Early cost estimation of software reworks using fuzzy requirement-based model

Khalid, Tarig Ahmed; Yeoh, Eng-Thiam

doi:10.1109/iccccee.2017.7866082

Cited by 6 publications

(1 citation statement)

References 9 publications

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“…Different datasets can likewise be attempted and tried. Tarig AhmedKhalid (2017) has proposed a fuzzy model to survey the cost of deformities evacuation at the beginning periods of venture arranging. This has been completed by considering the functional size of the venture and the experience of the development group.…”

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confidence: 99%

Fuzzy Optimization Algorithm for Software Cost Estimation

Ch.,

Singh

2020

IJEAT

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Estimation of a software cost depends on a probabilistic model and thus it doesn't create precise values. In any case, accessibility of good chronicled information combined with a efficient technique can create improved outcomes. This paper, we have displayed a Software Effort Estimation Model utilizing PSO and Fuzzy Logic. Fuzzy sets have been utilized for displaying uncertainty and imprecision in estimation of effort while PSO has been utilized for tuning parameters. This has been seen from the outcomes that Fuzzy-PSO intelligence gives precise outcomes when compared through its different partners. This system relies upon thinking by linguistic quantifiers and fuzzy logic. This kind of model holds well, when the product plans are communicated by absolute or potentially arithmetical data. Along these lines, this projected methodology improves the old style correlation process that doesn't think about clear cut data. In the fuzzy correlation model, fuzzy sets are used to describe both the clear cut and the arithmetical data.

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confidence: 99%

Fuzzy Optimization Algorithm for Software Cost Estimation

Ch.,

Singh

2020

IJEAT

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Intelligence-Software Cost Estimation Model for Optimizing Project Management

Naik

Nayak²

2019

Advances in Intelligent Systems and Computing

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An Amplified COCOMO-II Based Cost Estimation Model in Global Software Development Context

Khan

et al. 2021

IEEE Access

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Global Software Development (GSD) projects comprise several critical cost drivers that affect the overall project cost and budget overhead. Thus, there is a need to amplify the existing model in GSD context to reduce the risks associated with cost overhead. Motivated by this, the current work aims at amplifying the existing algorithmic model with GSD cost drivers to get efficient estimates in the context of GSD. To achieve the targeted research objective, current state-of-the-art cost estimation techniques and GSD models are reported. Furthermore, the current study has proposed a conceptual framework to amplify the algorithmic COCOMO-II model in the GSD domain to accommodate additional cost drivers empirically validated by a systematic review and industrial practitioners. The main phases of amplification include identifying cost drivers, categorizing cost drivers, forming metrics, assignment of values, and finally altering the base model equation. Moreover, the proposed conceptual model's effectiveness is validated through expert judgment, case studies, and Magnitude of Relative Estimates (MRE). The obtained estimates are efficient, quantified, and cover additional GSD aspects than the existing models; hence we could overcome the GSD project's overall risk by implementing the model. Finally, the results indicate that the model needs further calibration and validation.

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Early cost estimation of software reworks using fuzzy requirement-based model

Cited by 6 publications

References 9 publications

Fuzzy Optimization Algorithm for Software Cost Estimation

Fuzzy Optimization Algorithm for Software Cost Estimation

Intelligence-Software Cost Estimation Model for Optimizing Project Management

An Amplified COCOMO-II Based Cost Estimation Model in Global Software Development Context

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