BITS Faculty Publications
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Item Development of software reliability growth model incorporating enhancement of features and related release policy(Springer, 2010-07) Chanda, UdayanThe software industry can be considered as the typical high technology industry where rate of innovation and knowledge creation plays a pivotal role for continued firm growth. In the last few decades it has been observed that the world of software development management has evolved rapidly due to the intensified market competition. In particular the use of feature-addition model of software products in the industry is fast becoming the commonplace. The up-gradation model can be characterized by increasing the number of features in the software that will give the firm competitive edge in the market. The up-gradation of the system is done by extending it through add-ons, interfacing with other applications, etc. Continuous up-gradation of software’s also brings complexity in the systems once it failed to work properly. In recent years, there has been a growing interest to predict the link between the rates of failure and the reliability of software. Many software reliability growth models (SRGM) have been proposed over past three decades that estimate the reliability of a software system as it undergoes changes through the removal of failure causing faults. But unfortunately most of the models did not consider anything about the increase in failure rate once an up-gradation is made on the software. The objective of this paper is to propose the software reliability growth model that incorporates the effect of enhancement of features on software during testing and debugging process. In addition, we have also discussed the related optimal release time policy that minimizes the total cost.Item A Genetic Algorithm Approach for Optimal Allocation of Software Testing Effort(IJCA, 2023-05) Chanda, UdayanAllocation of limited testing efforts to a software development project is a complex task for software managers. The challenges become difficult when the nature of the development process is considered in the dynamic environment. Numerous software reliability growth models have been proposed in last one decade to minimize the whole testing effort expenditures, but generally under static assumption. The main purpose of this article is to distribute total testing resource optimally under dynamic condition. An elaborate optimization policy is proposed using genetic algorithm and numerical example is also demonstrated. Genetic Algorithms (GAs) works with a set of individuals, representing probable solutions of the task. The selection theory is applied by using a criterion, giving an evaluation for the individual with respect to the desired solution. This article also studies the optimal resource allocation problems for different conditions by investigative the activities of the model parameters.Item Optimal allocation of testing effort during testing and debugging phases: a control theoretic approach(Taylor & Francis, 2012-04) Chanda, UdayanAllocation of efforts to a software development project during the testing phase is a multifaceted task for software managers. The challenges become stiffer when the nature of the development process is considered in the dynamic environment. Many software reliability growth models have been proposed in last decade to minimise the total testing-effort expenditures, but mostly under static assumption. The main purpose of this article is to investigate an optimal resource allocation plan to minimise the cost of software during the testing and operational phase under dynamic condition. An elaborate optimisation policy based on the optimal control theory is proposed and numerical examples are illustrated. This article also studies the optimal resource allocation problems for various conditions by examining the behaviour of the model parameters and also suggests policy for the optimal release time of the software. The experimental results greatly help us to identify the contribution of each selected parameter and its weight.Item Dynamic Effort Allocation Problem Using Genetic Algorithm Approach(MECS Press, 2014-06) Chanda, UdayanEffort distribution plays a major role in software engineering field. Because the limited price projects are becoming common today, the process of effort estimation becomes crucial, to control the budget agreed upon. In last 10 years, numerous software reliability growth models (SRGM) have been developed but majority of model are under static assumption. The basic goal of this article is to explore an optimal resource allocation plan to minimize the software cost throughout the testing phase and operational phase under dynamic condition using genetic algorithm technique. This article also studies the resource allocation problems optimally for various conditions by investigating the activities of the model parameters and also suggests policies for the optimal release time of the software in market place.Item Resource Allocation Policies for Fault Detection and Removal Process(IMECS, 2014-11) Chanda, UdayanIn software testing, fault detection and removal process is one of the key elements for quality assurance of the software. In the last three decades, several software reliability growth models were developed for detection and correction of faults. These models were developed under strictly static assumptions. The main goal of this article is to investigate an optimal resource allocation plan for fault detection and removal process of software to minimize cost during testing and operational phase under dynamic condition. For this we develop a mathematical model for fault detection and removal process and Pontryagain‘s Maximum principle is applied for solving the model. Genetic algorithm is used to find the optimal allocation of fault detection and removal process. Numerical example is also solved for resource allocation for fault detection and remoal process