Rana Majumdar

Evolutionary Algorithm Based Faults Optimization of Multi-modular Software

Computer systems characteristically comprise of hardware and either system or application software. In software developing environment, to accomplish precision is a great thought-provoking task. As there exists every probability that a mistake can be introduced and can persist in software during its established phase. Occurrence of fault cannot be predicted it may be due to human’s mistake which gets noticed during execution of a software activity and at times these faults can lead to failures with disastrous results. Hence, software organizations put emphasis on evading introduction of faults during software development before software gets released. A single software is a combination of several segments each segment has its specific functionality. When all these segments come together, the reliability of the software becomes of utmost importance as it quantifies software failures during the development process and also in operational phase. In order to increase the reliability, an all-inclusive test plan should be included which ensures that all requirements are covered and tested accurately. The main purpose is to maximize the number of faults removed within time constraint during the development phase of software. Each segment may consist of finite number of subparts. These subparts may have errors of different severity depending upon the factors like quality of manpower involved, computer time consumed, etc. The objective of this work is to maximize the number of faults removed in different modules using the Genetic Algorithm and optimized time while removing them; hence find out the faults of different severity and time devoted to removing them in various modules with a predefined reliability.

Modelling the successive software release time of S-shaped model with imperfect debugging

Software Reliability is a significant attribute of the software quality, so attaining reliability is a vital subject for the evaluation of any software product. Software Reliability Growth model defines the phenomenon for fault discovery in testing phase of the development process of a software. Software Reliability models being a contrivance of Software Reliability Engineering (SRE), focuses on engineering methodology and techniques that can be used for the quantitative assessment of the software product, develop test results, schedule timely status, and observe the variations in software reliability performance [9]. Due to extreme competitions, the software companies are approaching with multiple upgrade versions of the software to endure the competition, thus analysing the software in the functional stage. This paper presents a continuous successive releases time modelling based on S-shaped SRGM with imperfect debugging.

Quantifying software reliability using testing effort

Multiple Software Reliability Growth Models (SRGM) has been illustrated to inspire designers and software developers to develop quality software. These models implicitly assume that expenditure is constant throughout testing effort. Recently importance was given to the testing phase by the development team and it requires controlled screening closely to raise its overall operational efficiency. Software Reliability Growth Models exhibits a precise relation between the failure patterns with time. Considering this as a basic building block a SRGM which is a Non-Homogeneous Poisson Process in nature is i in this work. The various aspects of our proposed model are testing effort function and fault detection rate (FDR). Mainly in Software Reliability Growth Model it was assumed that fault removal process are perfect which is not true in reality as new faults may get introduced during removal or some faults may not get removed due to its complexity. Thus in this model the concept of imperfect debugging was considered and assists us to justify the software reliability more convincingly through the help of testing effort function.

Assessment of environmental factors affecting software development process using ISM & MICMAC analysis

Abstract Changing trends and globalization has given rise to various challenges to the software industry. Today the repute of any software engineering is related to its quality and timely delivery of product. The repute also depends on how the industry keeps in pace with the new expertise and changing market situation. The factors like transparency, recognition, work life balance etc. play an imperative part in preserving the reasonable edge. The ISM is a methodology for interactive learning process. In this method the factors that affect the system directly or indirectly are outlined into a complete structure model. The major advantage of the ISM model is its graphical representations of identified factors in a structured manner is indeed the subject in consideration. As a tool, it organizes the elements affecting the system’s credibility. It also highlights the hierarchical complexity among the factors of the system. The ultimate necessity is to analyze the performance of these factors for their operative application in the execution of software development process. The main objective of this paper is to identify the shared communication of these factors and identify the driving and dependent factors. In this work an ISM model has been prepared to recognize significant factors and their administrative consequences from software release time point of view.

Measuring testing efficiency & effectiveness for software upgradation and its impact on CBP

The aim of any company is to deliver reliable product in dynamic and competitive environment. Measuring Testing efficiency and effectiveness is done by proper identification of test attributes and defect origin at various levels of software development phase and removal of these errors becoming an important influencing factor for the invention of quality software. This paper provides an experimental investigation for testing efficiency & effectiveness for software upgradation through numeric example and demonstrates its impact on overall software upgradations as well as on cost, penalty & benefit. The aim of this study is threefold i) To examine the origin of defects and detection during testing phase.(late testing) ii) To investigate proper product release time (early testing)for measuring efficiency and effectiveness and its consequences on overall software upgradation iii) Impact on relative cost, penalty and benefit of a software during its development phase by identifying injected defects and possible magnitudes if they remain untraced and debugged at the final phase before releasing the product.

Role of parameter estimation & prediction during development of Software using SRGM

Predicting Reliability of Software using SRGMs are a big challenge for Software Engineers. Software Reliability is a way to find the probability of software to operate in a given time limit and in a specified environment without causing any failure; hence it is reviewed as Quantifiable Metric. System faults can be the result of software or hardware errors. Software fault is comparatively more difficult to predict than hardware faults. Even the Reliability of a web application is also hard to determine due to its highly distributed nature. Predicting the reliability of application helps the Engineers to compute the softwares release date/time and to manage various resources of software such as people, money, time etc. In this paper SRGM Models are considered namely Goel Okumoto Model (GO Model), Yamada S-shaped Model and Kapur & Garg Model (KG Model) to estimate and predict Software Reliability by detecting the cumulative number of faults in software application within specified time. Additional number of days are also calculated to remove them and release the software on time. By implementing the test cases of actual defects per day, Rate of Change or Test Case Efficiency can be measured.

Measuring testing efficiency: An alternative approach

One of the basics of any IT business organization is its stability in the form of providing consistent product in vibrant and modest environment. Growth of quality software hence has become an expected constraint for software production teams. Enhancing Testing Efficiency being one of the prompting factors for the production of this high quality software. Thus, it is obligatory for software firms to orient themselves towards effective fault controlling mechanism by incorporating testing attribute for attaining improved efficiency, and thus reliability. This paper provides an empirical analysis of several testing attributes through data collection and applications of collected data using Analytical Hierarchy Process (AHP), which is used as a tool to classify the relative importance of these attributes for getting better testing efficiency. The purpose of this analysis is to examine the efficiency of testing during software development process. Then, the study calls for a strong need to improve testing methods using techniques such as AHP for proper testing solutions in lieu of old conventional approach of static testing. This paper demonstrates the perspective of Team Leader, Developer and Tester to assess the functioning of each of the attributes and can serve as an important indicator for measuring testing efficiency. Efficient -testing practices increase the ability of detection and elimination of software flaws right at the inception phase and thereby reduce the cost and time of rework. It further improves productivity, quality and sustainability of software industry.

Handling mutual exclusion in a distributed application through Zookeeper

Zookeeper a powerful, feasible approach to build distributed applications implementing open APIs that enables developers to apply their own powerful co-ordination primitives. The aim of this study is twofold i) To study the anatomy and life cycle of zookeeper and make use of as a role of high-performance coordination service for distributed applications ii) a case study was presented about Zookeeper implementations in the payment process where synchronization and coordination is not meet due to dual server implementation, where orders are placed through an estore application. Finally the potentiality of Zookeeper replications is considered to address reliability and performance issues.

Spatial data mining: Recent trends and techniques

Data mining is process of discovering potential useful and interesting pattern hidden in large data set. Spatial data mining is emerged as new era in research community. Mining in spatial data is different in many aspect compare to mining in classical data. Spatial data mining application includes but not limited to social networking, disaster management and weather prediction. In this paper, a survey of currently available spatial data mining trend and techniques are presented.

Barriers to Agile Adoption: A Developer Perspective

Agile methods are one of the most widely adopted methodologies for developing software. Agile methods refer to a family of lightweight methods that tend to favor working code over documentation, individuals over tools, and collaboration over negotiation. Agile methodology proves beneficial over conventional software engineering methods in terms of time and cost. However, apprehensions of developer community toward adopting agile are an area of concern that results in barriers toward complete agile adoption. In this work, we report the barriers identified through literature survey and results of investigating the relationship that exists between observed barriers. This paper focuses on structural equation modeling that utilizes different classes of modular approaches and establishes connections among identified variables, having the fundamental objective of providing a confirmatory test of a hypothetical model. Our work demonstrates a path model through the analysis of the identified barriers faced by developers during agile adoption.