The selection of third-party libraries is an essential element of virtually any software development project. However, deciding which libraries to choose is a challenging practical problem. Selecting the wrong library can severely impact a software project in terms of cost, time, and development effort, with the severity of the impact depending on the role of the library in the software architecture, among others. Despite the importance of following a careful library selection process, in practice, the selection of third-party libraries is still conducted in an ad-hoc manner, where dozens of factors play an influential role in the decision.
In this paper, we study the factors that influence the selection process of libraries, as perceived by industry developers. To that aim, we perform a cross-sectional interview study with 16 developers from 11 different businesses and survey 115 developers that are involved in the selection of libraries. We systematically devised a comprehensive set of 26 technical, human, and economic factors that developers take into consideration when selecting a software library. Eight of these factors are new to the literature. We explain each of these factors and how they play a role in the decision. Finally, we discuss the implications of our work to library maintainers, potential library users, package manager developers, and empirical software engineering researchers.@en

Modern software projects consist of more than just code: teams follow development processes, the code runs on servers or mobile phones and produces run time logs and users talk about the software in forums like StackOverflow and Twitter and rate it on app stores. Insights stemming from the real-time analysis of combined software engineering data can help software practitioners to conduct faster decision-making. With the development of CodeFeedr, a Real-time Software Analytics Platform, we aim to make software analytics a core feedback loop for software engineering projects. CodeFeedr's vision entails: (1) The ability to unify archival and current software analytics data under a single query language, and (2) The feasibility to apply new techniques and methods for high-level aggregation and summarization of near real-time information on software development. In this paper, we outline three use cases where our platform is expected to have a significant impact on the quality and speed of decision making; dependency management, productivity analytics, and run-time error feedback.@en