Collaborative Risk Management in Software Projects

2012 ◽  
Author(s):  
Pedro Sa Silva ◽  
Antonio Trigo ◽  
Joao Varajao
Keyword(s):  
Risk Management ◽  
Software Projects

Case study on risk management practice in large offshore‐outsourced Agile software projects

IET Software ◽  
2014 ◽  
Vol 8 (6) ◽  
pp. 245-257 ◽  
Author(s):  
Srikrishnan Sundararajan ◽  
Marath Bhasi ◽  
Pramod K. Vijayaraghavan
Keyword(s):  
Risk Management ◽  
Management Practice ◽  
Software Projects ◽  
Agile Software

Dealing with Risk: A Practical Approach

1996 ◽  
Vol 11 (4) ◽  
pp. 333-346 ◽  
Author(s):  
Fred J. Heemstra ◽  
Rob J. Kusters
Keyword(s):  
Risk Management ◽  
Practical Approach ◽  
Successful Outcome ◽  
Software Projects ◽  
Counter Measures ◽  
Neutral Process ◽  
Related Approach ◽  
Process Risk ◽  
Management Method

Most software projects take place in a volatile environment in which many dangers exist that may affect the successful outcome of the project. After completion of the project an evaluation may show that many of the problems encountered during the project could have been foreseen before they actually occurred. Risk management is an approach that is aimed at predicting the occurrence of this type of problem and at taking counter measures to either prevent them from affecting the project or to soften their impact. In this paper the basic activities related to risk management are described. Furthermore a concrete method aimed at supporting risk management is presented. This method has been used successfully in practice. Some of the results obtained by using it are presented on the basis of five cases. Some conclusions are that: (1) the use of a short and structured checklist will ease identification of and discussions about risks, (2) a risk management method in which explicit use is made of a group related approach, involving all parties, will increase reliability and acceptance of the results, and (3) involvement of a neutral process risk advisor will further both the successful use of the method and the acceptance of the results.

Risk management in software projects through Knowledge Management techniques: Cases in Brazilian Incubated Technology-Based Firms

2014 ◽  
Vol 32 (1) ◽  
pp. 125-138 ◽  
Author(s):  
Sandra Miranda Neves ◽  
Carlos Eduardo Sanches da Silva ◽  
Valério Antonio Pamplona Salomon ◽  
Aneirson Francisco da Silva ◽  
Bárbara Elizabeth Pereira Sotomonte
Keyword(s):  
Risk Management ◽  
Knowledge Management ◽  
Software Projects ◽  
Management Techniques

Risk management for software projects

IEEE Software ◽  
1994 ◽  
Vol 11 (3) ◽  
pp. 57-67 ◽  
Author(s):  
R. Fairley
Keyword(s):  
Risk Management ◽  
Software Projects

scholarly journals Project risk management in Iranian software projects

2018 ◽  
Vol 8 (2) ◽  
pp. 81-88 ◽  
Author(s):  
Ali Afshari ◽  
Vladimir Brtka ◽  
Melita Ćoćkalo-Hronjec
Keyword(s):  
Risk Management ◽  
Project Risk Management ◽  
Software Projects ◽  
Project Risk

A Framework for Risk Management in AI System Development Projects

2019 ◽  
pp. 1-20
Author(s):  
Kitti Photikitti ◽  
Kitikorn Dowpiset ◽  
Jirapun Daengdej
Keyword(s):  
Artificial Intelligence ◽  
Risk Management ◽  
Project Management ◽  
Software Development ◽  
System Development ◽  
Systems Development ◽  
Development Projects ◽  
Software Project ◽  
Software Projects ◽  
Very High

It has been well-known that the chance of successfully delivering a software project within an allocated time and budget is very low. Most of the researches in this area have concluded that “user's requirements” of the systems is one of the most difficult risks to deal with in this case. Interestingly, until today, regardless of amount of effort put into this area, the possibility of project failure is still very high. The issue with requirement can be significantly increased when developing an artificial intelligence (AI) system, where one would like the systems to autonomously behave. This is because we are not only dealing with user's requirements, but we must also be able to deal with “system's behavior” that, in many cases, do not even exist during software development. This chapter discusses a preliminary work on a framework for risk management for AI systems development projects. The goal of this framework is to help project management in minimizing risk that can lead AI software projects to fail due to the inability to finish the projects on time and within budget.

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