Application OfFuzzy Logic in

Software-Engineering

M.Siddardha

P.Dinesh

Saurabh Sharma

WHAT IS SOFTWARE ENGINEERING?

Software engineering is an engineering that is concerned with all aspects of software production.

Software, is any set of machine instructions to perform specific operations.

Software Engineering is the application of a systematic, disciplined, quantifiable approach to Design

Development

Testing and

Maintenance and Evolution of a SOFTWARE.

Component-Based Software Engineering

• Most of today’s applications are large and complex.

• An application must have some additional characteristics like usability, flexibility, simple installation, reusability, portability, interoperable, etc. to fight with the advancement in the technology and rapidly changing requirements

Component Based Development (CBD)

• CBD can be best described by the following two guiding principles:

– Reuse but do not reinvent;

– Assemble pre-built components rather than coding line by line.

• Component Based Software Development (CBSD) is getting popular in software industry as a new effective development paradigm.

• It emphasizes the design and construction of software system using reusable components.

• CBSD is capable of reducing development cost and increasing the reliability of entire software system using components.

Component

• A component is a Reusable and self -contained piece of software with well-specified interface that is independent of any application.

• It is an independent executable entity that can be made up of one or more executable objects

• Size of a component may vary from simple functions to an entire application systems

• New components can be developed, or even acquired from third party.

• An extra effort must be paid for the additional functionality of the component beyond the current application’s need, to make the component more useful

Reusability

• It is the degree to which a component can be re-used and reduces the software development cost by enabling less coding and more integration

Implementation of Fuzzy Systemfor Estimation of Re-Usability

• Fuzzy based model for estimation of re-usability considers five factors as inputs and provides a crisp value of reusability

• All inputs can be classified into fuzzy sets

• The output reusability is classified as Very High, High, Medium, Low and Very Low.

Estimating The Reusability

• To estimate reusability of Component Based System, following factors have been identified:

– Customizability

– Interface Complexity

– Understandability

– Portability

• Customizability is defined as the ability to modify a component as per the application requirement

– Better reusability can be achieved if customizability is high

– Customizability of a component may vary from 0 to 1.

• Interface Complexity:

– As components are black box in nature, we are unable to get the source code of these components.

– Interface acts as a main source for understanding, use and implementation and finally maintenance for the component.

– Therefore for better reusability, interface complexity should be as low as possible .

• Understandability:

– Documentation provides the ease with which a user can learn to operate, prepare inputs for, and interpret outputs of a system or component.

– Better reusability can be achieved if Understandability is better

• Portability

– It is the ability of a component to be transferred from one environment to another. It is typically concerned with reuse of component on new platforms.

• There are many rules fed to FIM such as:– if Customizability of components is Low, Interaction

Complexity among component is High, Understandability is Low, Commonality is Low and Portability is Low then it is very difficult to maintain the system i.e. Reusability will be Very Low.

– If Customizability of components is Low, Interaction Complexity among component is High, Understandability is Low, Commonality is Medium and Portability is Medium then Reusability will be Low.

– Etc..,

Requirements Engineering

• Many of the Software development phases are highly communication-intensive activity that involves analysts, architects, developers, testers, business stakeholders, and end users.

• Among all the phases of software engineering, requirements are key ingredient

• So, the focus of every development methodology is on requirement engineering phase.

• Software development involves roughly 50 percent computing and 50 percent communication.

• Whenever human communication involve, various linguistic variables come into picture.

example

• For example, in object-oriented methods a candidate class is generally identified by applying the rule:

• If an entity in a requirement specification is relevant and exist autonomously then select it as a candidate class.

• This rule says "an entity is either a candidate class or not a candidate class but not both".

• The software engineer may sometimes conclude that the entity partially fulfils the relevance criterion, and may prefer to define the relevance of an entity, for instance, as substantially relevant. This definition would imply the classification of the entity as a partial class, which is considered as an inconsistent class definition by the current object-oriented methods.

example

• The rule should have been:• If an entity in a requirement specification is relevance-value

relevant and can exist autonomy value autonomous in the application domain, then select it as a relevance-value relevant candidate class. Here,– relevance and autonomy are the properties (inputs)– relevance-value and autonomy-value indicate the domains of these

properties.– Based on these domains and rules for the relevance of candidate class,

we can get the crisp output of candidate class

• For example, relevance-value may represent the set of values {Weakly, Slightly, Fairly, Substantially, Strongly}, and autonomy-value may represent the set of values {Dependently, Partially Dependently, Fully Autonomously}.

Autonomy Dependent Partiallydependent

Fully

Relevance

Weakly Weakly Weakly Weakly

Slightly Weakly Slightly Slightly

Fairly Weakly Slightly Fairly

Substantially Weakly Fairly Substantially

Strongly Slightly Fairly Strongly

Fuzzy Logic in Size estimation.

Size estimation

• To estimate the size of an object (to be created) using the sizes of predefined list of objects.

Advantages of size estimation

• Size estimation can be done in advance to make better plans

• To assist in tracking progress

• to learn and build estimating skills.

Uncertainty in estimation

• Estimation is an uncertain process

• Earlier you try to estimate, the less is the accuracy of estimation

Steps in size estimation

1. Gather size data on previously developed programs.

2. Divide the historical product size data into size ranges.

3. Compare the planned product with these prior products.

4. Based on this comparison, select the size that seems most appropriate for the new product.

Application of size estimation.

• A file utility of 1,844 LOC.

• A file management program of 5,834 LOC.

• A personnel record keeping program of 6,845 LOC.

• A report generating package of 18,386 LOC.

• An inventory management program of 25,943 LOC.

Steps in size estimation

• log(1844) = 3.266

• log(5834) = 3.766

• log(6845)= 3.835

• log(18386)= 4.2645

• log(25943)= 4.414

We will establish 5 size ranges, as follows:

3.122 – 3.409 (1,325 to 2,566) very small

3.409 – 3.696 ( 2,566 to 4,970) small

3.696 – 3.983 (4,970 to 9,626)medium

3.983 – 4.270 (9,626 to 18,641) large

4.270 – 4.557 (18,641 to 36,104) very large.

3.266 3.553 3.840 4.127 4.4143.122 3.409 3.696 3.983 4.270 4.557

• file utility very small

• file management program medium

• personnel record keeping programmedium

• A report generating package large

• An inventory management programverylarge

Analysis

• Suppose we want to estimate the size of a program “Analyze marketing”

• It is a substantially more complex application than either the file management or personnel programs. It is not as complex as the inventory management program and appears to have significantly more function than the report package. You conclude that the new program is in the lower end of “very large,” or from 18 to 25 KLOC.

Drawbacks of size estimation

• It requires a lot of data.

• It only provides a crude sizing.

• It is not useful for programs much larger or smaller than the historical data.

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