Investigating the Relationship between Human Factors and Test Code Quality

Software development is a collaborative, social, knowledge-intensive activity, and human-centered aspects such as communication and personality can impact software projects. These factors are essential for team diversity. There are three types of team diversity: informational (or knowledge), social, and values diversity. In this context, we have noticed that there's a lot of interest in the software engineering community about the relationship between human factors and code quality. It is important to investigate if knowledge diversity (human aspects) affects test code quality. The literature has brought up a number of studies investigating test code quality, but there is just a little empirical evidence on the effects of knowledge diversity (e.g., educational background, level of professional experience, expertise, and skills) and test code quality. Whether we consider the prevalence of test smells in current software testing research, the number is way more limited. Test smells are bad implementations inserted by developers and can harm the comprehensibility and maintainability of test suites. Recent studies discuss developers' perceptions of test smells and their impact on quality improvement, yet they have yet to discuss the effects of knowledge diversity in this regard. Our goal is to gather empirical evidence on such a relationship, {\color{blue} between developer knowledge diversity and test code quality}, with particular attention on the effect test smells can bring to software quality. Initially, we built a knowledge base considering the main concepts of software testing, software maintenance, and evolution, test smells, Software refactoring, Developer Classification, and Tool Support. Next, to accomplish our research objective, we used a combination of mixed methods approach (e.g., surveys, interviews, and mining of GitHub repositories) to gather empirical evidence on human aspects and test code quality. As a result, we intend to organize the findings in a set of guidelines. It can support developers in preventing the insertion of test smells during the creation of unit test cases.