Analysis of the ISBSG software repository from the ISO 9126 view of software product quality

Cheikhi, Laila; Abran, Alain; Desharnais, Jean-Marc

doi:10.1109/iecon.2012.6389405

Cited by 2 publications

(6 citation statements)

References 1 publication

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“…Open repositories are defined in different environments, whether academic or non-academic [Lima and Peres 2021, Danny et al 2019, Komiyama and Yamaji 2017, Cheikhi et al 2012. In [Danny et al 2019], the implementation of an open access institutional repository is presented.…”

Section: Open Repositoriesmentioning

confidence: 99%

Comparing Open Data Repositories

Costa¹,

Cordeiro²,

OliveiraJr³

2021

Anais Da v Escola Regional De Engenharia De Software (ERES 2021)

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Open Data is one of the main concepts of Open Science, which has the purpose to make scientific research artifacts accessible for everyone. Open data provides recommendations and practices to get access and use data from scientific researches, in a free, permanent, citable, auditable and interchangeable way. To facilitate the data management, it is important to store them in a repository. Considering this context, this paper provides a comparison among five known open data repositories. We performed the comparison taking into account a set of criteria, such as, data format constraints, digital identifier, versioning of published datasets, curators of data collections, metadata schema, versioning and exportation, storage limit, paid services, redundancy and preservation, access controls and APIs. We present results and discussions, in terms of such criteria.

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Section: Open Repositoriesmentioning

confidence: 99%

Comparing Open Data Repositories

Costa¹,

Cordeiro²,

OliveiraJr³

2021

Anais Da v Escola Regional De Engenharia De Software (ERES 2021)

View full text Add to dashboard Cite

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“…The detailed mappings between the six sigma methodologies of DMAIC and DFSS (IDDOV) and the ISBSG data questionnaire have been conducted: it highlights Table 5. Defect data fields in the ISBSG data extract [26].…”

Section: Mapping the Of Isbsg Questionnaire To Six Sigma Methodologiementioning

confidence: 99%

“…As recommended by [18] and [28] two verification steps have to be carried out before using the data set for analysis: data quality verification and data completeness verification.…”

Section: Analysis Of the Quality-related Data Fields In The Isbsg Ms-mentioning

confidence: 99%

“…The internal view of the ISBSG data repository corresponds closely to their data collection questionnaire, with some additional fields added by their repository manager [26]. The data repository of the ISBSG [13] is a publicly available multi-company data set which contains software project data collected from various organizations around the world from 1989 on.…”

Section: Isbsg Internal Viewmentioning

confidence: 99%

“…For the purpose of software benchmarking, ISBSG collects, analyzes and reports data relating to products developed and processes implemented within organizational units in order to [26]:…”

Section: Isbsg Internal Viewmentioning

confidence: 99%

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The ISBSG Software Project Repository: An Analysis from Six Sigma Measurement Perspective for Software Defect Estimation

Almakadmeh¹,

Abran²

2017

JSEA

Self Cite

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The International Software Benchmarking Standards Group (ISBSG) provides to researchers and practitioners a repository of software projects' data that has been used to date mostly for benchmarking and project estimation purposes, but rarely for software defects analysis. Sigma, in statistics, measures how far a process deviates from its goal. Six Sigma focuses on reducing variations within processes, because such variations may lead to an inconsistency in achieving projects' specifications which represent "defects", which mean not meeting customers' satisfaction. Six Sigma provides two methodologies to solve organizations' problems: "Define-Measure-Analyze-Improve-Control" process cycle (DMAIC) and Design of Six Sigma (DFSS). The DMAIC focuses on improving the existed processes, while the DFSS focuses on redesigning the existing processes and developing new processes. This paper presents an approach to provide an analysis of ISBSG repository based on Six Sigma measurements. It investigates the use of the ISBSG data repository with some of the related Six Sigma measurement aspects, including Sigma defect measurement and software defect estimation. This study presents the dataset preparation consisting of two levels of data preparations, and then analyzed the quality-related data fields in the ISBSG MS-Excel data extract (Release 12 -2013). It also presents an analysis of the extracted dataset of software projects. This study has found that the ISBSG MS-Excel data extract has a high ratio of missing data within the data fields of "Total Number of Defects" variable, which represents a serious challenge when the ISBSG dataset is being used for software defect estimation.

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Analysis of the ISBSG software repository from the ISO 9126 view of software product quality

Cited by 2 publications

References 1 publication

Comparing Open Data Repositories

Comparing Open Data Repositories

The ISBSG Software Project Repository: An Analysis from Six Sigma Measurement Perspective for Software Defect Estimation

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