Objective software quality assessment

Johnson, George C.; Yu, Xingbo

doi:10.1109/nssmic.1999.842911

Cited by 5 publications

(3 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…BBN 15, 16 requires large amount of data that prevent the widespread use of such techniques and adversely affect the accuracy of the results.…”

Section: Comparison With Other Methodologiesmentioning

confidence: 99%

“…Fenton and Neil 15 proposed a Bayesian Belief Network (BBN) model to predict software defect density, and Johnson and Yu 16 presented a BBN software quality model, based on BBN technique that determines software reliability through software engineering metrics assessment. These techniques require large amount of data and hence such techniques cannot be widely used.…”

Section: Previous Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Ranking of software engineering metrics by fuzzy‐based matrix methodology

Garg

Sharma

Nagpal

et al. 2011

Software Testing Verif & Rel

View full text Add to dashboard Cite

This research paper presents a framework for ranking of software engineering metrics based on expert opinion elicitation and fuzzy-based matrix methodology. The proposed methodology is able to accommodate the imprecise and inexact data involved in the problem of ranking of software engineering metrics, vagueness and ambiguity occurring during expert (human) decision making and to depart from the complexity of formulation of the objective and the constraint function. The matrices lend themselves to mechanical manipulations and are useful for analyzing and deriving systems functions expeditiously to meet the objectives. The current research is based on software engineering metrics identified in an earlier study conducted by Lawrence Livermore National Laboratory. A set of ranking criteria were identified. Software engineering metrics are then ranked in ascending order using experts' opinion in accordance with the value of Permanent function on their criteria matrix. The proposed methodology has also been compared with other known methodologies. Softw. Test. Verif. Reliab. 2013; :149-168 23 L (0,0.3,0.5) VL (0,0,0.3) Relevance to reliability M (0.2,0.5,0.8) H (0.5,0.7,1) L (0,0.3,0.5) M (0.2,0.5,0.8) H (0.5,0.7,1)

show abstract

“…BBN 15, 16 requires large amount of data that prevent the widespread use of such techniques and adversely affect the accuracy of the results.…”

Section: Comparison With Other Methodologiesmentioning

confidence: 99%

Section: Previous Related Workmentioning

confidence: 99%

Ranking of software engineering metrics by fuzzy‐based matrix methodology

Garg

Sharma

Nagpal

et al. 2011

Software Testing Verif & Rel

View full text Add to dashboard Cite

show abstract

“…There are many uncertainties in software project management (SPM), for example, (a) uncertainties in estimating project size, schedule, cost, quality; (b) uncertainties regarding the impact of changes in requirements; and (c) uncertainties about the impact of new technology adoption. Neil and Fenton [1] and Johnson [2] were the first ones to propose BBNs for modelling software development project uncertainties.…”

Section: Introductionmentioning

confidence: 99%

A 20‐year mapping of Bayesian belief networks in software project management

2021

View full text Add to dashboard Cite

In recent years, more software engineering researchers have focussed on methods, techniques, tools, and processes to support software project management (SPM) addressing quality, cost, and time constraints. In this direction, the use of Bayesian belief networks (BBNs) has gained attention for providing a powerful mechanism for cause–effect analysis with both qualitative and quantitative data to support decision making under uncertainty. This work aims to provide an overview of the first 20 years of research in BBNs applied to SPM, and by so doing it contributes to the structuring of this research topic and the identification of new research opportunities. We conducted a systematic mapping (SM) study on the use of BBN as a decision‐support tool for SPM issues. We analysed over 109 relevant publications, from 1999 to 2018 (i.e., 20 years), to understand the motivations for using Bayesian networks (why), the problem domain and model scope addressed by researchers (what), the stage of the life cycle in which BBNs are being used (when), the venues of the publications (where), and the tools used to model the Bayesian networks (how). We draw the following conclusions from the results of our SM: (1) The application of Bayesian networks in SPM has been an active research topic since 1999. (2) Prediction and planning are the most common purposes in 60% of selected papers. (3) Software quality (55%) is the problem domain most investigated. (4) Most of the surveyed studies embrace the project (47%) and product (37%) scopes. And finally, (5) the development phase (86%) is when Bayesian networks have been more used. As future work, we highlight the need to further investigate methodologies that enable the use of BBNs in real software development contexts.

show abstract