Together with many success stories, promises such as the increase in production speed and the improvement in stakeholders’ collaboration have contributed to making agile a transformation in the software industry in which many companies want to take part. However, driven either by a natural and expected evolution or by contextual factors that challenge the adoption of agile methods as prescribed by their creator(s), software processes in practice mutate into hybrids over time. Are these still agile? In this article, we investigate the question: what makes a software development method agile? We present an empirical study grounded in a large-scale international survey that aims to identify software development methods and practices that improve or tame agility. Based on 556 data points, we analyze the perceived degree of agility in the implementation of standard project disciplines and its relation to used development methods and practices. Our findings suggest that only a small number of participants operate their projects in a purely traditional or agile manner (under 15 percent). That said, most project disciplines and most practices show a clear trend towards increasing degrees of agility. Compared to the methods used to develop software, the selection of practices has a stronger effect on the degree of agility of a given discipline. Finally, there are no methods or practices that explicitly guarantee or prevent agility. We conclude that agility cannot be defined solely at the process level. Additional factors need to be taken into account when trying to implement or improve agility in a software company. Finally, we discuss the field of software process-related research in the light of our findings and present a roadmap for future research.

Abstract FinTech companies are challenging established financial institutions' dominance by offering the same products with a superior customer experience and delivering new features faster. The adoption of agile software development partially enables this competitive advantage. In response to this challenge, banks explore how they can improve their agile processes. LHV, a mid‐sized bank, uses agile practices but faces the challenge of further improvement to stay competitive with FinTech companies. In this article, we explore how LHV can improve its agile software development process. We conduct a case study at LHV where we first derive eight change proposals based on a literature review and interviews. Then, we report on how LHV implemented the change proposals and their perceived impact. Our results stress the importance of taking a coherent approach to improving agile processes by considering both business units and operations involved in the product life‐cycle. It is also necessary to align organizational structures to enable team autonomy by, for instance, decentralizing decision authority. Finally, it is beneficial to adapt agile practices to their context and have an IT architecture and technology supporting the agile approach.

Productivity in software development has been studied for a long time and is still a topic of interest. Many factors, ranging from team size to music listened by developers, have been studied regarding their effect on productivity. Surprisingly, little is known about how the dynamics of open-source projects that use agile practices are related to the productivity of the developer teams. Our study aims to close this gap by analyzing the productivity of open-source projects using measures that are popular in the context of agile software development. To do this, we study data from seven open-source projects and calculated both the individual velocity of developers and focus factor of teams per iteration. First, we applied statistical process control to identify iterations with out-of-control velocity and focus factor values. Then, we studied these iterations regarding four context factors that partly characterize the dynamics of open-source projects, i.e., iteration length, turnover of developers who left, turnover of new developers, and team stability index. Our results suggest that high team stability and low turnover are strongly associated with iterations showing high velocity.

Effort estimation is important to correctly plan the use of resources in a software project. In agile projects, a correct effort estimation helps decide which issues have to be fixed or finished during the next iteration. However, estimating issues can be a complex task and developers may make inaccurate estimates. Therefore, the use of automatic approaches that aim to support developers in the estimation process is worth to be studied. We explore the use of a predictive model that use developers' features to assign story points to issue reports. The performance of the model is compared with the performance of models based on features extracted from the text of issues. We assessed the models with different performance metrics including Accuracy, Mean Absolute Error, and Standardized Accuracy. The preliminary results show that the model that uses developers' features sightly outperforms the models based on text features, indicating a promising research direction.