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AI in SDLC

AI

AI in SDLC

Artificial Intelligence in Software Development Life Cycle (SDLC)

This post explains about the use of Artificial Intelligence in Software Development Life Cycle Requirements and its Model (SDLC).

AI research techniques make it possible to perceive, reason and act. Research in software engineering is concerned with supporting engineers to developed better software in less period.

Today several research directions of both disciplines come closer together and are beginning to build new research areas. Software agents play an important role as research objects in distributed AI (DAI) as well as in Agent Oriented Software Engineering (AOSE).

Use of Artificial Intelligence in Software Development Life Cycle Requirements Specification

1.Use of AI in Software Planning and Requirement Analysis:-

Requirement analysis is the most important and fundamental stage in SDLC. It is performed by the senior members of the team with inputs from the customer, the sales department, market surveys and domain experts in the industry.

This information is then used to plan the basic project approach and to conduct product feasibility study in the economical, operational and technical areas. Planning for the quality assurance requirements and identification of the risks associated with the project is also done in the planning stage.

2.Use of AI in Software Defining Requirements:-

Once the requirement analysis is done the next step is to clearly define and document the product requirements and get them approved from the customer or the market analysts. This is done through an SRS (Software Requirement Specification) document which consists of all the product requirements to be designed and developed during the project life cycle.

3.Use of AI in Software Designing the Product Architecture:-

SRS is the reference for product architects to come out with the best architecture for the product to be developed. Based on the requirements specified in SRS, usually more than one design approach for the product architecture is proposed and documented in a DDS – Design Document Specification.

A design approach clearly defines all the architectural modules of the product along with its communication and data flow representation with the external and third party modules (if any).

4.Use of AI in Software Building or Developing the Product:-

In this stage of SDLC the actual development starts and the product is built. The programming code is generated as per DDS during this stage. If the design is performed in a detailed and organized manner, code generation can be accomplished without much hassle.

Developers must follow the coding guidelines defined by their organization and programming tools like compilers, interpreters, debuggers, etc. are used to generate the code. Different high level programming languages such as C, C++, Pascal, Java and PHP are used for coding. The programming language is chosen with respect to the type of software being development.

5.Use of AI in Software Testing the Product:-

This stage is usually a subset of all the stages as in the modern SDLC models, the testing activities are mostly involved in all the stages of SDLC. However, this stage refers to the testing only stage of the product where product defects are reported, tracked, fixed and retested, until the product reaches the quality standards defined in the SRS.

6.Use of AI in Software design Deployment in the Market and Maintenance:-

Once the product is tested and ready to be deployed it is released formally in the appropriate market. Sometimes product deployment happens in stages as per the business strategy of that organization.

The product may first be released in a limited segment and tested in the real business environment (UAT- User acceptance testing).Then based on the feedback, the product may be released as it is or with suggested enhancements in the targeting market segment. After the product is released in the market, its maintenance is done for the existing customer base.

Uses of Artificial Intelligence in SDLC Models:-

1.V-Model :- The V-model is an SDLC model where execution of processes happens in a sequential manner in a V-shape. It is also known as Verification and Validation model.

The V-Model is an extension of the waterfall model and is based on the association of a testing phase for each corresponding development stage. This means that for every single phase in the development cycle, there is a directly associated testing phase.

2.Waterfall Model :-  The Waterfall Model is a linear sequential flow. In which progress is seen as flowing steadily downwards (like a waterfall) through the phases of software implementation. This means that any phase in the development process begins only if the previous phase is complete. The waterfall approach is the earliest approach and most widely known that was used for software development.

3.Iterative Model :- It is developed to overcome the weakness of the waterfall model. It is start with an initial planning and end with development with the cyclic interaction in between. It can consist of mini V-shaped model.

It used in shrink-wrap application and large system which built in small segments. It also, can be used in a system has separated component, examples:- ERP system. Which we can start with the budget module as a first iteration and then we can start with inventory module.

4.Spiral model :- Spiral model is one of the most important Software Development Life Cycle models, which provides support for Risk Handling. The exact number of loops of the spiral is unknown and can vary from project to project. Each loop of the spiral is called a Phase of the software development process. The Spiral model is called as a Meta Model because it subsumes all the other SDLC models. For example, a single loop spiral actually represents the Iterative Waterfall Model.