Software development projects have increasingly been adopting new practices, such as continuous delivery and deployment to enable rapid delivery of new features to end users. Tools that are commonly utilized with these practices generate a vast amount of data concerning various development events. Analysis of the data provides a lightweight data driven view on the software process. We present an efficient way of visualizing software process data to provide a good overall view on the features and potential problems of the process. We use the visualization in a case project that has become more agile by applying continuous integration and delivery together with development and infrastructure automation. We compare data visualizations with information gathered from the development team and describe how the evolution can be understood through our visualizations. The case project is a good example of how a change from a traditional long cycle development to a rapid cycle DevOps culture can actually be made in a few years. However, the results show that the team has to focus on the process improvement continuously in order to maintain continuous delivery all the time. As the main contribution, we present a lightweight way to software process visualization. Moreover, we discuss how such a heuristic can be used to track the characteristics of the target process.

Context: In continuous delivery, the aim is that every feature passes through the integration and deployment pipeline, resulting in an immediately deployable product. This practice has been proposed to accelerate value delivery, improve software quality and increase developer productivity.

Modern software organizations invest substantial effort in building and automating their tool chain. The goal is to maximize both the speed of development, and how rapidly new software is deployed. This paper presents results from a descriptive and exploratory single case study from an ongoing project of Finnish company Solita. Based on data from version control and production logs, we investigate the feature flow in the project to study the effect of lean processes and the continuous deployment tool chain to waste produced by the deployment pipeline. We find that flow efficiency can be improved simply by minimizing the idle time the feature waits in the production process after its implementation has been finalized. This reduction of waste benefits both end users and developers -- the users get access to new features, and the developers receive timely feedback.

Software projects have usually a lot of software engineering data available in different kinds of repositories. This data can be mined and used for software process improvement purposes. In general, agile methodologies emphasize reflection, making problems visible, and learning from the past. As the human mind is powerful in interpreting visual representations, visualizations could help in recognizing problems and areas of improvement in an agile software development process. In this paper an action research approach was taken to carry out software process improvement in an industry project. The research resulted in a visualization of the issue management system's data. The visualizations were a tool to identify problems in the development process and to make them visible for all stakeholders. The results show that this kind of visual approach can be used successfully to point out problems in the process. The visualizations form a basis for communication on possible software process improvement.