Abstract
Modeling software development effort estimation models has been a hot research topic over the lastthree decades. Numerous models were proposed in these decades to predict the effort. The key challenges for futuresoftware development is providing accurate software estimation. Failure to acknowledge the accuracy of effortestimation can cause inaccurate estimation, customer disappointment, and poor software development or projectfailure. This research presents a novel computational technique, named adaptive neuro-fuzzy inference system(ANFIS), for the modeling of software effort estimation. It was developed utilizing the Constructive Cost Model(COCOMO) dataset. The data were randomly divided into two sets: 83% for training and 17% for testing. The meanmagnitude relative-error (MMRE) and the coefficient of correlation (R) were used as assessment indices. Resultsshowed that the accuracy of the proposed model is quite satisfactory in comparison with actual values. Moreover, acomparison study was conducted with another approach. The results showed that ANFIS produced better results incomparison with Function Point Analysis, Software Lifecycle Management, and COCOMO methods. ANFIS wasfound to be a potential predictive model for software development effort estimation.
Recommended Citation
Mohsin, Zainab Rustum
(2021)
"Investigating the Use of an Adaptive Neuro-Fuzzy InferenceSystem in Software Development Effort Estimation,"
Iraqi Journal for Computer Science and Mathematics: Vol. 2:
Iss.
2, Article 3.
DOI: https://doi.org/10.52866/ijcsm.2021.02.02.003
Available at:
https://ijcsm.researchcommons.org/ijcsm/vol2/iss2/3
