Existing software engineering tools have proved useful in automating some aspects of the code review process, from uncovering defects to refactoring code. However, given that software teams still spend large amounts of time performing code reviews despite the use of such tools, much more research remains to be carried out in this area. This dissertation present two major contributions to this field. First, we perform a text classification experiment over thirty thousand GitHub review comments to understand what code reviewers typically discuss in reviews. Next, in an attempt to offer an innovative, data-driven approach to automating code reviews, we leverage probabilistic models of source code and graph embedding techniques to perform human-like code inspections. Our experimental results indicate that the proposed algorithm is able to emulate human-like code inspection behaviour in code reviews with a macro f1-score of 62%, representing an impressive contribution towards the relatively unexplored research domain of automated code reviewing tools. / Thesis / Master of Applied Science (MASc)

As software systems grow in size they will also grow in complexity. If the increased complexity is not managed the system will be increasingly difficult to maintain. The effect of unmaintainable software is even more distinct when using a agile development process. By increasing the maintainability of the system these problems will be dealt with and the system can be extended with sustained efficiency. This thesis will evaluate the development process of a modern, agile company in order to find changes that will promote increased maintainability. The result is an modified process that will increase the maintainability with the smallest possible overhead for the development organisation. The result is based on earlier studies of development technologies that have proven to increase the maintainability. The implementation of these technologies are adjusted to fit the development team, and some of the technologies that are not suitable for the team are rejected.

Background: COVID-19 is a dangerous contagious infection which was declared as a global pandemic by World Health Organisation (WHO) in March 2020. It was rapidly spreading worldwide, forcing the world to move into isolation and the software developing companies to change their work settings into remote working. Quality of the software is a significant attribute that determines the success of a project. Code reviews are an essential software development practice and are the first step towards improving the quality of the software. Objectives: The main objective of this research study is to list the challenges that the developers are facing while working from home and investigate the impact of challenges on code review practices. Methods: A multiple case study has been conducted in 5 organizations to understand and analyze the effect of transition on the code review process. We achieved this by conducting semi-structured interviews and participant observation with developers involved in code review practices of each organization considered for the study and qualitatively analyzed the gathered data using thematic analysis. Results: The results indicated challenges concerning team collaboration, infrastructure, productivity and burnout in the early stages of the pandemic. However, later, organizations’ mitigating strategies have helped them cope with the situation, and no significant impact due to working from home were observed on the code review process. Conclusions: Our findings highlight that there is no considerable impact of the challenges factored in due to working from home on the code review process. The major reasons behind that was the modernization of the tools used for code reviews and timely implementation of mitigation strategies by organizations. Based on the mitigation strategies taken by the organisations we formulated guidelines, which can be taken into consideration by the organisations still suffering with the transition to work from home.