International Journal of Computer and Applications

A privacy preserving association rule mining algorithm was introducedThis algorithm preserved privacy of individual values by computing scalar productMeanwhile the algorithm of computing scalar product was given and the security was analyzed

Privacy preserving association rule mining in vertically partitioned data

This paper summarizes the current state of the art and recent trends in software engineering economics. It provides an overview of economic analysis techniques and their applicability to software engineering and management. It surveys the field of software cost estimation, including the major estimation techniques available, the state of the art in algorithmic cost models, and the outstanding research issues in software cost estimation.

Software engineering economics

This book serves as an introduction to the flourishing field of super-resolution imaging. It is a compiled volume, with different authors for each of its 14 chapters. While not having a strong outline or textbook format, the chapters group into several sections.

Super-Resolution Imaging

Current rates of species loss triggered numerous attempts to protect and conserve biodiversity. Species conservation, however, requires species identification skills, a competence obtained through intensive training and experience. Field researchers, land managers, educators, civil servants, and the interested public would greatly benefit from accessible, up-to-date tools automating the process of species identification. Currently, relevant technologies, such as digital cameras, mobile devices, and remote access to databases, are ubiquitously available, accompanied by significant advances in image processing and pattern recognition. The idea of automated species identification is approaching reality. We review the technical status quo on computer vision approaches for plant species identification, highlight the main research challenges to overcome in providing applicable tools, and conclude with a discussion of open and future research thrusts.

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Automated plant species identification-Trends and future directions.

Software Testing is an important process of software development that is performed to support and enhance reliability and quality of the software. It consist of estimating testing effort, selecting suitable test team, designing test cases, executing the software with those test cases and examining the results produced by those executions. Studies indicate that more than fifty percent of the cost of software development is devoted to testing, with the percentage for testing critical software being even higher. Unless we can predict the testing effort and find efficient ways to perform effective testing, the percentage of development costs devoted to testing will increase significantly coupled with mismatch in project costing and development schedule. In order to estimate the testing effort, this paper makes an attempt to establish Cognitive Information Complexity Measure (CICM) as an appropriate estimation tool.

Software test effort estimation

Software maintenance forms an essential component of software development. Its planning includes estimation of maintenance effort, duration, personnel and costs. Adequate information regarding size, complexity and maintainability is however often unavailable. In the present work, a Neural Network (NN) based effort estimator is developed using Matlab. A feed forward back- propagation NN employing Bayesian regularization training is selected and trained for one dataset. Various categories of software maintenance cost drivers and their effect on maintenance effort have been analyzed using different combinations of number of hidden layers and hidden neurons etc. The NN is able to successfully model the maintenance effort as the obtained results are well within the previously published error limits

Estimating software maintenance effort: a neural network approach

Cognitive information complexity measure is based on cognitive informatics, which helps in comprehending the software characteristics. For any complexity measure to be robust, Weyuker properties must be satisfied to qualify as good and comprehensive one. In this paper, an attempt has also been made to evaluate cognitive information complexity measure in terms of nine Weyuker properties, through examples. It has been found that all the nine properties have been satisfied by cognitive information complexity measure and hence establishes cognitive information complexity measure based on information contained in the software as a robust and well-structured one.

Robustness analysis of cognitive information complexity measure using Weyuker properties

Most discipline of science have their own method of investigation built on foundation that is empirical and verifiable. Cognitive Informatics is no different. Cognitive Informatics is a field that studies internal information processing mechanism of the human brain and its application in software coding and computing. This paper attempts to empirically demonstrate the amount of information contained in software and develops a concept of cognitive information complexity measure based on the information contained in the software. It is found that software with higher cognitive information complexity measure has more information units contained in it. Therefore cognitive information complexity measure can be used to understand the cognitive information complexity and the information coding efficiency of the software.

A modified cognitive information complexity measure of software

Due to the constant change in technology, lack of standardization, difficulties of changes and absence of distributed architecture, the business value of legacy systems have become weaker. We cannot undermine the importance of legacy systems because some of their functions are too valuable to be discarded and too expensive to reproduce. The software industry and researchers have recently paid more attention towards the component based software development to enhance the productivity and accelerate time to market. Instead of re-implementing the business critical applications with-in time and resource constraints, the best option is Software Reengineering (SRE) with effective design and architecture which can make the system better for reusability and maintainability. The main motive behind the reengineering is integrating the legacy system with emerging technologies. To achieve these goals, we have proposed a systematic and concrete model named as Component Oriented Reverse Engineering (CORE). It aims to identify and develop reusable software components. By using the reverse engineering techniques; we can extract architectural information and services from legacy system and later on convert these services into components

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Arun Kumar Misra

Papers

Software test effort estimation

Estimating software maintenance effort: a neural network approach

Robustness analysis of cognitive information complexity measure using Weyuker properties

A modified cognitive information complexity measure of software

Creating Reusable Software Component from Object-Oriented Legacy System through Reverse Engineering