Model-driven Software development

 

Model driven Software development evolves existing systems and facilitates the creation of new software systems.

The salient features of model driven software development include:

1.       Domain-specific languages (DSLs) that express models at different abstraction levels.

2.       DSL notation syntaxes that are collected separately

3.       Model transformations for generating code from models either directly by model-to-text transformations or indirectly by intermediate model-to-model transformations.

An abstract syntax is defined by a metamodel that uses a metamodeling language to describe a set of concepts and their relationships. These languages use object-oriented constructs to build metamodels. The relationship between a model and a metamodel can be described by a “conforms-to” relationship.

There are seven metamodels including Knowledge Discovery Metamodel, Abstract Syntax Tree Metamodel, the Software Measurement Metamodel, analysis program, visualization, refactoring and transformation

ASTM and KDM are complimentary in modeling software systems’ syntax and semantics. ASTMs use Abstract Syntax Trees to mainly represent the source code’s syntax, KDM helps to represent semantic information about a software system, ranging from source code to higher level of abstractions. KDM is the language of architecture and provides a common interchange format intended for representing software assets and tools interoperability. Platform, user interface or data can each have its own KDM and are organized as packages. These packages are grouped into four abstraction layers to improve modularity and separation of concerns: infrastructure, program elements, runtime resource and abstractions.

SMM is the metamodel that can represent both metrics and measurements. It includes a set of elements to describe the metrics in KDM models and their measurements.

Taking the example of the modernization of a database forms application and migrating it to a Java platform, an important part of the migration could involve PL/SQL triggers in legacy Forms code. In a Forms application, the sets of SQL statements corresponding to triggers are tightly coupled to the User Interface. The cost of the migration project is proportional to the number and complexity of these couplings. The reverse engineering process involves extracting KDM models from the SQL code.

An extractor that generates the KDM model from SQL code can be automated. A framework that provides domain specific languages for extraction of model is available and this can be used to create a model that conforms to a target KDM from program that conforms to grammar. Dedicated parsers can help with this code-to-model transformation.

With the popularity of machine learning techniques and softmax classification, extracting domain classes according to syntax tree meta-model and semantic graphical information has become more meaningful. The two-step process of parsing to yield Abstract Syntax Tree Meta-model and restructuring to express Abstract Knowledge Discovery Model becomes enhanced with collocation and dependency information. This results in classifications at code organization units that were previously omitted. For example, code organization and call graphs can be used for such learning. The discovery of KDM and SMM can also be broken down into independent learning mechanisms with the Dependency Complexity being one of them.