Variation of risk profile across software life cycle in IS outsourcing

Sundararajan, Srikrishnan; Bhasi, M.; Vijayaraghavan, Pramod K.

doi:10.1007/s11219-019-09451-8

Cited by 8 publications

(3 citation statements)

References 13 publications

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“…The authors found that depending on the sufficiency of the project, organizational resources and profile requirements for project implementation, project managers can use these strategies as practical guidelines for systematic, thorough and effective risk reduction of a software project. The authors [16] proposed a questionnaire that allows measuring the risks and results of software development projects. With its help, a survey was conducted on the implementation of 145 software projects of global IT companies.…”

Section: Analysis Of Research and Publicationsmentioning

confidence: 99%

Project Team Management Model Under Risk Conditions

Rohovyi,

Grinchenko

2023

SM3P

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The paper examines the state of the problem of the influence of risks on the project team's work process. The processes of the team's work during the implementation of the project sprint are defined. The authors identified risk factors that affect the effectiveness of the project team. An analysis of modern approaches was carried out and three directions were identified, which represent the research of project team management processes under conditions of risk. A comprehensive reference model of project team management under risk conditions is proposed in the form of a framework. It reflects the interrelationship of four models: the project team behavior model, the model for assessing the quality of the formation of sprint tasks, the model for determining the distribution of tasks in the project team, and the model for the formation of recommendations. The project team evaluates the text description of the task, obtained from the information system, using the sprint task formation quality assessment model. Natural language processing methods are used to create a model for evaluating the quality of forming sprint tasks, which combine the method of processing text information and the method of learning based on precedents, which allows taking into account the previous experience of the team and its behavior. The project team behavior model allows taking into account the risks of irrational work organization during the sprint. The behavior of the project team is analyzed using Process Mining methods. The case representation model allows the project team to store and reuse knowledge and experience based on simulation modeling and reinforcement learning approaches. It allows the team to determine and evaluate possible options for the distribution of tasks and resources in the team in accordance with the reduction of possible risks. The central element of the proposed framework is the model of recommendations used in decision-making. It provides the project team with the necessary information for effective decision-making in terms of risks in project management. The proposed framework provides an opportunity to reduce the impact of the risks of non-fulfillment of project tasks during the sprint. Further studies of the task of managing the project team under conditions of risk should be directed to the development of specified models of the proposed framework

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Section: Analysis Of Research and Publicationsmentioning

confidence: 99%

Project Team Management Model Under Risk Conditions

Rohovyi,

Grinchenko

2023

SM3P

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“…The selected primary studies identify a total of 230 risks. Due to this large number of risks described in different ways, we decided to group them using a well known risks taxonomy [40], [41], [42] that provides three risk classes, its elements and attributes. We have collected all risks reported in the selected primary studies, classified according to the taxonomy, and summarized in Table VI.…”

Section: B Study Selectionmentioning

confidence: 99%

Managing Risks in Agile Methods: a Systematic Literature Mapping

García¹,

Hauck²,

Hahn³

2022

Proceedings of the 34th International Conference on Software Engineering and Knowledge Engineering

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Agile software development methods have been around since at least 2001. They accommodate changing requirements with the flexibility to deal with cost and scope and have increasingly been used. However, explicit risk management is often ignored as agile methods deal with risk intrinsically and focus on rapid value delivery. In certain contexts, explicit risk management practices are needed to complement agile methods. Thus, this paper presents a systematic literature mapping aiming to discover how do software organizations integrate explicit risk management practices into agile methods. As a result we found 23 primary studies that, in majority, applied case studies in the industry, using agile methods such as Scrum, and adapting agile practices such as Daily Meeting and Iteration Planning Meeting to manage risks related to schedule and communication, for example. The selected primary studies raise evidence that the introduction of explicit risk management practices bring benefits to agile methods.

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“…Em uma economia baseada em informações, a indústria de software tem desempenhado um papel significativo, contribuindo para o crescimento das atividades produtivas em todos os setores. Todavia, surgiram novos desafios no que diz respeito ao gerenciamento de projetos criados para o desenvolvimento de software, realizando um esforço sistemático para gerenciar os riscos associados aos projetos de software relevantes (Qu & Wang, 2015), já que o risco é representado pelo potencial de gerar resultado indesejado na forma de incidentes, eventos ou ocorrências (Badurdeen et al 2014), sendo essencial que sejam conhecidos e mensurados, monitorados e atenuados os seus efeitos negativos (Shao, Feng, & Hu, 2016;Firdose & Rao, 2018;Li et al 2019;Sundararajan, Bhasi, & Vijayaraghavan, 2019).…”

Section: Introductionunclassified

Risk Evaluation in Software Project Using Bayesian Network Modeling

Cassia¹,

Librantz²,

Costa³

et al. 2020

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Project risk events are often influenced by each other and rarely act independently. In this context, effective methods to identify, model and analyze these risks are necessary. The objective of this article is to apply the risk analysis in a software development project, based on the model of the Software Engineering Institute (SEI), using the Bayes model to calculate the event probabilities and also the Noisy-OR calculation structure to assign the initial weights of the network of factors that influence the project. In this way, it is expected to increase the chances of success of the risk analysis process. The results obtained by the techniques adopted prove to be promising in assisting the process of decision making by the managers of software development projects.

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Variation of risk profile across software life cycle in IS outsourcing

Cited by 8 publications

References 13 publications

Project Team Management Model Under Risk Conditions

Project Team Management Model Under Risk Conditions

Managing Risks in Agile Methods: a Systematic Literature Mapping

Risk Evaluation in Software Project Using Bayesian Network Modeling

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