Abstract
Modern software development increasingly depends on third-party libraries to boost productivity and quality. This development is complex and requires specialists with knowledge in several technologies, such as the nowadays libraries. Such complexity turns it extremely challenging to deliver quality software, given the pressure. For this purpose, it is necessary to identify and hire qualified developers, to obtain a good team, both in open source and proprietary systems. For these reasons, enterprise and open source projects try to build teams composed of highly skilled developers in specific libraries. However, their identification may not be trivial. Despite this fact, we still lack procedures to assess developers skills in widely popular libraries. In this paper, we first argue that source code activities can identify software developers’ hard skills, such as library expertise. We then evaluate a mining-based strategy to reduce the search space to identify library experts. To achieve our goal, we selected the 9 most popular Java libraries and 6 libraries for microservices (i.e., 15 libraries in total). We assessed the skills of more than 1.5 million developers in these libraries by analyzing their commits in more than 17 K Java projects on GitHub. We evaluated the results by applying two surveys with 158 developers. First, with 137 library expert candidates, they observed 63% precision for popular Java libraries’ used strategy. Second, we observe a precision of at least 71% for 21 library experts in microservices. These low precision values suggest space for further improvements in the evaluated strategy.
Highlights
Software development has become increasingly complex, both in opensource and proprietary systems (Damasiotis et al, 2017)
We can see a significant increase in the use of microservices architectural style since 2014 (Klock et al, 2017), which can be verified in the serviceoriented software industry where the usage of microservices has been far superior when com pared to other software architecture models (Alshuqayran et al, 2016)
We developed a heuristic to count the amount of lines of code (LOC) related to a specific library
Summary
Software development has become increasingly complex, both in opensource and proprietary systems (Damasiotis et al, 2017). Providing a more reliable way of identifying developers’ skills can help project managers make the right decision when hiring or attracting the right developers for an opensource project. The task of finding experts in spe cific technologies is especially complex, despite the exis tence of businessoriented social networks, such as LinkedIn, where developers write about their attributes and qualifica tions. This type of platform is commonly used for the online recruitment of professionals. Some individuals can overvalue their skills and omit some skills in a selfauthored curriculum
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