cocomo model in software engineering tutorial point

The experiment outputs suggest that the suggested model can provide better results and accurately forecast the software development effort. Mean-Square-Error (MSE) and Mean Magnitude of Relative-Error (MMRE) are used as performance measurement indices. COCOMO data-set is accustomed to test and train the network. The paper proposes usage of ANN (Artificial Neural Network) based model technologically advanced using Multi Layered Feed Forward Neural Network which is given training with Back Propagation training method. Capability of machine learning particularly Artificial Neural Networks is to adjust a complex set of bond among the various independent and dependent variables. Software Development Process Models - Tutorial to Software Development Process Models in Software Testing in simple, easy and step by step way with syntax. One of the most commonly used algorithmic model for estimating effort in industry is COCOMO. Dynamically fluctuating environment of technology in software development industry make effort estimation further perplexing. The major reason for such disappointments in projects are because of inaccurate software development norms effort estimation is one such practice. In modern software development practice, it is crucial to know the cost and time required for the software development before establishing new software projects. Providing accurate estimations of software is still very challenging.

Several models have been developed in these decades. Software Effort Estimation models are hot topic of study over 3 decades.

Cocomo model in software engineering tutorial point