Data-Driven Decisions and Actions in Today’s Software Development

Gall, Harald; Alexandru, Carol V.; Ciurumelea, Adelina; Grano, Giovanni; Laaber, Christoph; Panichella, Sebastiano; Proksch, Sebastian; Schermann, Gerald; Vassallo, Carmine; Zhao, Jitong

doi:10.1007/978-3-319-73897-0_9

Cited by 1 publication

(1 citation statement)

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“…They can act in the pattern classification identifying images on web [18], license plate [19], saliency map estimation [20], image recognition [21,22,23] image recognition in medical domain [24], text recognition [25], fault identification [26], among others. Already in the data mining part of forecasting development recent work was developed by [27,28,29,30].They use clever techniques to help managers and developers to understand the patterns involved in software development.Fuzzy rules-based fuzzy systems were used in [31] to perform the estimation of effort in the production of software using the UCP concepts. Already in the work of [32] the concepts of linear regression and perceptron were combined to solve the problems of estimation of efforts.…”

Section: Intelligence Models Used In Predicting Use-case Pointsmentioning

confidence: 99%

Regularized Fuzzy Neural Networks to Aid Effort Forecasting in the Construction and Software Development

Souza¹,

Guimarães²,

Araújo³

et al. 2018

IJAIA

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Predicting the time to build software is a very complex task for software engineering managers. There are complex factors that can directly interfere with the productivity of the development team. Factors directly related to the complexity of the system to be developed drastically change the time necessary for the completion of the works with the software factories. This work proposes the use of a hybrid system based on artificial neural networks and fuzzy systems to assist in the construction of an expert system based on rules to support in the prediction of hours destined to the development of software according to the complexity of the elements present in the same. The set of fuzzy rules obtained by the system helps the management and control of software development by providing a base of interpretable estimates based on fuzzy rules. The model was submitted to tests on a real database, and its results were promissory in the construction of an aid mechanism in the predictability of the software construction. KEYWORDSFuzzy neural networks, effort forecasting, use case point, expert systems,

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