DocumentCode :
3685953
Title :
Feature lifecycles as they spread, migrate, remain, and die in App Stores
Author :
Federica Sarro;Afnan A. Al-Subaihin;Mark Harman;Yue Jia;William Martin;Yuanyuan Zhang
Author_Institution :
CREST, Department of Computer Science, University College London, UK
fYear :
2015
Firstpage :
76
Lastpage :
85
Abstract :
We introduce a theoretical characterisation of feature lifecycles in app stores, to help app developers to identify trends and to find undiscovered requirements. To illustrate and motivate app feature lifecycle analysis, we use our theory to empirically analyse the migratory and non-migratory behaviours of 4,053 non-free features from two App Stores (Samsung and BlackBerry). The results reveal that, in both stores, intransitive features (those that neither migrate nor die out) exhibit significantly different behaviours with regard to important properties, such as their price. Further correlation analysis also highlights differences between trends relating price, rating, and popularity. Our results indicate that feature lifecycle analysis can yield insights that may also help developers to understand feature behaviours and attribute relationships.
Keywords :
"Feature extraction","Data mining","Databases","Software","HTML","Market research","Natural language processing"
Publisher :
ieee
Conference_Titel :
Requirements Engineering Conference (RE), 2015 IEEE 23rd International
Type :
conf
DOI :
10.1109/RE.2015.7320410
Filename :
7320410
Link To Document :
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