Samaresh Mishra

A Review of Software Cost Estimation in Agile Software Development Using Soft Computing Techniques

For a successful software project, accurate prediction of its overall effort and cost estimation is a very much essential task. Software projects have evolved through a number of development models over the last few decades. Hence, to cover an accurate measurement of the effort and cost for different software projects based on different development models having new and innovative phases of software development, is a crucial task to be done. An accurate prediction always leads to a successful software project within the budget with no delay, but any percentage of misconduct in the overall effort and cost estimate may lead to a project failure in terms of delivery time, budget or features. Software industries have adopted various development models based on the project requirements and organizations capabilities. Due to adaptability to changes in a software project, agile software development model has become a much successful and popular framework for development over the last decade. The customer is involved as an active participant in the development using an agile framework. Hence, changes can occur at any phase of development and they can be dynamic in nature. That is why an accurate prediction of effort and cost of such projects is a crucial task to be done as the complexity of overall development structure is increased with the time. Soft computing techniques have proven that they are one of the best problem solving techniques in such scenarios. Such techniques are more flexible and presence of bio-intelligence increases their accuracy. Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Neural Network (ANN), Fuzzy Inference Systems (FIS), etc. are applied successfully for estimation of cost and effort of agile based software projects. This paper deals with such soft computing techniques and provides a detailed and analytical overview of such methods. It also provides the future scope and possibilities to explore such techniques on the basis of survey provided by this paper.

Reliability enhancement of software programs by minimizing the overflow errors

Reliability is always important in all systems but sometimes it is more important than other quality attributes, especially in mission critical systems where the severity of consequence resulting from failure is very high. Hence, it is important to develop comprehensive techniques for developing reliable software. But, it is found that there exist no suitable model to enhance the reliability of software for diverse operating environment and also it is difficult to develop a fully reliable software for all applications. Considering these aspects this paper proposes an effective approach to enhance the reliability of software by minimizing the overflow errors caused during the execution of any program.

Estimation of effort based on back-end size of business software using er model

We propose a technique for estimating the back-end size based on its complexity of business software using ER diagram artifacts. Our size estimation is based on the structural complexity of ER diagram which includes the concepts of generalization/specialization, and aggregation as well as the semantic integrity constraints identified during conceptual design phase. We proposed size metrics for measuring entity size, relationship size and semantic integrity constraints size and finally the effort of development has been estimated using COCOMO model.

Reliability enhancement of computer software

Reliability is always important in all systems but sometimes it is more important than other quality attributes, especially in mission critical systems where the severity of consequence resulting from failure is very high. Hence, it is important to develop comprehensive techniques for developing reliable software. But, it is found that there exist no suitable model to enhance the reliability of software for diverse operating environment and also it is difficult to develop a fully reliable software for all applications. Considering these aspects this paper proposes an effective approach to enhance the reliability of software by minimizing the operational errors (like overflow etc.) caused during the execution of any program.

Chaos-based Modified Morphological Genetic Algorithm for Software Development Cost Estimation

We have proposed a morphological approach based on an evolutionary learning for software development cost estimation (SDCE). The dilation–erosion perceptron (DEP) method which is a hybrid artificial neuron is built on mathematical morphology (MM) framework. This method has its roots in the complete lattice theory. The proposed work also presents an evolutionary learning procedure, i.e., a chaotic modified genetic algorithm (CMGA) to construct the DEP (CMGA) model overcoming the drawbacks arising in the morphological operator’s gradient estimation in the classical learning procedure of DEP. The experimental analysis was conducted on estimation of five different SDCE problems and then analyzed using three performance measurement metrics.

Critique on Signature Analysis Using Cellular Automata and Linear Feedback Shift Register

In surge to cater the needs of modern technology and high performance computation requirement the complexity of the VLSI design increasing with complex logic design, more memory space and large test vector for testing the digital circuit. Signature analysis compresses the data. It is also known to be a compacting technique which follows the concept of cyclic redundancy checking (CRC) which in turn detects error during transmission. It is used in hardware using shift register, cellular automata, etc. as a part of VLSI design process. This paper deals with the popular mechanism of signature analysis in the context of digital system testing using LFSR and CA-based signature analysis along with its critique.

Estimating Database Size and Its Development Effort at Conceptual Design Stage

In recent years, the database size of information system software is increasing rapidly along with the development of the technology of software and its estimation techniques. Generally, any software product may consist of basic three components: data, functional, and document. The estimation of development effort for software depends on the effort required for the development of these components. The database development effort primarily depends on the database volume. In this paper, a set of metrics have been proposed and validated for estimating database size using ER and Enhanced ER diagram artifacts. The effort of database development based on the proposed size metrics have been validated using COCOMO model.