This Dataset contains data for performing fault-proneness, defect prediction or any other kind of research for ~200 projects. I will keep on expanding this dataset with data for more projects for as long as feasible. data also available on https://github.com/grimasta/SERDat/</p
Developers have to select appropriate tools, methods and approaches in order to efficiently reproduc...
This dataset is about a systematic review of unsupervised learning techniques for software defect pr...
This is a collection of defect datasets for the software engineering research community. This collec...
Software code life cycle is characterized by continuous changes requiring a great effort to perform ...
Dataset used for paper "Issues-Driven Features for Software Fault Prediction". The dataset...
This data set contains the results of an extensive, systematic literature review on the use of machi...
Dataset for the paper "A Mixed-Criticality Approach to Fault Tolerance: Integrating Schedulability a...
This dataset contains all data collected to conduct the studies in Chapter 3 "Fine-Grained Just-In-T...
This paper describes a study performed in an industrial setting that attempts to build predictive mo...
Context: Software fault prediction has been an important research topic in the software engineering ...
Fault-proneness of a software module is the probability that the module contains faults. To predict ...
This is the dataset for our study of variability warnings and bugs. Our raw data was much too large ...
Background: Fault prediction is a key problem in software engineering domain. In recent years, an in...
Context: Continuous Integration (CI) is a DevOps technique which is widely used in practice. Studies...
Most software fault proneness prediction techniques utilize machine learning models which act as bla...
Developers have to select appropriate tools, methods and approaches in order to efficiently reproduc...
This dataset is about a systematic review of unsupervised learning techniques for software defect pr...
This is a collection of defect datasets for the software engineering research community. This collec...
Software code life cycle is characterized by continuous changes requiring a great effort to perform ...
Dataset used for paper "Issues-Driven Features for Software Fault Prediction". The dataset...
This data set contains the results of an extensive, systematic literature review on the use of machi...
Dataset for the paper "A Mixed-Criticality Approach to Fault Tolerance: Integrating Schedulability a...
This dataset contains all data collected to conduct the studies in Chapter 3 "Fine-Grained Just-In-T...
This paper describes a study performed in an industrial setting that attempts to build predictive mo...
Context: Software fault prediction has been an important research topic in the software engineering ...
Fault-proneness of a software module is the probability that the module contains faults. To predict ...
This is the dataset for our study of variability warnings and bugs. Our raw data was much too large ...
Background: Fault prediction is a key problem in software engineering domain. In recent years, an in...
Context: Continuous Integration (CI) is a DevOps technique which is widely used in practice. Studies...
Most software fault proneness prediction techniques utilize machine learning models which act as bla...
Developers have to select appropriate tools, methods and approaches in order to efficiently reproduc...
This dataset is about a systematic review of unsupervised learning techniques for software defect pr...
This is a collection of defect datasets for the software engineering research community. This collec...