User-intensive software, such asWeb andmobile applications, heavily depends on the interactions with large and unknown populations of users. Knowing the preferences and behaviors of these populations is crucial for the success of this class of systems. A/B testing is an increasingly popular technique that supports the iterative development of userintensive software based on controlled experiments performed on live users. However, as currently performed, A/B testing is a time consuming, error prone and costly manual activity. In this paper, we investigate a novel approach to automate A/B testing. More specifically, we rephrase A/B testing as a search-based software engineering problem and we propose an initial approach that supports automated A/B testing through aspect-oriented programming and genetic algorithms.
Search-Based Software Engineering - 6th International Symposium, SSBSE 2014, Proceedings
TAMBURRELLI, GIORDANO;MARGARA, ALESSANDRO
2014-01-01
Abstract
User-intensive software, such asWeb andmobile applications, heavily depends on the interactions with large and unknown populations of users. Knowing the preferences and behaviors of these populations is crucial for the success of this class of systems. A/B testing is an increasingly popular technique that supports the iterative development of userintensive software based on controlled experiments performed on live users. However, as currently performed, A/B testing is a time consuming, error prone and costly manual activity. In this paper, we investigate a novel approach to automate A/B testing. More specifically, we rephrase A/B testing as a search-based software engineering problem and we propose an initial approach that supports automated A/B testing through aspect-oriented programming and genetic algorithms.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
