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Factors and actors leading to the adoption of a JavaScript framework

Authors: Amantia Pano; Daniel Graziotin; Pekka Abrahamsson;

Factors and actors leading to the adoption of a JavaScript framework

Abstract

The increasing popularity of JavaScript has led to a variety of JavaScript frameworks that aim to help developers to address programming tasks. However, the number of JavaScript frameworks has risen rapidly to thousands of versions. It is challenging for practitioners to identify the frameworks that best fit their needs and to develop new ones which fit such needs. Furthermore, there is a lack of knowledge regarding what drives developers towards the choice. This paper explores the factors and actors that lead to the choice of a JavaScript framework. We conducted a qualitative interpretive study of semi-structured interviews. We interviewed 18 decision makers regarding the JavaScript framework selection, up to reaching theoretical saturation. Through coding the interview responses, we offer a model of desirable JavaScript framework adoption factors. The factors are grouped into categories that are derived via the Unified Theory of Acceptance and Use of Technology. The factors are performance expectancy (performance, size), effort expectancy (automatization, learnability, complexity, understandability), social influence (competitor analysis, collegial advice, community size, community responsiveness), facilitating conditions (suitability, updates, modularity, isolation, extensibility), and price value. A combination of four actors, which are customer, developer, team, and team leader, leads to the choice. Our model contributes to the body of knowledge related to the adoption of technology by software engineers. As a practical implication, our model is useful for decision makers when evaluating JavaScript frameworks, as well as for developers for producing desirable frameworks.

34 pages, 2 figures. Minor Revisions at Empirical Software Engineering journal

Keywords

JavaScript, FOS: Computer and information sciences, human aspects of software development, päätöksenteko, tulkinta, laadullinen tutkimus, programming frameworks, technology adoption, ohjelmointikielet, Software Engineering (cs.SE), Computer Science - Software Engineering, interpretivism, teknologia, ohjelmistokehitys, kvalitatiivinen tutkimus, omaksuminen

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    24
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Top 10%
Top 10%
Green
bronze