Related papers: Continuous Defect Prediction: The Idea and a Relat…
In this paper, we present ApacheJIT, a large dataset for Just-In-Time defect prediction. ApacheJIT consists of clean and bug-inducing software changes in popular Apache projects. ApacheJIT has a total of 106,674 commits (28,239 bug-inducing…
The software industry is experiencing a surge in the adoption of Continuous Integration (CI) practices, both in commercial and open-source environments. CI practices facilitate the seamless integration of code changes by employing automated…
Defect prediction is one of the most popular research topics due to its potential to minimize software quality assurance efforts. Existing approaches have examined defect prediction from various perspectives such as complexity and developer…
In current research, there are contrasting results about the applicability of software source code metrics as features for defect prediction models. The goal of the paper is to evaluate the adoption of software metrics in models for…
Continuous Integration (CI) provides early feedback by automatically building software, but long build durations can hinder developer productivity. CI services use caching to speed up builds by reusing infrequently changing artifacts, yet…
Background: Much research has been conducted to investigate the impact of Continuous Integration (CI) on the productivity and quality of open-source projects. Most of studies have analyzed the impact of adopting a CI server service (e.g,…
Context: The effectiveness of data selection approaches in improving the performance of cross project defect prediction(CPDP) has been shown in multiple previous studies. Beside that, replication studies play an important role in the…
Cross-Project-Defect Prediction as a sub-topic of defect prediction in general has become a popular topic in research. In this article, we present a systematic mapping study with the focus on CPDP, for which we found 50 publications. We…
Training machine learning approaches for vulnerability identification and producing reliable tools to assist developers in implementing quality software -- free of vulnerabilities -- is challenging due to the lack of large datasets and real…
Continuous Integration (CI) is a software development practice that builds and tests software frequently (e.g., at every push). One main motivator to adopt CI is the potential to deliver software functionalities more quickly than not using…
The growing popularity of machine learning (ML) and the integration of ML components with other software artifacts has led to the use of continuous integration and delivery (CI/CD) tools, such as Travis CI, GitHub Actions, etc. that enable…
Defect prediction can be a powerful tool to guide the use of quality assurance resources. In recent years, many researchers focused on the problem of Cross-Project Defect Prediction (CPDP), i.e., the creation of prediction models based on…
Cross-project defect prediction (CPDP) aims to use data from external projects as historical data may not be available from the same project. In CPDP, deciding on a particular historical project to build a training model can be difficult.…
Software defect prediction heavily relies on the metrics collected from software projects. Earlier studies often used machine learning techniques to build, validate, and improve bug prediction models using either a set of metrics collected…
Predicting the number of defects in a project is critical for project test managers to allocate budget, resources, and schedule for testing, support and maintenance efforts. Software Defect Prediction models predict the number of defects in…
We present Curated Industrial Developer Repository (CIDR), a large-scale dataset of real-world software repositories collected through direct collaboration with 12 industrial partner organizations. The dataset comprises 2,440 repositories…
In a critical software system, the testers have to spend an enormous amount of time and effort to maintain the software due to the continuous occurrence of defects. Among such defects, some severe defects may adversely affect the software.…
Just-in-time defect prediction assigns a defect risk to each new change to a software repository in order to prioritize review and testing efforts. Over the last decades different approaches were proposed in literature to craft more…
Numerous articles emphasize the benefits of implementing Continuous Integration and Delivery (CI/CD) pipelines in software development. These pipelines are expected to improve the reputation of a project and decrease the number of commits…
Continuous Integration (CI) requires efficient regression testing to ensure software quality without significantly delaying its CI builds. This warrants the need for techniques to reduce regression testing time, such as Test Case…