A Model Driven Approach for Modeling and Generating PHP CodeIgniter based Applicationspring
Journal Title: Transactions on Machine Learning and Artificial Intelligence - Year 2017, Vol 5, Issue 4
Abstract
During the last decade, web development industry has grown exponentially. Models have been introduced as a solution to face the challenge of both business and technology changes. In this article, we present a Model Driven based approach concerning the design of CodeIgniter based web applications. We describe a meta model of this framework and we also specify a set of transformations to generate the application’s source code taking into account the MVC (ModelViewController) architecture of CodeIgniter. In this approach, the PHP framework meta model is considered as a platform Specific model (PSM). Its instances are used as inputs to generate the source code through transformation rules carried out by Acceleo. This proposal is validated through the use of our approach to generate CRUD (Create, Read, Update and Delete) applications.
Authors and Affiliations
Karim Arrhioui, Samir Mbarki, Oualid Betari, Sarra Roubi, Mohammed Erramdani
Novel Compact CPW LowPass Filter Integrating Periodic Triangle DGS Cells
In this paper, we introduce a new periodic structure for CPW of a low pass filter based on the DGS technique with triangle slot cell forme. The proposed structure is a minuature low pass filter that exhibits low insertio...
Role of Management and Policy Issues in Computer Security: Rand Report R-609 within Organization
The need to provide strengthened Security for Information Systems within organization increases day after day seeing the large development of interconnection of the World Wide Web and the clear effect that results by the...
Stock Recommendations using Bio-Inspired Computations on Social Media
The tremendous growth of the social networks has paved way for social interactions of investing communities about a company�s stock performance. Investors are able to share their comments on stocks using social media pla...
Nonlinear Time Series Prediction Performance Using Constrained Motion Particle Swarm Optimization
Constrained Motion Particle Swarm Optimization (CMPSO) is a general framework for optimizing Support Vector Regression (SVR) free parameters for nonlinear time series regression and prediction. CMPSO uses Particle Swarm...
Creatinine, Urea and Uric Acid in Hospitalized Patients with and Without Hyperglycemia Analysis using Generalized Additive Model
Hyperglycemia is an important risk factor for heart disease and premature mortality. In hospitalized patients, it is related to an increase in morbidity and development of other disease like kidney disease. To evaluate t...