Automatically Finding Hidden Industrial Criteria used in Test Selection

Abstract

In this paper we propose a way to find weights of a ranking function semi-automatically. From the manual choices made by (experienced) human test architects, our idea is to propose an optimization model that tries to find the necessary weights automatically. We present some experiments by encoding our optimization model in the Z3 SMT solver and using real Motorola Mobility 1 data.

HSP: A hybrid selection and prioritisation of regression test cases based on information retrieval and code coverage applied on an industrial case study

“…Yet, we also consider investigating prioritisation strategies reported in Magalhães et al [2016b], regarding coverage and bugs found. We have presented in this work ways to prioritise test cases through information retrieval or code coverage.…”