Nomen est omen: exploring and exploiting similarities between argument and parameter names

Nomen est omen: exploring and exploiting similarities between argument and parameter names 2016 IEEE/ACM 38th IEEE International Conference on Software Engineering Nomen est Omen: Exploring and Exploiting Similarities between Argument and Parameter Names Hui Liu1 , Qiurong Liu1 , Cristian-Alexandru Staicu2 , Michael Pradel2 , Yue Luo1 School of Computer Science and Technology, Beijing Institute of Technology, China 2 Department of Computer Science, TU Darmstadt, Germany {liuhui08,liuqiurong}@bit.edu.cn, cris.staicu@gmail.com, michael@binaervarianz.de, 102286165@qq.com ABSTRACT Programmer-provided identifier names convey information about the semantics of a program. This information can complement traditional program analyses in various software engineering tasks, such as bug finding, code completion, and documentation. Even though identifier names appear to be a rich source of information, little is known about their properties and their potential usefulness. This paper presents an empirical study of the lexical similarity between arguments and parameters of methods, which is one prominent situation where names can provide otherwise missing information. The study involves 60 real-world Java programs. We find that, for most arguments, the similarity is either very high or very low, and that short and generic names often cause low similarities. Furthermore, we show that inferring a set of low-similarity parameter names from one set of programs allows for pruning such names in another set of programs. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Nomen est omen: exploring and exploiting similarities between argument and parameter names

Loading next page...
/lp/association-for-computing-machinery/nomen-est-omen-exploring-and-exploiting-similarities-between-argument-B1lAsJqh8p?dateFacetFrom=NOW%2FDAY-5YEARS&page=9
Datasource
acm
Copyright
Copyright © 2016 by ACM Inc.
ISBN
978-1-4503-3900-1
D.O.I.
10.1145/2884781.2884841
Publisher site
See Article on Publisher Site

Abstract

2016 IEEE/ACM 38th IEEE International Conference on Software Engineering Nomen est Omen: Exploring and Exploiting Similarities between Argument and Parameter Names Hui Liu1 , Qiurong Liu1 , Cristian-Alexandru Staicu2 , Michael Pradel2 , Yue Luo1 School of Computer Science and Technology, Beijing Institute of Technology, China 2 Department of Computer Science, TU Darmstadt, Germany {liuhui08,liuqiurong}@bit.edu.cn, cris.staicu@gmail.com, michael@binaervarianz.de, 102286165@qq.com ABSTRACT Programmer-provided identifier names convey information about the semantics of a program. This information can complement traditional program analyses in various software engineering tasks, such as bug finding, code completion, and documentation. Even though identifier names appear to be a rich source of information, little is known about their properties and their potential usefulness. This paper presents an empirical study of the lexical similarity between arguments and parameters of methods, which is one prominent situation where names can provide otherwise missing information. The study involves 60 real-world Java programs. We find that, for most arguments, the similarity is either very high or very low, and that short and generic names often cause low similarities. Furthermore, we show that inferring a set of low-similarity parameter names from one set of programs allows for pruning such names in another set of programs.

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create folders to
organize your research

Export folders, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off