On the Diversity of Software Package Popularity Metrics: An Empirical Study of npm

Abstract

Software systems often leverage on open source software libraries to reuse functionalities. Such libraries are readily available through software package managers like npm for JavaScript. Due to the huge amount of packages available in such package distributions, developers often decide to rely on or contribute to a software package based on its popularity. Moreover, it is a common practice for researchers to depend on popularity metrics for data sampling and choosing the right candidates for their studies. However, the meaning of popularity is relative and can be defined and measured in a diversity of ways, that might produce different outcomes even when considered for the same studies. In this paper, we show evidence of how different is the meaning of popularity in software engineering research. Moreover, we empirically analyse the relationship between different software popularity measures. As a case study, for a large dataset of 175k npm packages, we computed and extracted 9 different popularity metrics from three open source tracking systems: libraries.io, npmjs.com and GitHub. We found that indeed popularity can be measured with different unrelated metrics, each metric can be defined within a specific context. This indicates a need for a generic framework that would use a portfolio of popularity metrics drawing from different concepts.

Investigating diversity and impact of the popularity metrics for ranking software packages

“…In fact, every study comes up with a different metric. This study extends the work of Zerouali et al 2 to explore the diversity of different popularity metrics by using cluster analysis anticipating that clustering will reveal more details about the independence of these metrics. Furthermore, to the best of our knowledge, there is no research work that focuses on examining the relation between the popularity and development activity of software packages.…”

“…Zerouali et al 2 examined 175k npm packages, by extracting nine popularity metrics from three open-source tracking systems (libraries.io, npmjs.com, and GitHub). They aimed to find the relationship between the popularity metrics, with a broad focus on raising the awareness of risks associated with the use of these popularity metrics.…”

“…Zerouali et al 2 analyzed the diversity of popularity metrics for npm software packages. The authors examined nine popularity metrics extracted from libraries.io, npmjs.com, and GitHub on a data set of 195k software packages.…”

“…Due to a large number of metrics for measuring popularity of software packages from technical as well as social viewpoints, the need is felt for devising a software popularity model on the same lines as the software quality model, or the software reliability model. 2,3 In this paper, we attempt to create a package popularity model by aggregating existing popularity metrics. First, a set of independent metrics is chosen, and then the random forests method is employed to find the importance of individual metrics in determining the popularity of a software package.…”

The Emergence of Software Diversity in Maven Central

“…Because it is duallicense, many OSS libraries avoid to depend on it, but other closed-source software are still using it and there is no way to quantify their number. However, as suggested in previous studies, software popularity can be measured in a variety of ways, depending on different factors such as social or technical aspects [24]. Another concern relates to the fact that conventions on semantic versioning are not really taken well into account by library maintainers [25].…”