Aspects of software naturalness through the generation of identifier names

Zaitsev, Oleksandr

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Students Research & Project Works | Роботи студентів
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Факультет прикладних наук
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Освітня програма наук про дані
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2019
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dc.contributor.author	Zaitsev, Oleksandr
dc.date.accessioned	2019-02-20T08:22:31Z
dc.date.available	2019-02-20T08:22:31Z
dc.date.issued	2019
dc.identifier.citation	Zaitsev, Oleksandr. Aspects of software naturalness through the generation of identifier names : Master Thesis : manuscript / Oleksandr Zaitsev ; Supervisor Stéphane Ducasse, Alexandre Bergel ; Ukrainian Catholic University, Department of Computer Sciences. – Lviv : [s.n.], 2019. – 38 p. : ill.	uk
dc.identifier.uri	http://er.ucu.edu.ua/handle/1/1338
dc.language.iso	en	uk
dc.subject	Aspects of software naturalness	uk
dc.subject	Naturalness of Pharo	uk
dc.subject	Translating source code	uk
dc.title	Aspects of software naturalness through the generation of identifier names	uk
dc.type	Preprint	uk
dc.status	Публікується вперше	uk
dc.description.abstracten	Modern-day programming can be viewed as a form of communication between the person who is writing code and the one reading it. Nevertheless, very often developers neglect readability of software, and even well-written code becomes less comprehensive through the course of software evolution. In this work, we study how naturalness of source code written in Pharo allows us to train machine learning models that extract semantic information from method’s body and map it to a short descriptive name. We collect a dataset of methods from 10 biggest projects written in Pharo and build an attention-based sequence to sequence network that generates method names by translating source code into a couple of English words. We evaluate our model on an independent test set and report the precision of over 50%. To our knowledge, this is the first application of machine learning and natural language processing to the source code of Pharo.	uk