Mining of Motivators and De-Motivators for Software Developers from GitHub : an Empirical Study
Saha, Niladri (2022)
Saha, Niladri
2022
Master's Programme in Computing Sciences
Informaatioteknologian ja viestinnän tiedekunta - Faculty of Information Technology and Communication Sciences
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Hyväksymispäivämäärä
2022-04-08
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202203222674
https://urn.fi/URN:NBN:fi:tuni-202203222674
Tiivistelmä
In the present day, the software industry is experiencing a high rise of burnout cases amongst soft-ware engineers. Several companies are implementing various policies to motivate software engineers and prevent the rise of burnout cases and depression in the software industry. But still, the cases are rising worldwide. As software engineers are an essential part of the software industry, it is a concern for the software industry and its growth. Thus, it is necessary to find an approach to deal with this.
This thesis aims to find out measurable motivators and de-motivators that can be extracted from GitHub Repositories. It will also be useful for future research on the well-being of software developers in the context of open-source software development as well as for an organization.
An empirical study is done to find out the motivational and de-motivational factors from the extracted data of GitHub. First, a literature review is done to get the list of motivators and de-motivators. Then a quantitative approach is applied by extracting over 26566 Issues with comments from 35 reposito-ries and over 6520 commits from 35 repositories. From the extracted data, mapping is done with the motivators and de-motivators. Once the mapping is completed, the calculation of the motivators and de-motivators is done using metrics that are based on the extracted data. After this, variations of those factors are observed with different sentiments and emotions. Then a survey is done with the developers associated with different GitHub repositories. Once the survey is completed, both the re-sults from the data mining and survey are compared to verify whether these factors from GitHub cor-rectly match with the developers’ viewpoint.
Results show that Issue complexity, risk, and collaboration are the factors that can be measured from the GitHub repository. However, it is found that risk is not at all a de-motivator as both the survey and mining results show developers are more willing to work on risky issues. The collaboration score seems to be contradictory with survey results as the survey shows developers feel the positive effect on collaboration.
This thesis aims to find out measurable motivators and de-motivators that can be extracted from GitHub Repositories. It will also be useful for future research on the well-being of software developers in the context of open-source software development as well as for an organization.
An empirical study is done to find out the motivational and de-motivational factors from the extracted data of GitHub. First, a literature review is done to get the list of motivators and de-motivators. Then a quantitative approach is applied by extracting over 26566 Issues with comments from 35 reposito-ries and over 6520 commits from 35 repositories. From the extracted data, mapping is done with the motivators and de-motivators. Once the mapping is completed, the calculation of the motivators and de-motivators is done using metrics that are based on the extracted data. After this, variations of those factors are observed with different sentiments and emotions. Then a survey is done with the developers associated with different GitHub repositories. Once the survey is completed, both the re-sults from the data mining and survey are compared to verify whether these factors from GitHub cor-rectly match with the developers’ viewpoint.
Results show that Issue complexity, risk, and collaboration are the factors that can be measured from the GitHub repository. However, it is found that risk is not at all a de-motivator as both the survey and mining results show developers are more willing to work on risky issues. The collaboration score seems to be contradictory with survey results as the survey shows developers feel the positive effect on collaboration.