All student projects

My Software Code Reads Better than Yours

Software companies care about improving productivity. At Meta, improving productivity means finding a balance between code velocity, reliability, and readability of software systems.

The proposed two master theses projects contribute to understanding what is readable software and how to write more readable software. This project is in collaboration with Prof. Rui Abreu, a research software engineer with Meta.

The first project uses natural language processing and information retrieval techniques to identify what developers think improves code readability in open-source software. This study will determine the types of readability issues and their relevance. The relevance of readability issues can be established by linking the issues and their impact on the review decision and duration of the process. Sentiments could be another dimension to gauge how authors and reviewers perceive the readability issue.

The second project solicits developer perceptions on what software codes they find more readable and why. This study offers a plugin to measure software code’s readability and reasons why one code is more readable than another.

Available spots: 2

Pointers to literature

Buse, Raymond PL, and Westley R. Weimer. “A metric for software readability.” In Proceedings of the 2008 international symposium on Software testing and analysis, pp. 121-130. 2008.

Posnett, Daryl, Abram Hindle, and Premkumar Devanbu. “A simpler model of software readability.” In Proceedings of the 8th working conference on mining software repositories, pp. 73-82. 2011.

Mannan, Umme Ayda, Iftekhar Ahmed, and Anita Sarma. “Towards understanding code readability and its impact on design quality.” In Proceedings of the 4th ACM SIGSOFT International Workshop on NLP for Software Engineering, pp. 18-21. 2018.

Fakhoury, Sarah, Devjeet Roy, Adnan Hassan, and Vernera Arnaoudova. “Improving source code readability: Theory and practice.” In 2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC), pp. 2-12. IEEE, 2019.


Dr. Ayushi Rastogi

Dr. Ayushi Rastogi

assistant professor

SEARCH Group • University of Groningen • 2023
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