loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Valasia Dimaridou ; Alexandros-Charalampos Kyprianidis ; Michail Papamichail ; Themistoklis Diamantopoulos and Andreas Symeonidis

Affiliation: Aristotle University of Thessaloniki, Greece

Keyword(s): Code Quality, Static Analysis Metrics, User-perceived Quality, Principal Feature Analysis.

Related Ontology Subjects/Areas/Topics: Software Engineering ; Software Metrics ; Software Project Management

Abstract: Nowadays, software has to be designed and developed as fast as possible, while maintaining quality standards. In this context, developers tend to adopt a component-based software engineering approach, reusing own implementations and/or resorting to third-party source code. This practice is in principle cost-effective, however it may lead to low quality software products. Thus, measuring the quality of software components is of vital importance. Several approaches that use code metrics rely on the aid of experts for defining target quality scores and deriving metric thresholds, leading to results that are highly context-dependent and subjective. In this work, we build a mechanism that employs static analysis metrics extracted from GitHub projects and defines a target quality score based on repositories’ stars and forks, which indicate their adoption/acceptance by the developers’ community. Upon removing outliers with a one-class classifier, we employ Principal Feature Analysis and exa mine the semantics among metrics to provide an analysis on five axes for a source code component: complexity, coupling, size, degree of inheritance, and quality of documentation. Neural networks are used to estimate the final quality score given metrics from all of these axes. Preliminary evaluation indicates that our approach can effectively estimate software quality. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 44.212.26.248

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Dimaridou, V.; Kyprianidis, A.; Papamichail, M.; Diamantopoulos, T. and Symeonidis, A. (2017). Towards Modeling the User-perceived Quality of Source Code using Static Analysis Metrics. In Proceedings of the 12th International Conference on Software Technologies - ICSOFT; ISBN 978-989-758-262-2; ISSN 2184-2833, SciTePress, pages 73-84. DOI: 10.5220/0006420000730084

@conference{icsoft17,
author={Valasia Dimaridou. and Alexandros{-}Charalampos Kyprianidis. and Michail Papamichail. and Themistoklis Diamantopoulos. and Andreas Symeonidis.},
title={Towards Modeling the User-perceived Quality of Source Code using Static Analysis Metrics},
booktitle={Proceedings of the 12th International Conference on Software Technologies - ICSOFT},
year={2017},
pages={73-84},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006420000730084},
isbn={978-989-758-262-2},
issn={2184-2833},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Software Technologies - ICSOFT
TI - Towards Modeling the User-perceived Quality of Source Code using Static Analysis Metrics
SN - 978-989-758-262-2
IS - 2184-2833
AU - Dimaridou, V.
AU - Kyprianidis, A.
AU - Papamichail, M.
AU - Diamantopoulos, T.
AU - Symeonidis, A.
PY - 2017
SP - 73
EP - 84
DO - 10.5220/0006420000730084
PB - SciTePress