Impact of Installation Counts on Perceived Quality: A Case Study on Debian

Herraiz Tabernero, Israel; Shihab, Emad; Nguyen, Thanh H.D. y Hassan, Ahmed E. (2011). Impact of Installation Counts on Perceived Quality: A Case Study on Debian. En: "18th Working Conference on Reverse Engineering", 17-21 October 2011, Limerick, Ireland.

Descripción

Título: Impact of Installation Counts on Perceived Quality: A Case Study on Debian
Autor/es:
  • Herraiz Tabernero, Israel
  • Shihab, Emad
  • Nguyen, Thanh H.D.
  • Hassan, Ahmed E.
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 18th Working Conference on Reverse Engineering
Fechas del Evento: 17-21 October 2011
Lugar del Evento: Limerick, Ireland
Título del Libro: Proceedings of the 18th Working Conference on Reverse Engineering
Fecha: 20 Octubre 2011
Materias:
Escuela: E.T.S.I. Caminos, Canales y Puertos (UPM)
Departamento: Matemática e Informática Aplicadas a la Ingeniería Civil [hasta 2014]
Licencias Creative Commons: Reconocimiento

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Resumen

Software defects are generally used to indicate software quality. However, due to the nature of software, we are often only able to know about the defects found and reported; either following the testing process or after being deployed. In software research studies, it is assumed that a higher amount of defect reports represents a higher amount of defects in the software system. In this paper, we argue that widely deployed programs have more reported defects, regardless of their actual number of defects. To address this question, we perform a case study on the Debian GNU/Linux distribution, a well-known free / open source software collection. We compare the defects reported for all the software packages in Debian with their popularity. We find that the number of reported defects for a Debian package is limited by its popularity. This finding has implications on defect prediction studies, showing that they need to consider the impact of popularity on perceived quality, otherwise they might be risking bias.

Más información

ID de Registro: 9585
Identificador DC: http://oa.upm.es/9585/
Identificador OAI: oai:oa.upm.es:9585
URL Oficial: http://ieeexplore.ieee.org
Depositado por: Israel Herraiz
Depositado el: 31 Oct 2011 19:58
Ultima Modificación: 20 Abr 2016 17:56
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