short-paper

Semantic Coupling Between Classes: Corpora or Identifiers?

Authors:

Nemitari Ajienka,

Andrea CapiluppiAuthors Info & Claims

ESEM '16: Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement

Article No.: 40, Pages 1 - 6

https://doi.org/10.1145/2961111.2962622

Published: 08 September 2016 Publication History

Abstract

Context: Conceptual coupling is a measure of how loosely or closely related two software artifacts are, by considering the semantic information embedded in the comments and identifiers. This type of coupling is typically evaluated using the semantic information from source code into a words corpus. The extraction of words corpora can be lengthy, especially when systems are large and many classes are involved.

Goal: This study investigates whether using only the class identifiers (e.g., the class names) can be used to evaluate the conceptual coupling between classes, as opposed to the words corpora of the entire classes.

Method: In this study, we analyze two Java systems and extract the conceptual coupling between pairs of classes, using (i) a corpus-based approach; and (ii) two identifier-based tools.

Results: Our results show that measuring the semantic similarity between classes using (only) their identifiers is similar to using the class corpora. Additionally, using the identifiers is more efficient in terms of precision, recall, and computation time.

Conclusions: Using only class identifiers to measure their semantic similarity can save time on program comprehension tasks for large software projects; the findings of this paper support this hypothesis, for the systems that were used in the evaluation and can also be used to guide researchers developing future generations of tools supporting program comprehension.

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Cited By

Sas CCapiluppi A(2023)Weak Labelling for File-level Source Code Classification2023 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)10.1109/SANER56733.2023.00074(698-702)Online publication date: Mar-2023
https://doi.org/10.1109/SANER56733.2023.00074
Sas CCapiluppi A(2023)Multi-granular software annotation using file-level weak labellingEmpirical Software Engineering10.1007/s10664-023-10423-729:1Online publication date: 30-Nov-2023
https://dl.acm.org/doi/10.1007/s10664-023-10423-7
Capiluppi AAjienka NAdams BConstantinou EMens TRobles G(2018)National boundaries and semantics of artefacts in open source developmentProceedings of the 1st International Workshop on Software Health10.1145/3194124.3194131(33-39)Online publication date: 28-May-2018
https://dl.acm.org/doi/10.1145/3194124.3194131
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cover image ACM Conferences

ESEM '16: Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement

September 2016

457 pages

ISBN:9781450344272

DOI:10.1145/2961111

General Chair:
Marcela Genero
University of Castilla-La Mancha, Spain
,
Program Chairs:
Andreas Jedlitschka
Fraunhofer IESE, Germany
,
Magne Jørgensen
Simula Research Laboratory, Norway
,
Giuseppe Scanniello
University of Basilicata, Italy
,
Sreedevi Sampath
University of Maryland Baltimore County, USA
,
Danilo Caivano
SER&Practices, Italy
,
Daniel Port
University of Hawaii, USA

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 08 September 2016

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ESEM '16: ACM/IEEE 9th International Symposium on Empirical Software Engineering and Measurement

September 8 - 9, 2016

Ciudad Real, Spain

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Cited By

Sas CCapiluppi A(2023)Weak Labelling for File-level Source Code Classification2023 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)10.1109/SANER56733.2023.00074(698-702)Online publication date: Mar-2023
https://doi.org/10.1109/SANER56733.2023.00074
Sas CCapiluppi A(2023)Multi-granular software annotation using file-level weak labellingEmpirical Software Engineering10.1007/s10664-023-10423-729:1Online publication date: 30-Nov-2023
https://dl.acm.org/doi/10.1007/s10664-023-10423-7
Capiluppi AAjienka NAdams BConstantinou EMens TRobles G(2018)National boundaries and semantics of artefacts in open source developmentProceedings of the 1st International Workshop on Software Health10.1145/3194124.3194131(33-39)Online publication date: 28-May-2018
https://dl.acm.org/doi/10.1145/3194124.3194131
Tiwari SRathore SReddy YVarma VCleland JBellur USengupta SSharma NLoganathan RSharma RSarkar S(2018)Coupling and Cohesion Metrics for Object-Oriented SoftwareProceedings of the 11th Innovations in Software Engineering Conference10.1145/3172871.3172878(1-11)Online publication date: 9-Feb-2018
https://dl.acm.org/doi/10.1145/3172871.3172878
Ajienka NCapiluppi ACounsell S(2018)An empirical study on the interplay between semantic coupling and co-change of software classesEmpirical Software Engineering10.1007/s10664-017-9569-223:3(1791-1825)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1007/s10664-017-9569-2
Ajienka NCapiluppi ACounsell SBener ATurhan BBiffl S(2017)Managing hidden dependencies in OO softwareProceedings of the 11th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement10.1109/ESEM.2017.21(141-150)Online publication date: 9-Nov-2017
https://dl.acm.org/doi/10.1109/ESEM.2017.21

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