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On the effectiveness of manual and automatic unit test generation: ten years later

Type of publication Peer-reviewed
Publikationsform Proceedings (peer-reviewed)
Author Serra Domenico, Grano Giovanni, Palomba Fabio, Ferrucci Filomena, Gall Harald C., Bacchelli Alberto,
Project SURF-MobileAppsData
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Proceedings (peer-reviewed)

Editor , Adams Bram; , Storey Margaret-Anne D.; , Haiduc Sonia
Page(s) 121 - 125
Title of proceedings Proceedings of the 16th Int Conf on Mining Software Repositories, MSR 2019
DOI 10.1109/msr.2019.00028

Open Access

URL https://www.zora.uzh.ch/id/eprint/171578/
Type of Open Access Repository (Green Open Access)

Abstract

Good unit tests play a paramount role when it comes to foster and evaluate software quality. However, writing effective tests is an extremely costly and time consuming practice. To reduce such a burden for developers, researchers devised ingenious techniques to automatically generate test suite for existing code bases. Nevertheless, how automatically generated test cases fare against manually written ones is an open research question. In 2008, Bacchelli et.al. conducted an initial case study comparing automatic and manually generated test suites. Since in the last ten years we have witnessed a huge amount of work on novel approaches and tools for automatic test generation, in this paper we revise their study using current tools as well as complementing their research method by evaluating these tools' ability in finding regressions.
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