scholarly journals Routine Vaccine Simulation for Infants in a Mobile Environment

2022 ◽  
Vol 6 ◽  
pp. 763-780
Author(s):  
Annabelle Joy Asiado ◽  
◽  
Sweet Zerlyn Cabuntucan ◽  
Cereneo Jr. Santiago ◽  
◽  
...  
Keyword(s):  
Information Dissemination ◽  
Health Workers ◽  
Vaccine Safety ◽  
Strategy Implementation ◽  
Fourth Generation ◽  
Mobile Environment ◽  
Data Presentation ◽  
Generation Technique ◽  
Development Life Cycle ◽  
Software Development Life Cycle

Purpose–Thisstudy aimed to develop and evaluate the Routine Vaccine Simulation for Infants. The routine vaccine simulation application was developed for the health workers and parents to provide basic information and press the importance of the vaccination to infants.Method–The researchers used the fourth-generation technique (4GT) for the software development life cycle of the application. The technique adapted contains four major parts namely, requirements gathering, design strategy, implementation, and testing.Results–The application was tested and evaluated by health workers, parents, and IT practitioners from the academe and the industry. The evaluation was based on criteria for core app quality. Descriptive and inferential statistics were employed for data presentation and interpretation. As a whole, the evaluation of the android-based routine vaccine simulation application was found excellent in most of its features. The finding asserts the adherence to the standards of android developmentapplicationsand conforms to the expectations of the app’s potentialusers. Conclusion–The development of a routine vaccine app for infants serves as a new platform for immunization awareness and education. Once information given in the app is taken earnestly, infants will be protected against diseases. Thus, controversies surrounding vaccination hesitancies can be decreased.Recommendations–A thorough information dissemination and education campaign regarding vaccine safety can be initiated in the local communities to address the issues on vaccine safety and hesitancy.Research Implications–The healthcare system in the communities through the local government unit (LGU) willbe able to benchmark and implement the information dissemination and education to mothers and health workers using the app.

Computable metrics of personal performance in software development teams

2019 ◽  
Author(s):  
Andriy Lishchytovych ◽  
Volodymyr Pavlenko
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Product Quality ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
Project Manager ◽  
Development Life Cycle ◽  
Software Product ◽  
Software Development Life Cycle

The present article describes setup, configuration and usage of the key performance indicators (KPIs) of members of project teams involved into the software development life cycle. Key performance indicators are described for the full software development life cycle and imply the deep integration with both task tracking systems and project code management systems, as well as a software product quality testing system. To illustrate, we used the extremely popular products - Atlassian Jira (tracking development tasks and bugs tracking system) and git (code management system). The calculation of key performance indicators is given for a team of three developers, two testing engineers responsible for product quality, one designer, one system administrator, one product manager (responsible for setting business requirements) and one project manager. For the key members of the team, it is suggested to use one integral key performance indicator per the role / team member, which reflects the quality of the fulfillment of the corresponding role of the tasks. The model of performance indicators is inverse positive - the initial value of each of the indicators is zero and increases in the case of certain deviations from the standard performance of official duties inherent in a particular role. The calculation of the proposed key performance indicators can be fully automated (in particular, using Atlassian Jira and Atlassian Bitbucket (git) or any other systems, like Redmine, GitLab or TestLink), which eliminates the human factor and, after the automation, does not require any additional effort to calculate. Using such a tool as the key performance indicators allows project managers to completely eliminate bias, reduce the emotional component and provide objective data for the project manager. The described key performance indicators can be used to reduce the time required to resolve conflicts in the team, increase productivity and improve the quality of the software product.

A Systematic Review and Catalog of Security Metric during the Secure Software Development Life Cycle

2020 ◽  
Vol 13 ◽  
Author(s):  
Sampada G.C ◽  
Tende Ivo Sake ◽  
Amrita
Keyword(s):  
Systematic Review ◽  
Life Cycle ◽  
Software Development ◽  
Software Security ◽  
Security Assessment ◽  
Security Metrics ◽  
Development Life Cycle ◽  
Development Processes ◽  
Secure Software Development ◽  
Software Development Life Cycle

Background: With the advancement in the field of software development, software poses threats and risks to customers’ data and privacy. Most of these threats are persistent because security is mostly considered as a feature or a non-functional requirement, not taken into account during the software development life cycle (SDLC). Introduction: In order to evaluate the security performance of a software system, it is necessary to integrate the security metrics during the SDLC. The appropriate security metrics adopted for each phase of SDLC aids in defining the security goals and objectives of the software as well as quantify the security in the software. Methods: This paper presents systematic review and catalog of security metrics that can be adopted during the distinguishable phases of SDLC, security metrics for vulnerability and risk assessment reported in the literature for secure development of software. The practices of these metrics enable software security experts to improve the security characteristics of the software being developed. The critical analysis of security metrics of each phase and their comparison are also discussed. Results: Security metrics obtained during the development processes help to improve the confidentiality, integrity, and availability of software. Hence, it is imperative to consider security during the development of the software, which can be done with the use of software security metrics. Conclusion: This paper reviews the various security metrics that are meditated in the copious phases during the progression of the SDLC in order to provide researchers and practitioners with substantial knowledge for adaptation and further security assessment.

Software Traceability – A Key to Improve Software Evolution

2016 ◽  
Vol 685 ◽  
pp. 881-885
Author(s):  
Alexey Ponomarev ◽  
Hitesh S. Nalamwar
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Software Evolution ◽  
Software Traceability ◽  
Development Life Cycle ◽  
Methods And Techniques ◽  
Software Development Life Cycle

Software traceability is an important part in software development that is getting more and more attention nowadays from organizations and researchers. The paper outlines the importance, different methods and techniques of software traceability. It also explains the need of automating traceability, problems and drawbacks of existing traceability tools, the ongoing challenges facing implementation of traceability in software development life cycle, and finally the paper discusses whether software traceability should be mandated as a key to improve software evolution

Project Implementation Decision Using Software Development Life Cycle Models: A Comparative Approach

2021 ◽  
Vol 28 (1) ◽  
Author(s):  
M.A. Adeagbo ◽  
J.E.T. Akinsola ◽  
A.A. Awoseyi ◽  
F. Kasali
Keyword(s):  
Life Cycle ◽  
Comparative Analysis ◽  
Software Development ◽  
Cost Estimation ◽  
Comparative Approach ◽  
Project Implementation ◽  
Development Life Cycle ◽  
Software Development Life Cycle ◽  
Waterfall Model ◽  
Spiral Model

Selection of a suitable Software Development Life Cycle (SDLC) model for project implementation is somewhat confusing as there are a lot of SDLC models with similar strengths and weaknesses. Also, the solutions proffered among the researchers so far have been the  qualitative comparative analysis of SDLC models. Hence, this paper proposes a comparative analysis of SDLC models using quantitative approach in relation to strengths and weaknesses of SDLC models. The study adapted comparative analysis and Software Development Life Cycle (SDLC) models features’ classification using ten characteristics such as project complexity, project size, project duration, project with risk, implementation/initial cost, error discovery, associated cost, risk analysis, maintenance and cost estimation. A quantitative measure that employs online survey using experts in software design and engineering, project management and system analysis was carried out for the evaluation of SDLC models. Purposeful Stratified Random Sampling (SRS) technique was used to gather the data for analysis using XLSTAT after pre-processing, taking into consideration both benefit and cost criteria. The overall performance evaluation showed that Spiral-Model is the best followed by V-Model and lastly Waterfall Model with comparative values of 38.63%, 35.76% and 25.61% respectively. As regards cost estimation, Waterfall Model is the most efficient with value of 41%, then V-Model with 31% and lastly Spiral Model with 28%. V-Model has great error recovery capability with value of 45% which is closely followed by Spiral Model with 37% and lastly Waterfall Model with 18%. The study revealed that, a model with efficient risk assurance does not guarantee efficient cost management. In the future work, more characteristics regarding SDLC models shall be considered.

Understanding Online Conversation about COVID-19 Vaccine on Twitter: Data Mining Approach (Preprint)

2021 ◽  
Author(s):  
Ekaterina Malova
Keyword(s):  
Online Social Networks ◽  
Information Seeking ◽  
Information Dissemination ◽  
Vaccine Development ◽  
Online Communication ◽  
Vaccine Safety ◽  
Interaction Patterns ◽  
Twitter Users ◽  
The Government ◽  
Online Conversation

BACKGROUND Timely vaccination against COVID-19 can prevent a large number of people from getting infected. However, given the disease novelty and fast vaccine development, some people are hesitant to vaccinate. Online social networks like Twitter produce huge amounts of public health information and impact peoples' vaccination decisions. Hence, it is important to understand the conversation around the COVID-19 vaccination through the lens of social media. OBJECTIVE The present study aimed to define the nature of a larger Twitter conversation around the COVID-19 vaccine and explored interaction patterns between Twitter users engaged in such a conversation. METHODS Data collection took place in November 2020 on the wave of the news about the COVID-19 vaccine breakthrough. In total, 9600 Twitter posts were analyzed using a combination of text and network analysis. RESULTS Results of this study show that mixed-emotions reactions and discussions about potential side effects and vaccine safety dominated the online conversation. Twitter was primarily used for two purposes: information dissemination and opinion expression. Overall, the communication network was sparse, non-reciprocal, decentralized, and highly modular. Four main network clusters highlighted different groups of conversation stakeholders. CONCLUSIONS This study provides important insights into public sentiments, information-seeking behaviors, and online communication patterns during a major COVID-19 crisis. Given the popularity of Twitter among different types of communities and its power for rapid information dissemination, it can be an effective tool for vaccination promotion. Thus, it should be actively used to promote safe and effective vaccination through major stakeholders in the government, science, and health sectors.

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