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Measuring and estimating the reusability of software components is important towards finding reusable candidates. Researchers have shown that software metrics can be effectively used to assess software reusability. This work provides a systematic literature review to investigate the main factors that influence software reusability and how these identified factors can be quantified using software metrics. This paper also investigates tool availability of the identified software metrics. Based on the extensive study, we narrowed down 44 factors that could positively or negatively affect the reusability of software systems. In term of software metrics, we report our findings through five main families of metrics, namely coupling, cohesion, complexity, inheritance, and size. We found that most of the metrics examine reusability at the class-level, and the availability of software tools is limited. Furthermore, not all reusability affecting factors are equally impactful to assess the reusability of software components.While existing studies often discussed the impact of complexity towards software reusability, we found that only a handful of complexity metrics were meant for assessing reusability. We have identified several open challenges and gaps in the area, in particular lack of quantifiable measurement for reusability, limited software tools, and limited metrics that directly measure reusability.

Code review is a widely-used practice in software development companies to identify defects. Hence, code review has been included in many software engineering curricula at universities worldwide. However, teaching code review is still a challenging task because the code review effectiveness depends on the code reading and analytical skills of a reviewer. While several studies have investigated the code reading techniques that students should use to find defects during code review, little has focused on a learning activity that involves analytical skills. Indeed, developing a code review checklist should stimulate students to develop their analytical skills to anticipate potential issues (i.e., software defects). Yet, it is unclear whether students can anticipate potential issues given their limited experience in software development (programming, testing, etc.). We perform a qualitative analysis to investigate whether students are capable of creating code review checklists, and if the checklists can be used to guide reviewers to find defects. In addition, we identify common mistakes that students make when developing a code review checklist. Our results show that while there are some misconceptions among students about the purpose of code review, students are able to anticipate potential defects and create a relatively good code review checklist. Hence, our results lead us to conclude that developing a code review checklist can be a part of the learning activities for code review in order to scaffold students' skills.

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