This study mainly focuses on how object-oriented analysis makes compatible with newly develop or other existing business computing application in a better way. This study also focuses on the modeling of the exact procedure or near to the exact procedure within its application domain which may model by using different objects class. Objects are basically structured into different classes of objects which are generally related to behaviors and characteristics. These methodologies may use different generalization, classification, and different aggregation as a structure object assemblies for the target actions like services or activities which are related to the objects. There are numerous misconceptions related to object oriented analysis which are required to address when we consider the use of any object-oriented method. In this paper try to represent different advantages and various application of the UML in the field of automatic system analysis and modeling. The platform presented here is a comprehensive range of the different UML templates with all other required information.
This document provides an overview of object-oriented concepts, principles, and software development. It defines key object-oriented terms like class, object, encapsulation, inheritance, and polymorphism. It also describes the three phases of object-oriented software development: object-oriented analysis, design, and construction. Object-oriented analysis identifies classes, objects, relationships, and system requirements. Design further develops the static and dynamic models. Construction implements the analysis and design models based on the programming language environment.
Object-Oriented Analysis (OOA) is a technique developed by Coad and Yourdon to model system functionality using objects. There are five major activities in OOA: (1) finding classes and objects, (2) identifying structures like generalization/specialization and whole-part, (3) identifying subjects, (4) defining attributes, and (5) defining services. OOA provides a consistent way to represent a problem domain using objects and can help tackle complex problems, improve communication between analysts and domain experts, and increase consistency while building resilient specifications that can be reused.
Software Design Patterns - An OverviewFarwa Ansari
The document summarizes different types of software design patterns. It discusses creational patterns, which deal with object creation mechanisms and increase flexibility. Examples include abstract factory, builder, factory method, prototype and singleton patterns. Structural patterns provide relationships between classes and objects, such as adapter, bridge, composite, and decorator. Behavioral patterns define communication between classes, for example chain of responsibility, command, interpreter, and observer. Design patterns are reusable solutions to common programming problems and increase flexibility and reuse in software design.
Survey on Supervised Method for Face Image Retrieval Based on Euclidean Dist...Editor IJCATR
This document summarizes various supervised methods for face image retrieval based on Euclidean distance. It discusses literature on active shape models, principal component analysis, linear discriminant analysis, locality-constrained linear coding, bag-of-words models, local binary patterns, and support vector machines. It evaluates support vector machines as the best classifier for face image retrieval systems due to its ability to significantly reduce the need for labeled training data and accurately classify faces, proteins, and characters. The document concludes that a content-based face retrieval system using support vector machines improves detection performance by retrieving similar faces from a database based on Euclidean distance calculations between local binary pattern features of the query and database images.
This document discusses conceptual data modeling and Entity-Relationship diagrams. It defines key terms like entities, attributes, relationships and cardinality. It explains how to represent these concepts in ER diagrams and discusses best practices for naming relationships and defining domains. The goals of conceptual data modeling are to accurately represent organizational data and rules through diagrams and establish consistency between the data, process and logic models.
EFFICIENT FEATURE SUBSET SELECTION MODEL FOR HIGH DIMENSIONAL DATAIJCI JOURNAL
This paper proposes a new method that intends on reducing the size of high dimensional dataset by
identifying and removing irrelevant and redundant features. Dataset reduction is important in the case of
machine learning and data mining. The measure of dependence is used to evaluate the relationship
between feature and target concept and or between features for irrelevant and redundant feature removal.
The proposed work initially removes all the irrelevant features and then a minimum spanning tree of
relevant features is constructed using Prim’s algorithm. Splitting the minimum spanning tree based on the
dependency between features leads to the generation of forests. A representative feature from each of the
forests is taken to form the final feature subset
Metadata and Cooperative Knowledge ManagementRalf Klamma
This document discusses cooperative knowledge management and its implications for metadata and conceptual modeling. It argues that current approaches like UML and ERP systems do not fully address the "culture facet" of knowledge work practices. Three relevant theories are reviewed: 1) a cultural science theory that views knowledge creation as cultural discourse influenced by changing media, 2) an organizational behavior theory that describes extracting, manipulating, and applying knowledge to practice, and 3) an engineering theory emphasizing refining knowledge from failures through scenario management. The document advocates for additional research on metadata management and conceptual modeling to better support cooperative knowledge work practices.
Object-oriented software engineering is a process that uses object-oriented concepts to solve customer problems and develop large, high-quality software systems efficiently. It views software as a collection of discrete objects that encapsulate their data and functionality. This methodology encourages modeling the real world as a system of cooperative objects. Benefits include faster development, reusability, increased quality, and easier maintenance compared to traditional approaches.
This document provides an overview of object-oriented concepts, principles, and software development. It defines key object-oriented terms like class, object, encapsulation, inheritance, and polymorphism. It also describes the three phases of object-oriented software development: object-oriented analysis, design, and construction. Object-oriented analysis identifies classes, objects, relationships, and system requirements. Design further develops the static and dynamic models. Construction implements the analysis and design models based on the programming language environment.
Object-Oriented Analysis (OOA) is a technique developed by Coad and Yourdon to model system functionality using objects. There are five major activities in OOA: (1) finding classes and objects, (2) identifying structures like generalization/specialization and whole-part, (3) identifying subjects, (4) defining attributes, and (5) defining services. OOA provides a consistent way to represent a problem domain using objects and can help tackle complex problems, improve communication between analysts and domain experts, and increase consistency while building resilient specifications that can be reused.
Software Design Patterns - An OverviewFarwa Ansari
The document summarizes different types of software design patterns. It discusses creational patterns, which deal with object creation mechanisms and increase flexibility. Examples include abstract factory, builder, factory method, prototype and singleton patterns. Structural patterns provide relationships between classes and objects, such as adapter, bridge, composite, and decorator. Behavioral patterns define communication between classes, for example chain of responsibility, command, interpreter, and observer. Design patterns are reusable solutions to common programming problems and increase flexibility and reuse in software design.
Survey on Supervised Method for Face Image Retrieval Based on Euclidean Dist...Editor IJCATR
This document summarizes various supervised methods for face image retrieval based on Euclidean distance. It discusses literature on active shape models, principal component analysis, linear discriminant analysis, locality-constrained linear coding, bag-of-words models, local binary patterns, and support vector machines. It evaluates support vector machines as the best classifier for face image retrieval systems due to its ability to significantly reduce the need for labeled training data and accurately classify faces, proteins, and characters. The document concludes that a content-based face retrieval system using support vector machines improves detection performance by retrieving similar faces from a database based on Euclidean distance calculations between local binary pattern features of the query and database images.
This document discusses conceptual data modeling and Entity-Relationship diagrams. It defines key terms like entities, attributes, relationships and cardinality. It explains how to represent these concepts in ER diagrams and discusses best practices for naming relationships and defining domains. The goals of conceptual data modeling are to accurately represent organizational data and rules through diagrams and establish consistency between the data, process and logic models.
EFFICIENT FEATURE SUBSET SELECTION MODEL FOR HIGH DIMENSIONAL DATAIJCI JOURNAL
This paper proposes a new method that intends on reducing the size of high dimensional dataset by
identifying and removing irrelevant and redundant features. Dataset reduction is important in the case of
machine learning and data mining. The measure of dependence is used to evaluate the relationship
between feature and target concept and or between features for irrelevant and redundant feature removal.
The proposed work initially removes all the irrelevant features and then a minimum spanning tree of
relevant features is constructed using Prim’s algorithm. Splitting the minimum spanning tree based on the
dependency between features leads to the generation of forests. A representative feature from each of the
forests is taken to form the final feature subset
Metadata and Cooperative Knowledge ManagementRalf Klamma
This document discusses cooperative knowledge management and its implications for metadata and conceptual modeling. It argues that current approaches like UML and ERP systems do not fully address the "culture facet" of knowledge work practices. Three relevant theories are reviewed: 1) a cultural science theory that views knowledge creation as cultural discourse influenced by changing media, 2) an organizational behavior theory that describes extracting, manipulating, and applying knowledge to practice, and 3) an engineering theory emphasizing refining knowledge from failures through scenario management. The document advocates for additional research on metadata management and conceptual modeling to better support cooperative knowledge work practices.
Object-oriented software engineering is a process that uses object-oriented concepts to solve customer problems and develop large, high-quality software systems efficiently. It views software as a collection of discrete objects that encapsulate their data and functionality. This methodology encourages modeling the real world as a system of cooperative objects. Benefits include faster development, reusability, increased quality, and easier maintenance compared to traditional approaches.
This document summarizes a research paper on developing a feature-based product recommendation system. It begins by introducing recommender systems and their importance for e-commerce. It then describes how the proposed system takes basic product descriptions as input, recognizes features using association rule mining and k-nearest neighbor algorithms, and outputs recommended additional features to improve the product profile. The paper evaluates the system's performance on recommending antivirus software features. In under 3 sentences.
This document provides a listing and brief descriptions of working papers from 2000. It includes 12 papers with titles and short 1-2 paragraph summaries of each paper's topic or focus. The papers cover a range of topics related to text mining, machine learning, data compression, knowledge discovery, and user interfaces for developing classifiers.
IRJET- Book Recommendation System using Item Based Collaborative FilteringIRJET Journal
This document describes an item-based collaborative filtering approach for a book recommendation system. It discusses different recommendation system techniques including collaborative filtering, content-based filtering, and hybrid filtering. It then focuses on item-based collaborative filtering, explaining how it calculates item similarities using adjusted cosine similarity and makes predictions using weighted sums. The document tests the approach on the Goodbooks10k dataset and evaluates it using mean absolute error, finding lower error rates with more neighbor items. In conclusion, item-based collaborative filtering is an effective approach for book recommendations.
COMPACT WEIGHTED CLASS ASSOCIATION RULE MINING USING INFORMATION GAINIJDKP
Weighted association rule mining reflects semantic significance of item by considering its weight.
Classification constructs the classifier and predicts the new data instance. This paper proposes compact
weighted class association rule mining method, which applies weighted association rule mining in the
classification and constructs an efficient weighted associative classifier. This proposed associative
classification algorithm chooses one non class informative attribute from dataset and all the weighted class
association rules are generated based on that attribute. The weight of the item is considered as one of the
parameter in generating the weighted class association rules. This proposed algorithm calculates the
weight using the HITS model. Experimental results show that the proposed system generates less number of
high quality rules which improves the classification accuracy.
Feature Selection Algorithm for Supervised and Semisupervised ClusteringEditor IJCATR
This document summarizes a research paper on feature selection algorithms for supervised and semi-supervised clustering. It discusses how semi-supervised learning uses both labeled and unlabeled data for training, between unsupervised and supervised learning. It also describes a fast clustering-based feature selection algorithm (FAST) that works in two steps: 1) using graph-theoretic clustering to separate features into clusters, and 2) selecting the most representative feature from each cluster to form a subset of features. The algorithm aims to efficiently obtain a good feature subset by removing unrelated and redundant features.
IRJET - Recommendation System using Big Data Mining on Social NetworksIRJET Journal
The document describes a job recommendation system that uses machine learning algorithms and natural language processing on data collected from social networks. It uses naive Bayes, logistic regression, and random forest models to recommend jobs to users based on their profiles. The system tokenizes and lemmatizes words from user input before making recommendations. Evaluation of the models found naive Bayes had the highest training accuracy at 94.56% but lowest testing accuracy at 69.19%, while random forest had the highest testing accuracy at 70%.
Recommender systems have grown to be a critical research subject after the emergence of the first paper on collaborative filtering in the Nineties. Despite the fact that educational studies on recommender systems, has extended extensively over the last 10 years, there are deficiencies in the complete literature evaluation and classification of that research. Because of this, we reviewed articles on recommender structures, and then classified those based on sentiment analysis. The articles are categorized into three techniques of recommender system, i.e.; collaborative filtering (CF), content based and context based. We have tried to find out the research papers related to sentimental analysis based recommender system. To classify research done by authors in this field, we have shown different approaches of recommender system based on sentimental analysis with the help of tables. Our studies give statistics, approximately trends in recommender structures research, and gives practitioners and researchers with perception and destiny route on the recommender system using sentimental analysis. We hope that this paper enables all and sundry who is interested in recommender systems research with insight for destiny.
The Statement of Conjunctive and Disjunctive Queries in Object Oriented Datab...Editor IJCATR
Entrance of object orienting concept in database caused the relation database gradually to replace with object oriented
database in various fields. On the other hand for solving the problem of real world uncertain data, several methods were presented.
One of these methods for modeling database is an approach wich couples object-oriented database modeling with fuzzy logic. Many
queries that users to pose are expressed on the basis of linguistic variables. Because of classical databases are not able to support these
variables, leads to fuzzy approaches are considered. We investigate databases queries in this study both simple and complex ways. In
the complex way, we use conjunctive and disjunctive queries. In the following, we use the XML labels to express inqueries into fuzzy.
We can also communicate with other sections of software by entering into XML world as the most reliable opportunity. Also we want
to correct conjunctive and disjunctive queries related to fuzzy object oriented database using the concept of dependency measure and
weight, and weight be assigned to different phrases of a query based on user emphasis. The other aim of this research is mapping fuzzy
queries to fuzzy-XML. It is expected to be simple implement of query, and output of execution of queries be greatly closer to users'
needs and fulfill her expect. The results show that the proposed method explains the possible conjunctive and disjunctive queries the
database in the form of Fuzzy-XML.
A Novel Approach for Travel Package Recommendation Using Probabilistic Matrix...IJSRD
This document proposes a novel approach for travel package recommendation using probabilistic matrix factorization (PMF). It discusses how existing recommendation systems are usually classification-based and supervised, whereas the proposed approach uses an unsupervised E-TRAST (Efficient-Tourist Relation Area Season Topic) model. The E-TRAST model represents travel packages and tourists using different topics modeled through PMF. It analyzes travel data characteristics and introduces a cocktail approach considering features like seasonal tourist performance to recommend customized travel packages.
SIMILARITY MEASURES FOR RECOMMENDER SYSTEMS: A COMPARATIVE STUDYJournal For Research
Recommender Systems have the ability to guide the users in a personalized way to interesting items in a large space of possible options. They have fundamental applications in e-commerce and information retrieval, providing suggestion that prune large information spaces so that users are directed towards those items that best meets the needs and preferences. A variety of approaches have been proposed but collaborative filtering has been the most popular and widely used which makes use of various similarity measures to calculate the similarity. Collaborative Filtering takes the user feedback in the form of ratings in an application area and uses it to find similarities and differences between user profiles to generate recommendations. Collaborative Filtering makes use of various similarity measures to calculate the similarity or difference between the users. This paper provides an overview on few important similarity measures that are currently being used. Different similarity measures provide different results against same input parameters. So, to understand how various similarity measures behave when they are put in different contexts but with same input, few observations are made. This paper also provides a comparison graph to help understand the results of different similarity measures.
The document discusses various information retrieval models, including:
1) Classic models like Boolean and vector space models that use index terms to represent documents and queries.
2) Probabilistic models that view IR as estimating the probability of relevance between documents and queries.
3) Structured models that incorporate document structure, including models based on non-overlapping text regions and hierarchical document structure.
4) Browsing models like flat, structure-guided, and hypertext models for navigating document collections.
This document provides an overview of data modeling, including definitions of key concepts like data models and data modeling. It describes the evolution of popular data models from hierarchical to network to relational to entity-relationship to object-oriented models. For each model, it outlines the basic concepts, advantages, and disadvantages. The document emphasizes that newer data models aimed to address shortcomings of previous approaches and capture real-world data and relationships.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Formal Models for Context Aware ComputingEditor IJCATR
Context-aware computing refers to a general class of mobile systems that can sense their physical environment, and
adapt their behavior accordingly. In this paper we seek to develop a systematic understanding of context-aware computing by
constructing a formal model and notation for expressing context-aware computations. This discussion is followed by a
description and comparison of current context modeling and reasoning techniques.
Effective Feature Selection for Feature Possessing Group Structurerahulmonikasharma
This document proposes a new method called efficient group variable selection (EGVS) for feature selection when features have a group structure. EGVS has two stages: 1) within-group variable selection evaluates each feature individually to select discriminative features within each group. 2) Between-group variable selection re-evaluates all features to remove redundancy and obtain an optimal subset by considering relationships between groups. The method is demonstrated on benchmark datasets, showing it increases classification accuracy by leveraging the group structure during feature selection.
A STUDY ON SIMILARITY MEASURE FUNCTIONS ON ENGINEERING MATERIALS SELECTION cscpconf
This document presents a study on using similarity measure functions to select engineering materials from a database. Thirteen similarity/distance functions are examined to quantify the similarity between materials based on their properties. A performance index measure is used to evaluate how well a selected material matches the target material. The materials are ranked based on their normalized performance index values. An algorithm is presented that takes a target material, calculates similarities to materials in a database using different functions, computes performance indexes, and selects the material with the minimum normalized performance index as the best match. Experimental results applied the approach to select materials from a database of 5670 materials that best match a target material described by 25 properties.
The use of genetic algorithm, clustering and feature selection techniques in ...IJMIT JOURNAL
Decision tree modelling, as one of data mining techniques, is used for credit scoring of bank customers.
The main problem is the construction of decision trees that could classify customers optimally. This study
presents a new hybrid mining approach in the design of an effective and appropriate credit scoring model.
It is based on genetic algorithm for credit scoring of bank customers in order to offer credit facilities to
each class of customers. Genetic algorithm can help banks in credit scoring of customers by selecting
appropriate features and building optimum decision trees. The new proposed hybrid classification model is
established based on a combination of clustering, feature selection, decision trees, and genetic algorithm
techniques. We used clustering and feature selection techniques to pre-process the input samples to
construct the decision trees in the credit scoring model. The proposed hybrid model choices and combines
the best decision trees based on the optimality criteria. It constructs the final decision tree for credit
scoring of customers. Using one credit dataset, results confirm that the classification accuracy of the
proposed hybrid classification model is more than almost the entire classification models that have been
compared in this paper. Furthermore, the number of leaves and the size of the constructed decision tree
(i.e. complexity) are less, compared with other decision tree models. In this work, one financial dataset was
chosen for experiments, including Bank Mellat credit dataset.
Generating requirements analysis models from textual requiremenfortes
This document describes a process for generating use case models from textual requirements. The process uses the EA-Miner tool to analyze textual requirements and extract information like functional concerns, RDL sentences, and a syntactically tagged document. This extracted information is used to derive initial candidate use cases, actors, and relationships. The candidate model is then refined by activities like removing undesirable use cases, completing abstraction names, adding new use cases/actors, and defining relationships between use cases. The overall goal is to reduce the time and effort required to produce requirements artifacts from textual specifications.
This document discusses object-oriented concepts and modeling. It begins by listing three textbooks on these topics. It then provides an overview of object-oriented concepts like objects, classes, inheritance, polymorphism, and encapsulation. It describes the stages of object-oriented analysis, design and implementation. It discusses the three main models used in object-oriented modeling: class models, state models, and interaction models. Finally, it covers object-oriented themes like abstraction, encapsulation, and polymorphism and the purposes of modeling.
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
Object-oriented analysis and design is an evolutionary development method built upon past proven concepts. The document discusses object-oriented systems development processes including use case driven analysis, the Object Modeling Technique (OMT), class diagrams, relationships between classes, and object-oriented modeling. It provides examples of class diagrams showing classes, attributes, operations, and relationships. It also explains the four views of OMT - the object model, dynamic model, functional model, and how OMT separates modeling.
Object oriented analysis emphasizes investigating the problem domain to identify relevant objects and their relationships. The key goals are to define relevant classes and their attributes, operations, relationships, and behaviors through iterative refinement. Various analysis methods take different approaches, but generally involve use case modeling, class modeling, and behavior modeling.
This document summarizes a research paper on developing a feature-based product recommendation system. It begins by introducing recommender systems and their importance for e-commerce. It then describes how the proposed system takes basic product descriptions as input, recognizes features using association rule mining and k-nearest neighbor algorithms, and outputs recommended additional features to improve the product profile. The paper evaluates the system's performance on recommending antivirus software features. In under 3 sentences.
This document provides a listing and brief descriptions of working papers from 2000. It includes 12 papers with titles and short 1-2 paragraph summaries of each paper's topic or focus. The papers cover a range of topics related to text mining, machine learning, data compression, knowledge discovery, and user interfaces for developing classifiers.
IRJET- Book Recommendation System using Item Based Collaborative FilteringIRJET Journal
This document describes an item-based collaborative filtering approach for a book recommendation system. It discusses different recommendation system techniques including collaborative filtering, content-based filtering, and hybrid filtering. It then focuses on item-based collaborative filtering, explaining how it calculates item similarities using adjusted cosine similarity and makes predictions using weighted sums. The document tests the approach on the Goodbooks10k dataset and evaluates it using mean absolute error, finding lower error rates with more neighbor items. In conclusion, item-based collaborative filtering is an effective approach for book recommendations.
COMPACT WEIGHTED CLASS ASSOCIATION RULE MINING USING INFORMATION GAINIJDKP
Weighted association rule mining reflects semantic significance of item by considering its weight.
Classification constructs the classifier and predicts the new data instance. This paper proposes compact
weighted class association rule mining method, which applies weighted association rule mining in the
classification and constructs an efficient weighted associative classifier. This proposed associative
classification algorithm chooses one non class informative attribute from dataset and all the weighted class
association rules are generated based on that attribute. The weight of the item is considered as one of the
parameter in generating the weighted class association rules. This proposed algorithm calculates the
weight using the HITS model. Experimental results show that the proposed system generates less number of
high quality rules which improves the classification accuracy.
Feature Selection Algorithm for Supervised and Semisupervised ClusteringEditor IJCATR
This document summarizes a research paper on feature selection algorithms for supervised and semi-supervised clustering. It discusses how semi-supervised learning uses both labeled and unlabeled data for training, between unsupervised and supervised learning. It also describes a fast clustering-based feature selection algorithm (FAST) that works in two steps: 1) using graph-theoretic clustering to separate features into clusters, and 2) selecting the most representative feature from each cluster to form a subset of features. The algorithm aims to efficiently obtain a good feature subset by removing unrelated and redundant features.
IRJET - Recommendation System using Big Data Mining on Social NetworksIRJET Journal
The document describes a job recommendation system that uses machine learning algorithms and natural language processing on data collected from social networks. It uses naive Bayes, logistic regression, and random forest models to recommend jobs to users based on their profiles. The system tokenizes and lemmatizes words from user input before making recommendations. Evaluation of the models found naive Bayes had the highest training accuracy at 94.56% but lowest testing accuracy at 69.19%, while random forest had the highest testing accuracy at 70%.
Recommender systems have grown to be a critical research subject after the emergence of the first paper on collaborative filtering in the Nineties. Despite the fact that educational studies on recommender systems, has extended extensively over the last 10 years, there are deficiencies in the complete literature evaluation and classification of that research. Because of this, we reviewed articles on recommender structures, and then classified those based on sentiment analysis. The articles are categorized into three techniques of recommender system, i.e.; collaborative filtering (CF), content based and context based. We have tried to find out the research papers related to sentimental analysis based recommender system. To classify research done by authors in this field, we have shown different approaches of recommender system based on sentimental analysis with the help of tables. Our studies give statistics, approximately trends in recommender structures research, and gives practitioners and researchers with perception and destiny route on the recommender system using sentimental analysis. We hope that this paper enables all and sundry who is interested in recommender systems research with insight for destiny.
The Statement of Conjunctive and Disjunctive Queries in Object Oriented Datab...Editor IJCATR
Entrance of object orienting concept in database caused the relation database gradually to replace with object oriented
database in various fields. On the other hand for solving the problem of real world uncertain data, several methods were presented.
One of these methods for modeling database is an approach wich couples object-oriented database modeling with fuzzy logic. Many
queries that users to pose are expressed on the basis of linguistic variables. Because of classical databases are not able to support these
variables, leads to fuzzy approaches are considered. We investigate databases queries in this study both simple and complex ways. In
the complex way, we use conjunctive and disjunctive queries. In the following, we use the XML labels to express inqueries into fuzzy.
We can also communicate with other sections of software by entering into XML world as the most reliable opportunity. Also we want
to correct conjunctive and disjunctive queries related to fuzzy object oriented database using the concept of dependency measure and
weight, and weight be assigned to different phrases of a query based on user emphasis. The other aim of this research is mapping fuzzy
queries to fuzzy-XML. It is expected to be simple implement of query, and output of execution of queries be greatly closer to users'
needs and fulfill her expect. The results show that the proposed method explains the possible conjunctive and disjunctive queries the
database in the form of Fuzzy-XML.
A Novel Approach for Travel Package Recommendation Using Probabilistic Matrix...IJSRD
This document proposes a novel approach for travel package recommendation using probabilistic matrix factorization (PMF). It discusses how existing recommendation systems are usually classification-based and supervised, whereas the proposed approach uses an unsupervised E-TRAST (Efficient-Tourist Relation Area Season Topic) model. The E-TRAST model represents travel packages and tourists using different topics modeled through PMF. It analyzes travel data characteristics and introduces a cocktail approach considering features like seasonal tourist performance to recommend customized travel packages.
SIMILARITY MEASURES FOR RECOMMENDER SYSTEMS: A COMPARATIVE STUDYJournal For Research
Recommender Systems have the ability to guide the users in a personalized way to interesting items in a large space of possible options. They have fundamental applications in e-commerce and information retrieval, providing suggestion that prune large information spaces so that users are directed towards those items that best meets the needs and preferences. A variety of approaches have been proposed but collaborative filtering has been the most popular and widely used which makes use of various similarity measures to calculate the similarity. Collaborative Filtering takes the user feedback in the form of ratings in an application area and uses it to find similarities and differences between user profiles to generate recommendations. Collaborative Filtering makes use of various similarity measures to calculate the similarity or difference between the users. This paper provides an overview on few important similarity measures that are currently being used. Different similarity measures provide different results against same input parameters. So, to understand how various similarity measures behave when they are put in different contexts but with same input, few observations are made. This paper also provides a comparison graph to help understand the results of different similarity measures.
The document discusses various information retrieval models, including:
1) Classic models like Boolean and vector space models that use index terms to represent documents and queries.
2) Probabilistic models that view IR as estimating the probability of relevance between documents and queries.
3) Structured models that incorporate document structure, including models based on non-overlapping text regions and hierarchical document structure.
4) Browsing models like flat, structure-guided, and hypertext models for navigating document collections.
This document provides an overview of data modeling, including definitions of key concepts like data models and data modeling. It describes the evolution of popular data models from hierarchical to network to relational to entity-relationship to object-oriented models. For each model, it outlines the basic concepts, advantages, and disadvantages. The document emphasizes that newer data models aimed to address shortcomings of previous approaches and capture real-world data and relationships.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Formal Models for Context Aware ComputingEditor IJCATR
Context-aware computing refers to a general class of mobile systems that can sense their physical environment, and
adapt their behavior accordingly. In this paper we seek to develop a systematic understanding of context-aware computing by
constructing a formal model and notation for expressing context-aware computations. This discussion is followed by a
description and comparison of current context modeling and reasoning techniques.
Effective Feature Selection for Feature Possessing Group Structurerahulmonikasharma
This document proposes a new method called efficient group variable selection (EGVS) for feature selection when features have a group structure. EGVS has two stages: 1) within-group variable selection evaluates each feature individually to select discriminative features within each group. 2) Between-group variable selection re-evaluates all features to remove redundancy and obtain an optimal subset by considering relationships between groups. The method is demonstrated on benchmark datasets, showing it increases classification accuracy by leveraging the group structure during feature selection.
A STUDY ON SIMILARITY MEASURE FUNCTIONS ON ENGINEERING MATERIALS SELECTION cscpconf
This document presents a study on using similarity measure functions to select engineering materials from a database. Thirteen similarity/distance functions are examined to quantify the similarity between materials based on their properties. A performance index measure is used to evaluate how well a selected material matches the target material. The materials are ranked based on their normalized performance index values. An algorithm is presented that takes a target material, calculates similarities to materials in a database using different functions, computes performance indexes, and selects the material with the minimum normalized performance index as the best match. Experimental results applied the approach to select materials from a database of 5670 materials that best match a target material described by 25 properties.
The use of genetic algorithm, clustering and feature selection techniques in ...IJMIT JOURNAL
Decision tree modelling, as one of data mining techniques, is used for credit scoring of bank customers.
The main problem is the construction of decision trees that could classify customers optimally. This study
presents a new hybrid mining approach in the design of an effective and appropriate credit scoring model.
It is based on genetic algorithm for credit scoring of bank customers in order to offer credit facilities to
each class of customers. Genetic algorithm can help banks in credit scoring of customers by selecting
appropriate features and building optimum decision trees. The new proposed hybrid classification model is
established based on a combination of clustering, feature selection, decision trees, and genetic algorithm
techniques. We used clustering and feature selection techniques to pre-process the input samples to
construct the decision trees in the credit scoring model. The proposed hybrid model choices and combines
the best decision trees based on the optimality criteria. It constructs the final decision tree for credit
scoring of customers. Using one credit dataset, results confirm that the classification accuracy of the
proposed hybrid classification model is more than almost the entire classification models that have been
compared in this paper. Furthermore, the number of leaves and the size of the constructed decision tree
(i.e. complexity) are less, compared with other decision tree models. In this work, one financial dataset was
chosen for experiments, including Bank Mellat credit dataset.
Generating requirements analysis models from textual requiremenfortes
This document describes a process for generating use case models from textual requirements. The process uses the EA-Miner tool to analyze textual requirements and extract information like functional concerns, RDL sentences, and a syntactically tagged document. This extracted information is used to derive initial candidate use cases, actors, and relationships. The candidate model is then refined by activities like removing undesirable use cases, completing abstraction names, adding new use cases/actors, and defining relationships between use cases. The overall goal is to reduce the time and effort required to produce requirements artifacts from textual specifications.
This document discusses object-oriented concepts and modeling. It begins by listing three textbooks on these topics. It then provides an overview of object-oriented concepts like objects, classes, inheritance, polymorphism, and encapsulation. It describes the stages of object-oriented analysis, design and implementation. It discusses the three main models used in object-oriented modeling: class models, state models, and interaction models. Finally, it covers object-oriented themes like abstraction, encapsulation, and polymorphism and the purposes of modeling.
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Object-Oriented Analysis and Design
1. International Journal of Advanced Engineering and Management
Vol. 1, No.1, PP.18-24, 2016
Received on: 28.11.2016,
Revised on: 20.12.2016,
www.ijoaem.com
Object-Oriented Analysis and Design
Authors: M. Mukherjee
International Journal of Advanced Engineering and Management,
India e-mail: editorijoaem@gmail.com
Subject Category:
Sub Category:
Management
System Management
Editor: M. Mukherjee
Keywords: Activity diagram;
Activities performed in object-oriented analysis;
Object-oriented analysis;
UML Diagram.
Paper No. 3
M . Mukherjee, "Object-Oriented Analysis and Design," International Journal of Advanced
Engineering and Management, Vol. 1, No. 1, pp. 18-24 , 2016. 18
2. International Journal of Advanced Engineering and Management
Vol. 1, No.1, PP.18-24, 2016
Received on: 28.11.2016,
Revised on: 20.12.2016,
www.ijoaem.com
Object-Oriented Analysis and Design
M. Mukherjee
Abstract
This study mainly focuses on how object-oriented analysis makes compatible with newly develop or other existing
business computing application in a better way. This study also focuses on the modeling of the exact procedure or
near to the exact procedure within its application domain which may model by using different objects class. Objects
are basically structured into different classes of objects which are generally related to behaviors and characteristics.
These methodologies may use different generalization, classification, and different aggregation as a structure object
assemblies for the target actions like services or activities which are related to the objects. There are numerous
misconceptions related to object oriented analysis which are required to address when we consider the use of any
object-oriented method. In this paper try to represent different advantages and various application of the UML in the
field of automatic system analysis and modeling. The platform presented here is a comprehensive range of the
different UML templates with all other required information.
1. Introduction
Object-oriented analysis and design (OOAD) is a globally accepted technical process for manipulative an
application specific, business or system model, and simple graphical diagram for analyzing and product quality
improvement by applying the object-oriented prototype method [1]. Object Oriented Analysis (OOA) is basically
collected works of concurring or cascading system modeling, incorporate various requirements and pre and post
analysis methodology for software systems. These methodologies are primarily influenced by different object-
oriented programming, data modeling and systematic interconnections [2]. Fundamental idea behind OOA is a
streamline software design and development by considering all model as a discreet objects, classes, methods and by
linking these one can designs and implement all kind of business requirements [3]. It mainly focused on the system
development and analysis. This study also focus on how it make compatible with newly develop or other existing
business computing application in better way. In the late 80‘s and 90‘s there were many different object-oriented
methods and modeling techniques used what limited sharing of models across projects (reduced reusability) and
hampered communication between team members and users. The main objective of any model is to build a distinct,
globally accepted standard procedure for object-oriented systems software [4]. Unified Modeling Language (UML)
is one of the standard widely accepted languages, generally is used for modeling any system considering as objects
for better analysis [5]. Such techniques mainly focus on the modeling of the exact procedure or near to the exact
procedure within its application domain which may model by using different objects class. These methodologies
may used different generalization, classification and different aggregation as a structure object assemblies for the
target actions like services or activities which are related with the objects. It can be implemented by MATLAB also
[6]. The major difficulty of preventing object oriented code and reuse code by different attackers is a major
challenges [7]. State changes may be affected the actions which are performed by that objects. There are numerous
misconceptions related to object oriented analysis which are required to address when we consider the use of any
object-oriented method.
2. Some familiar terms related to OOA
a) Object
It may sensed by one or more by our sensing organs like vision, touched, etc. or by which users able to store data
and correlate its behavior.
b) Attributes
This is basically all the information and different types of data which are used to describe the object characteristics
of interest.
c) Behaviour
It is basically refers to as a methodology, procedure, operation or service that the object able to correspond to any
functions which may be operate on the object‘s attributes or data.
M. Mukherjee, "Object-Oriented Analysis and Design," International Journal of Advanced
Engineering and Management, Vol. 1, No. 1, pp. 18-24 , 2016. 19
3. International Journal of Advanced Engineering and Management
Vol. 1, No.1, PP.18-24, 2016
Received on: 28.11.2016,
Revised on: 20.12.2016,
www.ijoaem.com
d) Inheritance
It may consider as general model or methods which may be reused by another object class intrinsically.
e) Encapsulation
It is basically binding or packaging of a number of items and operation together into a single unit which is also
known as to as the information biding. Different attributes and characteristics of the target object, both are both are
considered as the part of the target object and also packed together. The only possible technique to change or access
any attributes by changing specified behaviors of that object‘s which may consider as different object.
f) Class
It is basically a collection of different objects or objects set which are share their behavior and attributes. It is also
known as object class.
g) Generalization/specialization
It is basically a process or technique for widely reuses of inheritance, where the common attributes and
characteristics of several object classes are merging or clubbing together to form a general class. Sometimes it
referred as generalization class. The particular or set of methods and attributes of the mother object class are known
as specialization.
h) Object/class relationship
In general business organization may exists different relations among one or more objects or classes. Many
developers consider the class diagrams are complicated ones.
i) Multiplicity
It described how different instances of the particular object or class may associated with particular instance of the
other object or class.
j) Aggregation
It may describe as a special kind of relationship, which shows that some objects or classes are prepared by using
other objects or classes. By recognizing proper aggregation and interactions, one can able to separate any
complicated object by assigning different characteristics and attributes to the individual class or objects. There are
two types of aggregation relationships: (i) composition aggregate relationships among object classes all part-objects
make up and live in the whole-object, (ii) shared aggregation relationships, which imply that parts may be shared
with others.
k) Message
The message required to pass mainly when one of the objects requested for information from the one or more of
different objects for some particular action or a set of actions [8].
l) Polymorphism
It generally used for ―many forms‖ which are mainly applied any object-oriented process. The same attribute,
behavior or characteristics are accomplished by other objects or classes. What is important in message sending is
that the requested object or slave object previously knows what type of services to request come and from where.
3. UML diagrams
UML generally offers a graphical model of a system by using different groups based on its functionality. All UML
diagram or models prepared by the development expert are based on the various perspectives of the data and
information system [9]. The different types of UML diagrams and their objects are briefly discussed here:
(i) Use Case Diagrams: By using various type of graph, the structure illustrate the connections among the internal
systems and also different external systems along with end users [10]. It also graphically explains where this
model use and the various ways the end user may interact with the target system.
(ii) Class Diagrams: They represent the fundamental structure of the system‘s objectives. This may show how
object classes is smartly composed and maintain both inter and intra relationships between different object classes
purposefully.
(iii) Object Diagrams: It is quite analogous to the class diagrams but instead of describe the object classes it
replicate the actual object characteristics.
(iv) Sequence Diagrams: It illustrates graphically how different objects may interact or communicate between them
via passing various messages in the time of execution for any use case type operations. It also describe how
messages are transmitted and how it received maintaining the predefine sequence.
M . Mukherjee, "Object-Oriented Analysis and Design," International Journal of Advanced
Engineering and Management, Vol. 1, No. 1, pp. 18-24 , 2016. 20
4. International Journal of Advanced Engineering and Management
Vol. 1, No.1, PP.18-24, 2016
Received on: 28.11.2016,
Revised on: 20.12.2016,
www.ijoaem.com
(v) Collaboration Diagrams: It is analogous to the sequence diagrams only the difference it is not follow timing and
progression of messages. It may used to represent the inter communication between different objects in the
network.
(vi) Activity Diagrams: It is basically used for graphically modeling illustrates the sequential dataflow of various
activities may be business progression or any use case.
(vii) State Diagrams: It is used for modeling the various dynamic behavior of any particular object or class. It may
also describe a particular object‘s life cycle. The different states of the object may be considered as events which
cause state transaction.
(viii) Component Diagrams: This diagram frequently used for graphically describe any system physical
architecture.
(ix) Deployment Diagrams: It is used for represent the physical architectures of the both software and hardware of
any particular system. Different popular symbolic notations are used in UML class diagrams are shown in Fig. 1.
Association Club Members
Directed Hospital Patient
Association
Reflexive * Course
Associations
Prerequisite
Successor *
Multiplicity 2··*
Player
Gam
e
Composition
1···*
College Department
Aggregation
1···*
Library Books
Inheritance
Realization
Figure 1. Popular symbolic notations are used in UML class diagrams.
4. Activities performed in object-oriented analysis
There are four general activities are essential for any object-oriented analysis which are briefly discussed here.
a) Functions Modelling Techniques
These processes are usually used for modeling of the functional characteristics of the target systems [11]. The Use
Case modeling basically is the common method of any kind of system‘s functions modeling related to any business
events. It basically correlated between all events creators, and also how the system provides responds for any
particular events. Usually the Use Case behaviorally correlated all sequence of scenario or steps among the both
automated and manual procedure for implementation a particular business task. This may triggered or initiated by
any external users or by any systems, popularly known as Actors. The Actor may be representing anything which
are required to interact or communicate with the system for information exchange. In many business events related
information systems are automatically triggered by the particular date and time which is known as temporal event.
The Use Cases structure have few advantages like (i) it help to identify different objects easily and also their
different responsibilities and high-level relationships, (ii) it may provide a clear view of the system performance,
(iii) it may use an helpful tool for validating different requirements, (iii) it may use as an effective communication
tool and as a user‘s guide or manual.
Steps involved in use case modeling are (i) identify different factors and all type of use cases, (ii) required to
construct a diagram using simple graphically model by using Use Case. It simply illustrate different system scope
and its boundaries, which characterized the required relationships among the factors and the Use Cases for the all
business subsystems, (iii) document the use case course of the events – only general information about the business
event (typical and alternative courses), which is called requirements use case, (iv) define the analysis use cases –
M . Mukherjee, "Object-Oriented Analysis and Design," International Journal of Advanced
Engineering and Management, Vol. 1, No. 1, pp. 18-24 , 2016. 21
5. International Journal of Advanced Engineering and Management
Vol. 1, No.1, PP.18-24, 2016
Received on: 28.11.2016,
Revised on: 20.12.2016,
www.ijoaem.com
more information regarding each use case, which specifies the systems functionality in detail but without any
implementation details. When the use case contains complex functionality we can simplify it by extracting the
more complicated process for their own use cases, which are called extension use cases; an extension of the Use
Case which may be call upon only by it is extend use case. Sometimes there may be use cases performing steps of
identical functionality. They can be than extracted into separate use case of its own, which is familiar as abstract
use case. It represents a form of ―reuse‖ and may be further used for further Use Case structure which may
required its particular characteristics or functionality.
b) Finding and identifying the business objects
Steps involved in identifying and finding business objects for object modeling: (i) find the potential objects – the
best way is to review and reanalysis each and every use case to locate nouns which correspond to all business
events or entities, (ii) chose the planned objects and prepare a list contains all potential business entities. The list
time to time must be cleaned up by removing: unclear nouns which focus on really actions or attributes, nouns
which is outside the scope of the desired system, nouns without any unique activities or any external roles and also
all synonyms.
c) Organizing the objects and identifying their relationships
A class diagram is mainly used for graphically illustrate all the identified objects and also their associations and
relationships. In these graphical diagrams, user also able to include multiplicity, associations, aggregation of
generalized and specialized relationships.
Steps generally use to construct any class diagrams are discussed here:
(i) Identify associations and multiplicity – association between any two objects or classes are required to know
about the each other; to help insure that all possible relationships are identified we can create an object/class
matrix.
(ii) Identify generalization/specialization relationships – we should look for all one-to-one multiplicity
relationships between objects because they may be gen/spec relationships as well as for objects that have
common attributes and behaviors.
(iii) Identify aggregation relationships – we must remember that aggregation relationships do not imply inheritance.
The object, which is the part of another object does not inherit attributes or behavior commencing the whole
object), but they propagate behaviors. The behaviors which are applied to the entire system are automatically
applied to the each and every part of the sub-systems and sub-modules.
(iv) Prepare the class diagram as per requirement.
d) Modelling the behaviour of the objects
All object have a state, which is the significance attributes at any time instance. An object may change it state when
something insists to changes or when it‘s any attributes change. These changes in any state may triggered by an
external or internal events [12]. Any state diagram is the models of a single object life cycle. It may illustrate the
various states of an object may have. Events causes‘ the state change of the target object by some predefine rules
that direct the object‘s state transition. State diagrams are not essentially required for all objects or class. Typically
a state diagram may assemble only for individuals‘ objects that undoubtedly have particular states and may have
composite behavior.
5. Discussion
Using object-oriented analysis, it may possible improved reliability and flexibility, code reusability, reduced
maintenance cost and also real world modeling. Though, practically few users realize that the OOA different
benefits may not as persuasive as original. The OOA codes may reuse in comparison with other programming
language. Basically code reusability depends on how the system is defined and also a subjective thing. This method
does have the capability to minimize few major operating expense related with the model or structure, such as
system may essentially required maintenance and also continues development of the general programming template
and code data structures. We discuss here few common benefits of this approach:
a) Real-world modelling
Objects are basically structured into different classes of unique objects and generally correlated or associated with
all behaviors and characteristics. Object-oriented systems are able to model any type of business organization or
service provider as like as the real world. It generally models the whole system in a more complete fashion in
comparisons with other traditional approach.
M . Mukherjee, "Object-Oriented Analysis and Design," International Journal of Advanced
Engineering and Management, Vol. 1, No. 1, pp. 18-24 , 2016. 22
6. International Journal of Advanced Engineering and Management
Vol. 1, No.1, PP.18-24, 2016
Received on: 28.11.2016,
Revised on: 20.12.2016,
www.ijoaem.com
b) Maintenance cost reduction
One of the desire goals of any object-oriented system developments are must have a larger life span at reasonable
or very low maintenance costs. Since almost all of the processes are encapsulated, the behaviors can reuse and it
may incorporate into new characteristics or behaviors.
c) Code Reusability
Code reusability is another desired advantage of any programmer. When any new object or class is designed, the
characteristics and data attributes of the target class is automatically inherited. The new created object may also
able to inherit all the super-classes data and behaviors in which it is participate. When an end user design a new
widget, the new design object may acts as "wigitty", also it has new characteristics or behaviors which are quite
similar with parents system.
d) Reliability and flexibility improvement
In general object-oriented systems are assured its reliability than other traditional systems, above all due to new
behaviors or characteristics possible to generate from the existing objects or classes. These can be randomly and
dynamically called and also accessed. It is also possible to create a new object at any time as per requirement or as
per demand. The new objects can be able inherit all type of data and their attributes from one, or many other class
or objects. All such behaviors and characteristics may be obtained or inherited from the parents‘ class or super-
classes, and any or collective novel characteristics may be enriched by adding without affecting or changing the
existing systems or its any functions. Object-oriented Development is not considered as a technology and object; it
is not yet completely accepted by all the major vendors globally. Although many organizations are try to promote
object-oriented systems. Another challenge is less number of qualified programmers and DBA's available in this
field. When one tries to investigate the common recognition of the object-oriented systems in any organization or
any commercial marketplace, it discovers that most of the managers see that an technology approach as computer
applications, but they not train their staffs this methods.
6. Conclusion
For any systems designer or programmer, building or analyzing class diagrams are essential after the construction
of different blocks of OOA. As presented in this paper, all type of class diagram relations are very simple and easy
to realize. As a trial and error methods, design class graphical diagrams in very simple possible ways may allows
quite simple to understand and easily realized by programmer and also end user. For this target, designer must put
label to all classes or objects and different interaction as elaborative as much feasible. Lastly, the object model or
class models develop as like as the real time systems it must indicate the system change. This may imply that we
don‘t require putting all small detail in the first draft design. Generally all the model classes or objects are interlink
or interfaces and all required relationships which are essential for the system or graphical application design may
ultimately materialize as this advance process moves forward. For the developer job easier, one can able to tally the
online diagram, various application and examples offered in the different web site. Additionally, different platform
also supports various type of collaboration and able to integrate into others to keep the new diagrams proper
documented and updated for all. This tool must greatly development initiatives and also helpful for any
organization to meet their targets. Object-oriented development is one of the best solutions for any interactive static
as well as dynamic environments. Many large-scale object-oriented organizations are still under development and
much simple information are still required for systems applications.
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Engineering and Management, Vol. 1, No. 1, pp. 18-24 , 2016. 23
7. International Journal of Advanced Engineering and Management
Vol. 1, No.1, PP.18-24, 2016
Received on: 28.11.2016,
Revised on: 20.12.2016,
www.ijoaem.com
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![International Journal of Advanced Engineering and Management
Vol. 1, No.1, PP.18-24, 2016
Received on: 28.11.2016,
Revised on: 20.12.2016,
www.ijoaem.com
Object-Oriented Analysis and Design
M. Mukherjee
Abstract
This study mainly focuses on how object-oriented analysis makes compatible with newly develop or other existing
business computing application in a better way. This study also focuses on the modeling of the exact procedure or
near to the exact procedure within its application domain which may model by using different objects class. Objects
are basically structured into different classes of objects which are generally related to behaviors and characteristics.
These methodologies may use different generalization, classification, and different aggregation as a structure object
assemblies for the target actions like services or activities which are related to the objects. There are numerous
misconceptions related to object oriented analysis which are required to address when we consider the use of any
object-oriented method. In this paper try to represent different advantages and various application of the UML in the
field of automatic system analysis and modeling. The platform presented here is a comprehensive range of the
different UML templates with all other required information.
1. Introduction
Object-oriented analysis and design (OOAD) is a globally accepted technical process for manipulative an
application specific, business or system model, and simple graphical diagram for analyzing and product quality
improvement by applying the object-oriented prototype method [1]. Object Oriented Analysis (OOA) is basically
collected works of concurring or cascading system modeling, incorporate various requirements and pre and post
analysis methodology for software systems. These methodologies are primarily influenced by different object-
oriented programming, data modeling and systematic interconnections [2]. Fundamental idea behind OOA is a
streamline software design and development by considering all model as a discreet objects, classes, methods and by
linking these one can designs and implement all kind of business requirements [3]. It mainly focused on the system
development and analysis. This study also focus on how it make compatible with newly develop or other existing
business computing application in better way. In the late 80‘s and 90‘s there were many different object-oriented
methods and modeling techniques used what limited sharing of models across projects (reduced reusability) and
hampered communication between team members and users. The main objective of any model is to build a distinct,
globally accepted standard procedure for object-oriented systems software [4]. Unified Modeling Language (UML)
is one of the standard widely accepted languages, generally is used for modeling any system considering as objects
for better analysis [5]. Such techniques mainly focus on the modeling of the exact procedure or near to the exact
procedure within its application domain which may model by using different objects class. These methodologies
may used different generalization, classification and different aggregation as a structure object assemblies for the
target actions like services or activities which are related with the objects. It can be implemented by MATLAB also
[6]. The major difficulty of preventing object oriented code and reuse code by different attackers is a major
challenges [7]. State changes may be affected the actions which are performed by that objects. There are numerous
misconceptions related to object oriented analysis which are required to address when we consider the use of any
object-oriented method.
2. Some familiar terms related to OOA
a) Object
It may sensed by one or more by our sensing organs like vision, touched, etc. or by which users able to store data
and correlate its behavior.
b) Attributes
This is basically all the information and different types of data which are used to describe the object characteristics
of interest.
c) Behaviour
It is basically refers to as a methodology, procedure, operation or service that the object able to correspond to any
functions which may be operate on the object‘s attributes or data.
M. Mukherjee, "Object-Oriented Analysis and Design," International Journal of Advanced
Engineering and Management, Vol. 1, No. 1, pp. 18-24 , 2016. 19](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)