Impacts of Software Deployment in the Coffee Agribusiness of Brazil

2005 ◽  
pp. 257-271
Author(s):  
Claudio T. Bornstein ◽  
Lucia Silva Kubrusly ◽  
André Luiz Zambalde ◽  
Ana Regina Rocha
Keyword(s):  
Software Deployment

A Characterization Framework for Software Deployment Technologies

1998 ◽  
Author(s):  
Antonio Carzaniga ◽  
Alfonso Fuggetta ◽  
Richard S. Hall ◽  
Dennis Heimbigner ◽  
Andre van der Hoek ◽  
...  
Keyword(s):  
Software Deployment

scholarly journals An Analysis Method for Software Deployment Conflict Detection

2021 ◽  
Author(s):  
Han Wu ◽  
Xinhui Li ◽  
Jiawei Hu ◽  
Jingsen Zhang ◽  
Yucheng Hua ◽  
...  
Keyword(s):  
Conflict Detection ◽  
Analysis Method ◽  
Software Deployment

scholarly journals A review on Continuous Integration, Delivery and Deployment using Jenkins

2021 ◽  
Vol 23 (06) ◽  
pp. 919-922
Author(s):  
Arpita S.K ◽  
◽  
Amrathesh Amrathesh ◽  
Dr. Govinda Raju M ◽  
◽  
...  
Keyword(s):  
Software Development ◽  
Software Tools ◽  
Integration Process ◽  
Continuous Integration ◽  
Software Deployment ◽  
Development Cycle ◽  
Continuous Delivery ◽  
Standard Practices ◽  
Development Methods ◽  
The Given

Continuous Integration (CI) is the technique of integrating small changes made to the code more often rather than waiting till the end of the development cycle for integration. The software practice wherein the software deployment can be done anytime to the market is called Continuous Delivery (CD). With continuous integration and continuous delivery, the problem of taking time to find and resolve the bug can be reduced to a large extent. As the time to find the bugs and fix them gets reduced, many releases adhering to the given timeline can be made by an organization. Various software tools have been developed for the continuous integration process which includes Jenkins, Bitbucket, TeamCity. In this paper, a review on the standard practices, approaches, challenges faced while using the continuous integration/delivery in the software development, methods of solving them, and using Jenkins for the implantation of continuous integration/delivery is done.

Critical Analysis of the Roles of Actors in the Deployment of Software

2015 ◽  
pp. 135-152
Author(s):  
Tefo Sekgweleo
Keyword(s):  
Competitive Advantage ◽  
Heterogeneous Network ◽  
Critical Analysis ◽  
Case Study Research ◽  
Actor Network Theory ◽  
Daily Activities ◽  
Complex Nature ◽  
Study Research ◽  
Software Deployment

Many organizations resort to software deployment with the intention to simplify their daily activities, and for competitive advantage. The deployment consists of two main phases, development and implementation. Unfortunately, software doesn't always fulfil the organization's intentions. This is attributed to numerous factors, some of complex nature, which happen among humans, non-humans, and between humans and non-humans actors during development and implementation of software. Case study research was conducted to understand the roles of actors, and how their actions and interactions impact the development and implementation of software in the organization. Actor Network Theory (ANT) was employed in the analysis of the data. The theory focused on activities including the negotiation among actors which happened within heterogeneous network.

Social Software for Customer Knowledge Management

2010 ◽  
pp. 1246-1258
Author(s):  
Zuopeng (Justin) Zhang
Keyword(s):  
Knowledge Base ◽  
Optimal Level ◽  
Customer Relationship ◽  
Social Software ◽  
Electronic Business ◽  
Business Managers ◽  
Negative Effects ◽  
Customer Knowledge ◽  
Software Deployment ◽  
Customer Knowledge Management

Social software is assuming a significant role in electronic business, increasingly referred to as e-business, and has been utilized recently on a growing scale by companies in customer relationship management. However, it is largely unclear at what levels firms should implement social software. This chapter addresses the gap by identifying the optimal level of social software deployment for a firm that plans to maximize its transactional benefits through the management of a customer knowledge base. The conclusion reached is that the optimal level of social software depends on a range of factors: for example, the initial volume of knowledge base, transaction benefits, and the estimates of the positive and negative effects of social software use. The chapter offers insights and guidance for business managers and practitioners.

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