Monitoring the Execution of 14K Tests: Methods Tend to Have One Path that Is Significantly More Executed
The literature has provided evidence that developers are likely to test some behaviors of the program and avoid other ones. Despite this observation, we still lack empirical evidence from real-world systems. In this paper, we propose to automatically identify the tested paths of a method as a way to detect the method’s behaviors. Then, we provide an empirical study to assess the tested paths quantitatively. We monitor the execution of 14,177 tests from 25 real-world Python systems and assess 11,425 tested paths from 2,357 methods. Overall, our empirical study shows that one tested path is prevalent and receives most of the calls, while others are significantly less executed. We find that the most frequently executed tested path of a method has 4x more calls than the second one. Based on these findings, we discuss practical implications for practitioners and researchers and future research directions.
Andre Hora is currently a professor in the Department of Computer Science at UFMG, Brazil. He received his PhD in Computer Science at the University of Lille, France. He was a Postdoctoral researcher at the ASERG group. He worked as a software engineer at Inria (Lille, France) and was research intern at Siemens (Erlangen, Germany).
Thu 18 JulDisplayed time zone: Brasilia, Distrito Federal, Brazil change
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16:18 9mTalk | Monitoring the Execution of 14K Tests: Methods Tend to Have One Path that Is Significantly More Executed Ideas, Visions and Reflections Andre Hora UFMG Pre-print Media Attached | ||
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