Quality Assurance Awareness in Open Source Software Projects on GitHub

Software engineers employ a variety of approaches to ensure the quality of software systems, including software testing, modern code review, automated static analysis, build automation, and continuous integration. To make effective decisions regarding quality assurance (QA), software engineers need to have an awareness of (1) the QA approaches...

Recommender Systems for DevOps

The software development life cycle (SDLC) for a developer has increased in complexity and scale. With the advent of DevOps processes, the gap between development and operations teams reduced significantly. Developers are now expected to perform different roles from coding to operational support in the new model of software development. This...

On the Evaluation of NLP-based Models for Software Engineering

NLP-based models have been increasingly incorporated to address SE problems. These models are either employed in the SE domain with little to no change, or they are greatly tailored to source code and its unique characteristics. Many of these approaches are considered to be outperforming or complementing existing solutions. However, an important...

Data-Driven Extract Method Recommendations: A Study at ING

The sound identification of refactoring opportunities is still an open problem in software engineering. Recent studies have shown the effectiveness of machine learning models in recommending methods that should undergo different refactoring operations. In this work, we experiment with such approaches to identify methods that should undergo an...

Systematic Mapping Study on the Machine Learning Lifecycle

The development of artificial intelligence (AI) has made various industries eager to explore the benefits of AI. There is an increasing amount of research surrounding AI, most of which is centred on the development of new AI algorithms and techniques. However, the advent of AI is bringing an increasing set of practical problems related to AI...

Questions for Data Scientists in Software Engineering: A Replication

In 2014, a Microsoft study investigated the sort of questions that data science applied to software engineering should answer. This resulted in 145 questions that developers considered relevant for data scientists to answer, thus providing a research agenda to the community. Fast forward to five years, no further studies investigated whether the...

An Empirical Evaluation of Feedback-Driven Software Development

Software developers today crave for feedback, be it from their peers in the form of code review, static analysis tools like their compiler, or the local or remote execution of their tests in the Continuous Integration (CI) environment. With the advent of social coding sites such as GitHub and tight integration of CI services such as Travis CI,...

Human Handheld-Device Interaction: An Adaptive User Interface

The move to smaller, lighter and more powerful (mobile) handheld devices, whe-ther PDAs or smart-phones, looks like a trend that is building up speed. With numerous embedded technologies and wireless connectivity, the drift opens up unlimited opportunities in daily activities that are both more efficient and more exciting. Despite all these...