How do developers react to API evolution? A large-scale empirical study

Abstract

Software engineering research now considers that no system is an island, but it is part of an ecosystem involving other systems, developers, and users. When a framework or a library evolves, its clients often must adapt. For example, client developers might need to adapt to functionalities, client systems might need to be adapted to a new API, and client users might need to adapt to a new user interface. The consequences of these changes are yet unclear: what proportion of the ecosystem might be expected to react, how long might it take for a change to diffuse in the ecosystem, do all clients react in the same way? This paper reports an exploratory study aimed at observing API evolution and its impact on a large software ecosystem, Pharo, which has about 3,600 distinct systems, and six years of evolution. We analyze 118 API changes in the context of method replacement and suggestion, and answer research questions regarding the magnitude, duration, extension, and consistency of such changes in the ecosystem. The results of this study help to characterize the impact of API evolution in large software ecosystems and provide the basis to better understand how such impact can be alleviated.

On the Evolution of Technical Lag in the npm Package Dependency Network

“…Robbes et al [17] empirically studied the ripple effect of deprecated APIs in the Smalltalk ecosystem. Hora et al [18] explored the evolution of the Pharo ecosystem. This line of research differs from our own by its level of granularity: by analysing fine-grained API changes (e.g., at method level), it becomes possible to assess the effort and impact required to upgrade client applications to newer API versions.…”

Practitioner Views on the Interrelation of Microservice APIs and Domain-Driven Design: A Grey Literature Study Based on Grounded Theory

“…There are a number of empirical study on API documentation [11]- [13] which emphasize roles such as API documenter and API designer in this context. The scientific literature has studied various API quality attributes, such as accessibility [14], stability [15], compatibility [16], [17], evolvability [18]- [20], and usability [21]- [23].…”

Stability Metrics for Continuous Integration of Service-Oriented Systems

“…We focus in this paper on the first nine types of evolution changes, leaving as future work the last two types of changes. Even if there are empirical studies on how developers react to API evolution [21], these studies do not model the algorithmic steps of the client evolution. To cover this gap, we specify in Alg.…”