The birth of cloud-based development environments makes available an increasing number of data coming out from the interaction of different developers with a diverse level of expertise. This data, if opportunely captured and analyzed, can be useful to understand how developers head the coding activities and can suggest members of developers community how to improve their performances. This paper presents a framework allowing to generate event logs from cloud-based IDE. These event logs are then examined using a process mining technique to extract the developers' coding processes and compare them in the shared coding environment. The approach can be used to discover emergent and interesting developers' behavior. Thus, we compare the coding process extracted by developers with different skills. To validate our approach, we describe the results of a study in which we investigate the coding activities of forty students of an advanced Java programming course performing a given programming task - during four assignments. Results also prove that users with different performances possess distinct attitudes highlighting that the adopted process mining technique can be useful to comprehend how developers can improve their coding skills.

Mining Developer's Behavior from Web-Based IDE Logs

Bernardi M. L.;
2019-01-01

Abstract

The birth of cloud-based development environments makes available an increasing number of data coming out from the interaction of different developers with a diverse level of expertise. This data, if opportunely captured and analyzed, can be useful to understand how developers head the coding activities and can suggest members of developers community how to improve their performances. This paper presents a framework allowing to generate event logs from cloud-based IDE. These event logs are then examined using a process mining technique to extract the developers' coding processes and compare them in the shared coding environment. The approach can be used to discover emergent and interesting developers' behavior. Thus, we compare the coding process extracted by developers with different skills. To validate our approach, we describe the results of a study in which we investigate the coding activities of forty students of an advanced Java programming course performing a given programming task - during four assignments. Results also prove that users with different performances possess distinct attitudes highlighting that the adopted process mining technique can be useful to comprehend how developers can improve their coding skills.
2019
978-1-7281-0676-2
development workflows
IDE logging
process mining
source code
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12070/60161
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