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Advanced Computing & Communication Technologies (ACCT), 2012 Second International Conference on

Date 7-8 Jan. 2012

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Displaying Results 1 - 25 of 124
  • [Front cover]

    Publication Year: 2012 , Page(s): C1
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  • [Title page i]

    Publication Year: 2012 , Page(s): i
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  • [Title page iii]

    Publication Year: 2012 , Page(s): iii
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  • [Copyright notice]

    Publication Year: 2012 , Page(s): iv
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  • Table of contents

    Publication Year: 2012 , Page(s): v - xii
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  • Message from General Chair

    Publication Year: 2012 , Page(s): xiii
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  • Message from Program Chair

    Publication Year: 2012 , Page(s): xiv
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  • Organizing Committee

    Publication Year: 2012 , Page(s): xv
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  • Programme Committee

    Publication Year: 2012 , Page(s): xvi
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  • Reviewers

    Publication Year: 2012 , Page(s): xvii
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  • Use of Clonal Selection Algorithm as Software Test Data Generation Technique

    Publication Year: 2012 , Page(s): 1 - 5
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (310 KB) |  | HTML iconHTML  

    Clonal selection algorithm is an algorithm that belongs to the class of immune algorithm inspired form clonal selection principle of biological immune system. Initially clonal selection algorithm was designed for machine learning approach and was used in pattern recognition process of artificial intelligence. The other implementation of clonal selection algorithm is in the field of function optimization, which had gained a tremendous attention of the researchers. We too had used the clonal selection algorithm for the software test data generation technique for branch coverage with some modification according to the requirement. View full abstract»

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  • Analysis of Clustering Techniques for Software Quality Prediction

    Publication Year: 2012 , Page(s): 6 - 9
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (207 KB) |  | HTML iconHTML  

    Clustering is the unsupervised classification of patterns into groups. A clustering algorithm partitions a data set into several groups such that similarity within a group is larger than among groups The clustering problem has been addressed in many contexts and by researchers in many disciplines, this reflects its broad appeal and usefulness as one of the steps in exploratory data analysis. There is need to develop some methods to build the software fault prediction model based on unsupervised learning which can help to predict the fault -- proneness of a program modules when fault labels for modules are not present. One of the such method is use of clustering techniques. This paper presents a case study of different clustering techniques and analyzes their performance. View full abstract»

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  • Analysis and Modelling of Websites Quality Using Fuzzy Technique

    Publication Year: 2012 , Page(s): 10 - 15
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (365 KB) |  | HTML iconHTML  

    The quality of websites is evaluated on the basis of eleven important metrics load time, response time, mark-up validation, broken link, accessibility error, size, page rank, frequency of update, traffic and design optimisation. The metrics are taken as linguistic variables. Fuzzy logic is used to evaluate grade of a website. View full abstract»

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  • To Achieve Trust in the Cloud

    Publication Year: 2012 , Page(s): 16 - 19
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (401 KB) |  | HTML iconHTML  

    By providing businesses, universities, government agencies, and other entities with access to shared and often physically dispersed computing resources, cloud computing can simultaneously offer increased flexibility, reduced cost, and access to a wider array of services. However, the lack of confidence in entrusting sensitive information to cloud computing service providers is one of the primary obstacles to widespread adoption of cloud computing, as reported by a number of surveys. In this paper, we are trying to achieve trust in the cloud through preventive, detective and corrective controls. And we have also described steps to achieve trust in the cloud. View full abstract»

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  • A Study of Pair Programming in the Context of Facilitating the Team Building

    Publication Year: 2012 , Page(s): 20 - 23
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (229 KB) |  | HTML iconHTML  

    Anecdotal and qualitative evidence from industry indicates that two programmers working side-by-side at one computer, collaborating on the same design, algorithm, code, or test, perform substantially better than the two working alone and they have produced higher-quality software products in shorter amounts of time. But their evidence was anecdotal and subjective: "It works" or "It feels right." In education, pair programming also improves student morale, helps students to be more successful, and improves student retention in an information technology major. Our study provides an overview and history of pair programming followed by a summary of the use of pair programming in industry and academic. This paper also provides insight into the principles that make pair programming successful for the team building for newly hired programmers in an industry. View full abstract»

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  • Adoption of Knowledge Management Practices in Software Engineering Organizations: A Survey of Software Engineers' Perceptions

    Publication Year: 2012 , Page(s): 24 - 29
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (325 KB) |  | HTML iconHTML  

    Most businesses rely on the fact that their employees possess relevant knowledge and that they can apply it to the task at hand. But a serious problem exists, this knowledge is not owned by the organisation as such. Rather the knowledge is owned and controlled by its employees. The success or failure of the KM systems and the various KM practices claimed to be adopted by software engineering organisations can be best judged from software engineers' point of view as they are the ones who are the first-hand users of the KM systems and technologies. View full abstract»

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  • Experience Base Approach to Software Process Improvement: Comparative Analysis and Design of Improved Model

    Publication Year: 2012 , Page(s): 30 - 35
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (319 KB) |  | HTML iconHTML  

    Most of the modelling approaches presently used in software engineering concentrate on some specific aspect of software development and ignore other relevant aspects. For instance, process modelling approaches do not address product quality and methods for modelling product quality do not consider process modelling. Moreover, the modelling of software engineering reusable objects or technologies has yet not been addressed in the field. Dearth of integrated modelling approaches for various aspects of software projects leads to the present state of affairs where software engineers can not view the interdependencies among software development process, product attributes, software experience and the software development context. The EBM model proposed in this paper integrates these several concepts that have so far been considered independently and hence contributes to a more comprehensive understanding of software engineering as an applied discipline. View full abstract»

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  • A Clustered Approach to Analyze the Software Quality Using Software Defects

    Publication Year: 2012 , Page(s): 36 - 40
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (236 KB) |  | HTML iconHTML  

    As the software development begins there also exists the probability of occurrence of some defect in the software system. Software defects plays important role to take the decision about when the testing will be stopped. Software defects are one of the major factors that can decide the time of software delivery. Not only has the number of defects also the type of defect as well the criticality of a software defect affected the software quality. Software cannot be presented with software defects. All the Software Quality estimation approaches like CMM etc. follow the software defects as a parameter to estimate the software quality. The proposed work is also in the same direction. We are trying to categorize the software defects using some clustering approach and then the software defects will be measured in each clustered separately. The proposed system will analyze the software defect respective the software criticality and its integration with software module. View full abstract»

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  • Optimization of Automation in Fuzzy Decision Rules

    Publication Year: 2012 , Page(s): 41 - 45
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (228 KB) |  | HTML iconHTML  

    The advances in data collection have generated an urgent need for techniques that can intelligently and automatically analyze and mine knowledge from huge amounts of data. The Knowledge Discovery in Databases (KDD) is the process of extracting the knowledge from huge data collection. Data mining is a step of KDD in which patterns or models are extracted from data by using some automated techniques. Discovering knowledge in the form of classification rules is one of the most important tasks of data mining. Discovery of comprehensible, concise and interesting rules helps us to make right decisions. Therefore, several Machine Learning techniques such as Neural Network, Decision Tree Induction, K nearest neighbour and Bayesian approach have been applied for automated discovery of classification rules. Recently there have been several applications of genetic algorithms for successful discovery of concise and comprehensible rules with high predictive accuracy. View full abstract»

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  • Analyzing Object Models with Theory of Innovative Solution

    Publication Year: 2012 , Page(s): 46 - 50
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (450 KB) |  | HTML iconHTML  

    Object-Oriented Modeling is a modeling paradigm mainly used in computer programming that assists the programmer to address the complexity of a problem domain by considering the problem and reduce the effect on model caused by such problem and make designs more robust, more maintainable, and more reusable. It is a design strategy where system designers think in terms of 'things' instead of operations or functions. Object-Oriented software projects are becoming more popular than structured or functional technology based projects. While Object-Oriented modeling are already arriving in the marketplace but their formal foundations are still under development. Object Technology offers support to deliver products to market more quickly and to provide high quality with lower maintenance costs. Quality Assurance is an important field of software engineering and there is need for good Object-Oriented metrics and models for both process and product. The quality of object-oriented design has a decisive impact on the quality of a software product, but due to the diversity and complexity of design properties like coupling, encapsulation etc their assessment and correlation with external quality attributes like maintenance, portability etc is hard. To address these issues, we will use the innovative solution (TRIZ) to enhance quality with available Object-oriented metrics and affecting factors. TRIZ is a problem-solving, analysis and forecasting tool that is abbreviation of Russian word Teoriya Resheniya Izobretatelskikh Zadatch which typically rendered as the Theory of Inventive Problem Solving. The objective of TRIZ is development of an algorithmic approach to the invention of new systems, and the refinement of existing ones. In this paper we will apply TRIZ to Object-oriented Models to enhance the quality of Object-oriented design. This paper describes a method based on TRIZ principles and tools that can be easily applied to maintain the quality of Object-Oriented based mode- s. View full abstract»

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  • Software Tools Required to Develop GIS Applications: An Overview

    Publication Year: 2012 , Page(s): 51 - 56
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (229 KB) |  | HTML iconHTML  

    Due to the improved performance of computer systems, Geographic information systems (GIS) are becoming more usual. In this paper, we are elaborating the software tools that are used in the development of a complete and complex real-life GIS application in the analysis, design and implementation. We describe characteristics of these software tools helpful to understand better and to develop different type of GIS based application software's. View full abstract»

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  • Flexible Discrete Software Reliability Growth Model for Distributed Environment Incorporating Two Types of Imperfect Debugging

    Publication Year: 2012 , Page(s): 57 - 63
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (286 KB) |  | HTML iconHTML  

    In literature we have several software reliability growth models developed to monitor the reliability growth during the testing phase of the software development. These models typically use the calendar / execution time and hence are known as continuous time SRGM. However, very little seems to have been done in the literature to develop discrete SRGM. Discrete SRGM uses test cases in computer test runs as a unit of testing. Debugging process is usually imperfect because during testing all software faults are not completely removed as they are difficult to locate or new faults might be introduced. In real software development environment, the number of failures observed need not be same as the number of errors removed. If the number of failures observed is more than the number of faults removed then we have the case of imperfect debugging. Due to the complexity of the software system and the incomplete understanding of the software requirements, specifications and structure, the testing team may not be able to remove the fault perfectly on detection of the failure and the original fault may remain or get replaced by another fault. In this paper, we discuss a discrete software reliability growth model for distributed system considering imperfect debugging that faults are not always corrected/removed when they are detected and fault generation. The proposed model assumes that the software system consists of a finite number of reused and newly developed sub-systems. The reused sub-systems do not involve the effect of severity of the faults on the software reliability growth phenomenon because they stabilize over a period of time i.e. the growth is uniform whereas, the newly developed subsystem does involve. For newly developed component, it is assumed that removal process follows logistic growth curve due to the fact that learning of removal team grows as testing progresses. The fault removal phenomena for reused and newly developed sub-systems have been modeled separa- ely and are summed to obtain the total fault removal phenomenon of the software system. The model has been validated on two software data sets and it is shown that the proposed model fairs comparatively better than the existing one. View full abstract»

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  • Profound Survey on Cross Language Information Retrieval Methods (CLIR)

    Publication Year: 2012 , Page(s): 64 - 68
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (239 KB) |  | HTML iconHTML  

    Cross Language Information Retrieval is a sub field of Information Retrieval that deals with retrieving relevant information stored in a language different from the language of user's given query. It plays a vital role in future because large volume of information is stored in the web is in English. So there is a necessity of proper mechanisms that can retrieve some required relevant information in a collection of information or in a database. Generally the collection of stored information may not be necessarily in one language. The simplest way to search for the information is to scan every item in the database and when the need to translate the languages being used arises, and then there will be a need of developing Cross Language Information Retrieval systems will take place. This paper reviews some of the recent research methods focus on topics in cross language information retrieval and there great role in On-going latest innovative research directions in wide area of information retrieval systems will take place. View full abstract»

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  • Genetic Algorithm Approach to Automated Discovery of Comprehensible Production Rules

    Publication Year: 2012 , Page(s): 69 - 71
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (216 KB) |  | HTML iconHTML  

    In the recent past, there has been an increasing interest in applying evolutionary methods to Knowledge Discovery in Databases (KDD) and a number of successful applications of Genetic Algorithms (GA) and Genetic Programming (GP) to KDD have been demonstrated. The most predominant representation of the discovered knowledge is the standard Production Rules (PRs) in the form If P Then D. This paper presents a classification algorithm based on GA approach that discovers comprehensible rules in the form of PRs. The proposed approach has flexible chromosome encoding, where each chromosome corresponds to a PR. For the proposed scheme a suitable and effective fitness function and appropriate genetic operators are proposed for the suggested representation. Experimental results are presented to demonstrate the performance of the proposed algorithm. View full abstract»

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  • Revisiting Interestingness Measures for Knowledge Discovery in Databases

    Publication Year: 2012 , Page(s): 72 - 78
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (269 KB) |  | HTML iconHTML  

    The voluminous amount of data stored in databases contains hidden knowledge which could be valuable to improve decision making process of any organization. As it is not humanely possible to analyze large databases, it has become essential to apply advanced data mining algorithms for extracting patterns (models) from data to support decision making. A number of data mining algorithms produce information of a statistical nature that allows the user to assess how accurate and reliable the discovered knowledge is? However, in many cases this is not enough for the users. Even if the discovered knowledge is highly accurate from a statistical point of view, it might not be interesting to the user. Therefore the process of knowledge discovery in databases (KDD) aims at discovering knowledge that is interesting and useful to the user. Most of the data mining algorithms so far have paid lot of attention to discovery of accurate and comprehensible knowledge. Though, the question of interestingness has been addressed time to time, it is being increasingly realized by data mining community that this subject needs a renewed focus. This paper is an attempt to review the measures of interestingness used in the data mining literature. The main contribution of the paper is to improve the understanding of interestingness measures for discovery of knowledge and identify the unresolved problems to set the directions for the future research in this area. View full abstract»

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