This artifact includes the datasets used for Learning Realistic Mutations: Bug Creation for Neural Bug Detectors. Included are preprocessed Java datasets. Using CodeSearchNet as a starting point, the datasets are seeded with bugs of a specific bug type. We distinguish Binary operator bugs, VarMisuse bugs and Function misuses. For each bug type, we employed three level of mutator: weak, strong and contextual. In addition, we also include validation sets, which are used during experiments to validate the bug detection models, but do not relate to experiment results reported in the study. For each bug type, we also included the real world benchmark as test sets. For Python and JavaScript, we include the datasets preprocessed by the context...
Background: Bug prediction helps developers steer maintenance activities towards the buggy parts of ...
Artifact for "Neural Bug Detectors, Comparable to Software Developers?" Abstract: Debugging, that i...
For creating, optimizing, and evaluating our statistical model, we used the Public Unified Bug Datas...
Real bug fixes found in open source repositories seem to be the perfect source for learning to local...
A Public Unified Bug Dataset for Java and its Assessment Regarding Metrics and Bug Prediction. Onli...
Artifact for "Are Neural Bug Detectors Comparable to Software Developers on Variable Misuse Bugs?" ...
Extract the archive The archive contains a README.md that explains how to install the requirements ...
Bugs are inescapable during software development due to frequent code changes, tight deadlines, etc....
This data set provides 12,000 images for individual pest bugs in sugar cane crops, collected from pi...
International audienceWell-designed and publicly available datasets of bugs are an invaluable asset ...
Bug report assignment is an important part of software maintenance. In particular, incorrect assignm...
Bug report assignment is an important part of software maintenance. In particular, incorrect assignm...
The ManySStuBs4J corpus is a collection of simple fixes to Java bugs, designed for evaluating progra...
This dataset contains all the data that could not be included in the original repository: https://gi...
Bug datasets have been created and used by many researchers to build and validate novel bug predicti...
Background: Bug prediction helps developers steer maintenance activities towards the buggy parts of ...
Artifact for "Neural Bug Detectors, Comparable to Software Developers?" Abstract: Debugging, that i...
For creating, optimizing, and evaluating our statistical model, we used the Public Unified Bug Datas...
Real bug fixes found in open source repositories seem to be the perfect source for learning to local...
A Public Unified Bug Dataset for Java and its Assessment Regarding Metrics and Bug Prediction. Onli...
Artifact for "Are Neural Bug Detectors Comparable to Software Developers on Variable Misuse Bugs?" ...
Extract the archive The archive contains a README.md that explains how to install the requirements ...
Bugs are inescapable during software development due to frequent code changes, tight deadlines, etc....
This data set provides 12,000 images for individual pest bugs in sugar cane crops, collected from pi...
International audienceWell-designed and publicly available datasets of bugs are an invaluable asset ...
Bug report assignment is an important part of software maintenance. In particular, incorrect assignm...
Bug report assignment is an important part of software maintenance. In particular, incorrect assignm...
The ManySStuBs4J corpus is a collection of simple fixes to Java bugs, designed for evaluating progra...
This dataset contains all the data that could not be included in the original repository: https://gi...
Bug datasets have been created and used by many researchers to build and validate novel bug predicti...
Background: Bug prediction helps developers steer maintenance activities towards the buggy parts of ...
Artifact for "Neural Bug Detectors, Comparable to Software Developers?" Abstract: Debugging, that i...
For creating, optimizing, and evaluating our statistical model, we used the Public Unified Bug Datas...