scholarly journals ANALYSIS OF KNOWLEDGE SHARING PRACTICES IN DISTRIBUTED AGILE ENVIRONMENT

2016 ◽  
pp. 151-156
Author(s):  
NISHA GUPTA ◽  
JAGPUNEET KAUR BAJWA
Keyword(s):  
Software Development ◽  
Knowledge Sharing ◽  
Explicit Knowledge ◽  
Distributed Environment ◽  
Development Life Cycle ◽  
Software Development Life Cycle ◽  
Quality Of Products ◽  
Implicit And Explicit ◽  
Analysis Of Knowledge

Knowledge plays a key role in the software development process. Knowledge is necessarily required at all the phases of software development life cycle. Knowledge is the core resource, so organizations are now attempting to manage it in more efficient and systematic way. Knowledge sharing plays a very important role in the successful development of software. Knowledge sharing in distributed agile team is helpful in achieving the goals like better quality of products delivered on time and at lower cost. Our research analyzes the knowledge sharing practices in distributed environment and found the best implicit and explicit knowledge sharing practices.

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.

scholarly journals DevOps phases across Software Development Lifecycle

2021 ◽  
Author(s):  
Mayank Gokarna
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Implementation Strategy ◽  
Quality Of Services ◽  
Comprehensive Collection ◽  
Development Lifecycle ◽  
Development Life Cycle ◽  
Software Development Lifecycle ◽  
Software Development Life Cycle

DevOps is the combination of cultural mindset, practices, and tools that increases a team's ability to release applications and services at high velocity. The development and operations teams always have a conflict around the scope of responsibility. With these differences the quality and speed of delivery across software Development Life Cycle is negatively impacted. DevOps is about removing the barriers between two traditionally delimited teams, development and operations. With DevOps, these two teams work together to optimize both the productivity of developers and the reliability of operations. They strive to communicate frequently, increase efficiencies, and improve the quality of services they provide. They take full ownership for their services, often beyond where their stated roles or titles have traditionally been scoped. Transitioning to DevOps requires a change in culture and mindset first. It is quite difficult to persuade a whole company to change its culture at once. This paper aims to bring different phases of software development lifecycle into DevOps implementation strategy and presents a comprehensive collection of leading tools used across Software Development life Cycle to automate and integrate different stages of software delivery. This paper also highlights on DevOps practices which span across different phases of the Software Development Lifecycle and how those can be implemented with different tools available.

scholarly journals Architecture Evaluation of Mobile Application: Whatsapp

2019 ◽  
Vol 8 (10) ◽  
pp. 1253-1256
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Mobile Application ◽  
Life Quality ◽  
Stage Of Development ◽  
Development Life Cycle ◽  
Architecture Evaluation ◽  
Software Development Life Cycle ◽  
The One

Software become an unavoidable in every once life. Quality of the software is an import aspect in the software development life cycle. Quality for a software is represented in terms of functional and non-functional requirement. Software architecture is used to represent the using set of components and is connectivity as a relationship between these components. To assure the development process meet the requirement given by the user, the Software Evaluation is used. Early detection of error protect the software development producing the defect software. ATAM is the one of the method used to detect the risk, non-risk, scenarios and tradeoff in the earlier stage of development life cycle. Here in this paper security scenarios for mobile application has been elicited and compared with the scenarios extracted from the whatsapp application. Comparison shows few scenarios need to added with existing scenarios in order to improve / ensure full security for the metadata.

Managing Tacit Knowledge for a Software Development Process: A Case Study

2012 ◽  
Vol 11 (01) ◽  
pp. 1250001
Author(s):  
David P. Stevens ◽  
Sonya H. Y. Hsu ◽  
Zhiwei Zhu
Keyword(s):  
Software Development ◽  
Tacit Knowledge ◽  
Development Process ◽  
Explicit Knowledge ◽  
Software Development Process ◽  
Development Life Cycle ◽  
Managerial Implications ◽  
Software Development Life Cycle ◽  
Why Questions

The acquisition and management of knowledge is increasingly more important in today's economy because of the large proportion of the workforce eligible for retirement in the next 10 years. Companies have long understood that reusing explicit knowledge in the form of policies, documentation and procedures produces tremendous savings, reduces variability, decreases costs, and improves overall quality. Unfortunately, a considerable portion of corporate knowledge is tacit or known at a non-verbal level, and does not lend itself to reuse. This research examines "how" and "why" questions regarding a specific process used for managing and sharing tacit knowledge related to the software development life cycle. The issues related to acquiring, preserving and disseminating the tacit knowledge are discussed in detail, and the advantages and managerial implications of the results of the method are described, together with implications for knowledge workers and managers in other industries.

scholarly journals Analysis of Knowledge Sharing Using Canonical Correlation Toward Organizational Innovation

2019 ◽  
Vol 15 (2) ◽  
pp. 112-127
Author(s):  
Vebi Dewi Supartini ◽  
Anggraini Sukmawati ◽  
Elisa Anggraeni
Keyword(s):  
Knowledge Sharing ◽  
Canonical Correlation ◽  
Explicit Knowledge ◽  
Organizational Innovation ◽  
Strong Relationship ◽  
Collection Method ◽  
Tacit Knowledge Sharing ◽  
The Relationship ◽  
Analysis Of Knowledge

This paper is based on the importance of knowledge sharing to create innovation in an organization to overcome the problem of PTPN competition with the private sector. The purpose of this study is to determine the relationship between knowledge sharing variables, which are tacit knowledge sharing and explicit knowledge sharing, on innovation variables, which are speed innovation and quality innovation. The data collection method used a questionnaire with a sample of 100 employees and data were analyzed using canonical correlation analysis. The results of the study showed that there was an influence on each variable. Explicit knowledge sharing had influence on the speed and quality of innovation and explicit knowledge sharing had influence on the speed and quality of innovation. Conclusions from this study were that both variables had a strong relationship, so companies can consider these variables in strategic planning.

scholarly journals DevOps phases across Software Development Lifecycle

2021 ◽  
Author(s):  
Mayank Gokarna
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Implementation Strategy ◽  
Quality Of Services ◽  
Comprehensive Collection ◽  
Development Lifecycle ◽  
Development Life Cycle ◽  
Software Development Lifecycle ◽  
Software Development Life Cycle

DevOps is the combination of cultural mindset, practices, and tools that increases a team's ability to release applications and services at high velocity. The development and operations teams always have a conflict around the scope of responsibility. With these differences the quality and speed of delivery across software Development Life Cycle is negatively impacted. DevOps is about removing the barriers between two traditionally delimited teams, development and operations. With DevOps, these two teams work together to optimize both the productivity of developers and the reliability of operations. They strive to communicate frequently, increase efficiencies, and improve the quality of services they provide. They take full ownership for their services, often beyond where their stated roles or titles have traditionally been scoped. Transitioning to DevOps requires a change in culture and mindset first. It is quite difficult to persuade a whole company to change its culture at once. This paper aims to bring different phases of software development lifecycle into DevOps implementation strategy and presents a comprehensive collection of leading tools used across Software Development life Cycle to automate and integrate different stages of software delivery. This paper also highlights on DevOps practices which span across different phases of the Software Development Lifecycle and how those can be implemented with different tools available.

scholarly journals Software Development Life Cycle Models-A Comparative Study

2020 ◽  
pp. 30-37
Author(s):  
Gagan Gurung ◽  
Rahul Shah ◽  
Dhiraj Prasad Jaiswal
Keyword(s):  
Software Development ◽  
Small Firms ◽  
Development Process ◽  
Software Development Process ◽  
Advantages And Disadvantages ◽  
Step Procedure ◽  
Development Life Cycle ◽  
Software Development Life Cycle ◽  
Traditional Work

Software Development is one of the most powerful, vital, and the need for an hour in today's generation. Every organization, industries, small firms, institutes, etc. require the software for the functionality of their system and reducing the manual work or the traditional work, which used to be insecure and had more errors. SDLC is all about the minimization of the risk and failure and maximization of the quality of the product. To make the development works in a step by step procedure and precisely SDLC came into existence. The SDLC defines the framework that includes different activities and tasks to be carried out during the software development process. There are many types of SDLC models, which have their advantages and disadvantages and will work as per their needs.

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.

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