues-Driven Features for Software Fault Prediction". The dataset...
The increasing complexity of today's software requires the contribution of thousands of developers. ...
This archive file contains the dataset generated from project-KB by applying our two-phase improved ...
We present in this paper several solutions to the challenging task of clustering software defect rep...
Context: Defect prediction research is based on a small number of defect datasets and most are at cl...