Bio: Manjula R is an academic researcher from VIT University. The author has contributed to research in topics: Software development & Social software engineering. The author has an hindex of 2, co-authored 3 publications receiving 13 citations.
01 Nov 2016
TL;DR: A framework for selection of prioritization technique using fuzzy based rule engine is discussed and the developed framework could be beneficial to requirements engineer during requirement analysis phase.
Abstract: Requirement prioritization for software products is one of the most important activities in software development. Prioritization is a critical step towards making great choices with respect to product planning for single and multiple releases. There are numerous requirement prioritization techniques and selecting the most appropriate one is a challenging task. In this paper a framework for selection of prioritization technique using fuzzy based rule engine is discussed. Here, the user inputs the characteristic value of the prioritized factor as input and on the basis of the fuzzy rules formed; most appropriate prioritization technique is predicted. Various prioritization techniques like AGORA, AHP, Win-Win etc. are considered against factors like consistency, priority etc. and the best approach is anticipated. Later the results are validated using Decision Tree approach. The developed framework could be beneficial to requirements engineer during requirement analysis phase.
••01 Nov 2016
TL;DR: A detailed literature survey on software reuse processes, current research and challenges which encounters while software reusing is presented.
Abstract: Software reuse is the use of already existing concepts, objects or software components to build new software. The goal of software reuse research is to explore systematic procedures for developing new systems from existing ones. The systematic software reuse is the most effective way to improve software development. Domain engineering plays crucial role in Software Reuse research, which makes the use of approaches based on object oriented design, software architecture and architecture definition languages. These approaches can be significantly used at initial stages of Software Development Life Cycle (SDLC). It helps us to reduce the rework by enhancing the productivity and quality of reuse. Thus the goal is to identify barriers of software reusability that must be overcome for successful reuse. This paper presents a detailed literature survey on software reuse processes, current research and challenges which encounters while software reusing.
••01 Nov 2016
TL;DR: This paper gives the crucial and clear idea about the SOSE, which gives the thorough analysis platform for the Quality of Service (QoS), which contributes to cost-efficient software development.
Abstract: Nowadays complex and large-scale systems are developed for solving the problems by integrating the services. SOSE (Service Oriented Software Engineering) is the modern approach of software engineering to deal with these services. For the past 2–3 years' services have increased exponentially, among those which is the best one for the good software development is a challenge. The detailed study of SOSE is observed with respect to the Traditional Software Engineering. SOSE gives the thorough analysis platform for the Quality of Service (QoS), which contributes to cost-efficient software development. In this Quality of service is improved by reusability and scalability of services, which leads to solving many issues, which occur during software engineering maintenance and evolution. The SOSE differs Traditional SE with the consideration of its structure, method of implementation etc. like attributes. This paper gives the crucial and clear idea about the SOSE.
11 Feb 2022
TL;DR: In this article , an efficient method for irrigation is proposed in this system for Evapotranspiration (ET) calculation using Mamdani fuzzy inference system using data mining techniques can be used predict the crop yield and its quantity in advance before harvesting.
Abstract: Agriculture is a sector that can get easily affected by various factors like climatic conditional changes, availability of water, attributes of soil, etc. The data mining techniques can be used predict the crop yield and its quantity in advance before harvesting. The expert involvement to predict crop yield may fail due to lack of knowledge in natural events, fatigue and etc. An efficient method for irrigation is proposed in this system for Evapotranspiration (ET) calculation using Mamdani fuzzy inference system. This will help the former to plan irrigation based on the crops in various seasons, and its requirement according to the change of climatological parameters. This system avoids the excessive or insufficient irrigation that significantly affects quality of the crop and yields. The outcomes prove that the fuzzy model is a fast and exact tool to calculate the evapotranspiration required in net irrigation. Using this system farmer can indenture before their harvest and they can expect the quantity of yield in advance to ensure a more competitive price than wait until after the harvest. The obtained results shows that the system have a coefficient of correlation is more than 0.9.
TL;DR: In this article , the authors used Tesseract OCR and the YOLO V4 approach to solve the license plate recognition system issue and deliver their suggested system with high accuracy, which offers a powerful method for character localization, segmentation, and identiﬁcation inside the located plate.
Abstract: In this research paper, we’ll talk about ALPR technology, which has gained popularity recently because of all the many ways it may be used. The fundamental beneﬁt of this technology is that it may be utilized for a variety of purposes, including travel time analysis, intelligent parking, automated toll collec-tion, intelligent transportation systems in smart cities, and trafﬁc management. Automated License Plate Recognition (ALPR) reads the vehicle’s registration number by ﬁrst using YOLOv4 for object recognition following which we use OpenCV to enlarge the license plate image and identify the character boxes after which we use Tesseract optical character recognition to identify the various characters and form the license plate number. This system uses several image processing methods to recognize automobiles swiftly and automatically in video or picture material. As technology develops quickly with the introduction of machine learning and deep learning, the cost of computing falls, and the accuracy of used image processing methods rises, the usage of ALPR systems is becoming more widespread. In today’s congested trafﬁc system, a license plate detection system is crucial. It aids in monitoring compliance with trafﬁc laws and other law enforcement operations. There are many instances of reckless driving in India when vehicles break several trafﬁc laws. As a result, a license plate detection system has been suggested and put into use throughout the years to assist with quick and simple trafﬁc law enforcement by automobiles. This work offers a powerful method for character localization, segmentation, and identiﬁcation inside the located plate. We are going to utilize tesseract OCR and the YoLo V4 approach to solve the License plate recognition system issue and deliver our suggested system with high accuracy.
••01 Dec 2018
TL;DR: The impact of ML can be observed in requirement elicitation, analysis and specification, validation and management, and lessons learned are outlined and possible future directions for the domain are envisioned.
Abstract: Machine learning (ML) has demonstrated practical impact in a variety of application domains. Software engineering is a fertile domain where ML is helping in automating different tasks. In this paper, our focus is the intersection of software requirement engineering (RE) and ML. To obtain an overview of how ML is helping RE and the research trends in this area, we have surveyed a large number of research articles. We found that the impact of ML can be observed in requirement elicitation, analysis and specification, validation and management. Furthermore, in these categories, we discuss the specific problem solved by ML, the features and ML algorithms used as well as datasets, when available. We outline lessons learned and envision possible future directions for the domain.
TL;DR: In this article, a MCDM model for requirements prioritization is introduced and the test was conducted on MATLAB software and result evaluated on fuzzy comparison matrix with three supplier selection criteria based on FAHP and LOGANFIS.
Abstract: Requirements prioritization is a most important activity to rank the requirements as per their priority of order .It is a crucial phase of requirement engineering in software development process. In this research introduced a MCDM model for requirements prioritization. To select a best supplier firm of washing machine three important criteria are used. In this proposed model investigation for requirements prioritization, a case study adopted from Ozcan et al using LOG FAHP (Logarithmic fuzzy analytic hierarchy process) and ANN (Artificial Neural Network) based model to choose the best supplier firm granting the highest client satisfaction among all technical aspects. The test was conducted on MATLAB software and result evaluated on fuzzy comparison matrix with three supplier selection criteria based on FAHP and LOGANFIS that shows the decision making outcome for requirements prioritization is better than existing approaches with higher priority.
••24 Mar 2019
TL;DR: A comparative analysis of ten leading RP techniques have been performed, based on some key factors like RP scales, complexity, scalability, customizability, accuracy, suitable dataset and handling risk factor, to identify most favorable one in a given context.
Abstract: Requirement Prioritization (RP) bears a sheer significance in requirements engineering. It is deployed to rank the requirements for subsequent release in their respective order based on predefined criteria. Software systems primarily get more complex accompanying size of requirements. In most cases, it is not possible to consider all requirements due to limited time and resources. Thus, requirements need to be prioritized correctly according to their importance. Quality of software to be developed greatly depends upon the order of requirements. Many studies reveal, no single RP technique can be labeled as best for all applications. Hence there is a need to analyze the available RP techniques to identify most favorable one in a given context. In this paper, a comparative analysis of ten leading RP techniques have been performed, based on some key factors like RP scales, complexity, scalability, customizability, accuracy, suitable dataset and handling risk factor. Strengths and weaknesses of these techniques have been analyzed and discussed. A case study is also incorporated as an example of selection of most suitable RP technique. This study contributes in selection of most appropriate RP technique in a particular scenario.
TL;DR: The difference in time estimation with prioritization and without prioritization shows the significance of prioritization of functional requirements.
Abstract: Requirements prioritization shows significant role during effective implementation of requirements. Prioritization of requirements is not easy process particularly when requirements are large in size. The current methods of prioritization face limitations as the current prioritization techniques for functional requirements rely on the responses of stakeholders instead of prioritizing requirements on the basis of internal dependencies of one requirement on other requirements. Moreover, there is need to classify requirements on the basis of their importance i.e. how much they are needed for other requirements or dependent on other requirements. Requirements are first represented with spanning trees and then prioritized. Suggested spanning tree based approach is evaluated on requirements of ODOO ERP. Requirements are assigned to four developers. Time estimation with and without prioritization are calculated. The difference in time estimation with prioritization and without prioritization shows the significance of prioritization of functional requirements.
TL;DR: This study was conducted to define the characteristics of software component reusability evaluation approach (CREA) based on experienced software developer’s feedback, and to estimate the measurement level for each of the predefined metric.
Abstract: The study of software component reuse is rising in software development field and one of the methods used to reduce the production cost and time. Among the problems faced by software developers in component reuse, is the difficulty to determine which set of components are suitable to use in new software development. Thus, this study was conducted with the purpose; to define the characteristics of software component reusability evaluation approach (CREA) based on experienced software developer’s feedback, and to estimate the measurement level for each of the predefined metric. Three characteristics and sub characteristics, namely understandability (documentation level and observality), adaptability (customizability), and portability (external dependency) were identified that have been used to develop the metrics for CREA. The result for all metrics will be used as an input to the fuzzy inference system (FIS) for measuring the reusability level of the component.