Risk management automation of software projects based оn fuzzy inference

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Moreover, there is an increasing amount of literature covering specific geotechnical risk analysis and management topics. Examples of these are the difference between unsafe geotechnical certainty and safe geotechnical uncertainty (Barends, 2005), the role of the human factor in achieving geotechnical reliability (Bea, 2006), objective and subjective ways of geotechnical risk classification (Altabba et al., 2004), and contractual allocation of geotechnical risk (Essex, 2007).

Risk and risk management in software projects: A reassessment

Favorable planed management is the base of software project succeed. In this piece aim at the present situation of software project management, comprehensive use the thought of software engineering and project management, explore process and method of project schedule planning control. On the base of analysis software project schedule planning control difficulties, research based on PSP method. PSP follow adjustment, practice, measurement, comparison result and readjustment such a circulation and the continuous improvement of process, it is a process step by step for a long time. This paper studies the successful application of content; it can change insufficient plan in software project management process, the phenomenon of control adverse, improve comprehensive management ability and competitive power of project, creating Value for software company, improve high quality service for user.

Importance. The scale of implementation of educational projects in the Russian Federation is growing. Various federal projects, roadmaps for the development of education, strategies and policies for shaping the future of education, etc. are being developed. The results of our own research on risk management of educational projects are compared with the essential features characterising the current state of risk management of educational projects. The aim of the research is to substantiate the essential features identified and formulated in the course of this study, reflecting the meanings and values of the process of risk management of educational projects Materials and Methods. Texts of scientific articles, documents of applications for the status of the republican innovation site, documents summarising the work experience of the contestants in the field of educational projects in the republican contest “Teacher of the Year of the UR”, documents regulating educational projects within the framework of the National Project “Education”, documents aimed at the development of pedagogical education and training of pedagogical staff, texts of educational programmes of higher education–bachelor’s, master’s, and postgraduate courses. The research has been carried out using the methods of content analysis, critical discourse, reflexive problematisation, comparison and synthesis. Results and Discussion. The semantic units of the construct “risk management of educational projects” are highlighted and classified, and the results of our own research on each semantic unit are collated with the actual state of risk management processes. The study demonstrates that the risk management of educational projects is changing, the expert community is including risk management as an integral element in its activities, while the institutionalisation of risk management of educational projects is in the stage of methodological development.Conclusion. The activity of the subject of the educational project already includes risk management, while the process is built on the conscious use of an interdisciplinary approach, requiring special training, including the subject's awareness of the norms, rules, and regularities of risk management.

In a country like Ethiopia, where information and communication systems are in the early stage of development, software projects may face several challenges. Risk is one of the factors that challenges project performance, and even causes failure. Risk management helps project managers to control the effect of risks. However, risk management appears to be the least practiced component of project management. To help understand the software risk management practice in the developing countries (DC) context, this study explores the risk management practice of Ethiopian software projects. It also investigates the level of adoption of formal risk management models and which steps are included in the ad‐hoc risk management exercise. Finally, it looks into the relationship between risk management practice and project success. We conducted a survey of 45 banks, insurance companies and United Nations agency offices in Addis Ababa, Ethiopia. In this study, a very low rate of application of formal risk management models was observed. We observed a different perception of risk management whereby only watching projects to see if any risks occur during implementation without performing risk identification and mitigation or response plan was considered as a risk management practice by project managers. It was also found that some project managers were not able to confidently tell whether risk management processes have taken place in the projects they manage.

In the realm of software project management, predicting and mitigating risks are pivotal for successful project execution. Traditional risk assessment methods have limitations in handling complex and dynamic software projects. This study presents a novel approach that leverages artificial neural networks (ANNs) to enhance risk prediction accuracy. We utilize historical project data, encompassing project complexity, financial factors, performance metrics, schedule adherence, and user‐related variables, to train the ANN model. Our approach involves optimizing the ANN architecture, with various configurations tested to identify the most effective setup. We compare the performance of mean squared error (MSE) and mean absolute error (MAE) as error functions and find that MAE yields superior results. Furthermore, we demonstrate the effectiveness of our model through comprehensive risk assessment. We predict both the overall project risk and individual risk factors, providing project managers with a valuable tool for risk mitigation. Validation results confirm the robustness of our approach when applied to previously unseen data. The achieved accuracy of 97.12% (or 99.12% with uncertainty consideration) underscores the potential of ANNs in risk management. This research contributes to the software project management field by offering an innovative and highly accurate risk assessment model. It empowers project managers to make informed decisions and proactively address potential risks, ultimately enhancing project success.

Risk management and assessment of software project is highly relevant to the social and culture context of the development activities. This paper proposes a risk analysis approach which represents the organizational settings of a project as a social dependency network, and identifies risks originated from broken role dependency relations, unsatisfied goals, unfinished tasks, and unavailable resources amongst the network. Survey results on Chinese culture implications to software projects are incorporated as an example scenario to illustrate how to evaluate the influences of culture related factors to software project risk management using the proposed approach.

Despite the positive influence of risk management in Information Technology (IT) project results, many project managers are not managing risks or are managing them partially. To enhance risk management, collaborative project management has gained attention in recent years with the introduction of Web 2.0 tools. Project managers have used such tools to facilitate open communication and distribution of activities. This research introduces a prescriptive framework (W4RM – Wiki for Risk Management) based on a wiki to support collaborative risk management in IT projects. An exploratory focus group was set up and a series of interviews with practitioners was conducted to explore how a wiki can support risk management in IT projects. Findings show that project managers are facing difficulties managing risks and are the only ones responsible for identifying, registering and monitoring risks. By implementing a collaborative tool, managers can disseminate a collaboration culture and participate in risk management processes. This sense of collaboration may be used to keep the community identifying new risks, relating these risks to one or more projects, and facilitating continuous risk management. Practitioners can also adopt W4RM as a tool to support communication regarding risks status to be established for internal team stakeholders.

Due to globalisation, advances in computing technologies, as well as the deployment of software projects in distributed, collaborative and virtual environments, the software project management environment has changed. Traditional project management methods fail to address these added complexities. As a result, numerous software development projects either do not live up to expectations or they fail outright. The authors proposed the software project management model, entitled software project management supported by software agents (SPMSA) that aims to enhance software project management by taking the unique nature and changing environment of software projects into account. The SPMSA model supports the entire spectrum of software project management functionality, supporting and enhancing each key function with a team of software agents. In this extended paper, the authors adapt the SPMSA model to incorporate PMBOK2004 guidelines. The SPMSA model makes a fresh contribution to enhance software project management by utilising software agent technology.

Software project risk analysis using Bayesian networks with causality constraints

Project management is never easy, but an abundance of sophisticated Project Management (PM) software tools have certainly made the job of project managers easier than it was in the recent past. Project management software can manage, schedule, and monitor tasks, resources, and costs. However, with the plethora of features, the selection of the “right” features for inclusion in project management software becomes a dilemma for developers and vendors.This study provides a methodology for selecting the most profitable features for project management. Developers can include these features in contemplated future PM product lines. Filtered task lists and links to mainframe packages are the highest ranked profitable PM features. In contrast, On-line help is the lowest ranked among PM features.It is important to discover which features contribute the most to the segment margin. It reflects the profitability to the vendor and should guide the product designer. If the PM software contains these highest margin features, then most likely, it would command the highest possible profits.

Risk management in translation service companies is an effective, integrative, proactive way to handle risk. Such companies must integrate defined long-term risk management into their strategies, decision-making, and daily processes; top-management must fully support the risk management system; risk factors, management benefits, and processes require articulation amongst employees; job roles, responsibilities, performance evaluation, and motivation systems must incorporate risk management practices. Risk management in project-based companies might also account for changing clients’ requirements, tight deadlines and budgets, different participants, and high IT use. However, this requires identifying the critical success factors. The research method builds upon the analysis and systemization of the scientific literature – from risk management, emphasizing the underlying strategic approach and effective management, to deriving the focal-points of effective risk management of translation projects. This work unifies the gathered knowledge and results in a conceptual model that integrates the specific assessment criteria for project risk management in translation companies – process definiteness and versatility, responsibility definiteness, top-management involvement, and risk management communication. The operationalisation of the model may lead to the companies’ critical success performance. To the best of our knowledge, this work is one of the first contributions addressing risk management assessment criteria in this industry.

The use of agile methods tends to keep risks under control in software projects, due to their inherent characteristics of small increments, work visibility and expectation management. Thus, explicit risk management in agile projects has often been neglected, as the use of agile methods, with a focus on rapid value delivery, tends to lead to implicit risk management. However, software projects that use agile methods also can fail and implicit risk management may often not be sufficient for certain contexts. This has sparked research interest in the possible need for explicit risk management in software organizations that use agile methods. Motivated by the lack of information about risk management in agile software development contexts, in this work a comprehensive survey is carried out to understand how software development organizations that use agile methods are managing risk. We conducted an online survey with a statistically significant sample of 273 agile professionals in Brazil. Our findings indicate that although most organizations engage in some form of explicit risk management, a significant proportion consider agile methods insufficient for comprehensive risk mitigation. We also observed a set of 15 explicit risk management practices in agile contexts, with some agile ceremonies, notably daily and sprint planning meetings, emerging as conducive to the integration of explicit risk management practices. We also verified a statistically relevant association between these agile ceremonies and risk management processes.

This thesis explores the key concepts, theoretical frameworks, best practices and future trends in project risk management. Firstly, the definition and classification of risk and the basic process of project risk management are described in detail. Next, key risk management theories and models are analysed and risk management practices in different project management methodologies (e.g., waterfall model, agile methodology) are explored. The paper further discusses best practices in various stages of project risk management, including commonly used risk identification tools and techniques, qualitative and quantitative risk assessment methods, and demonstrates successful project risk management practices in different industries through case studies. Finally, the paper discusses the impact of emerging technologies on risk management and the challenges and opportunities facing project risk management in the future, and summarises the key success factors and lessons learned in project risk management. Through systematic risk management strategies, project teams can significantly improve project success rates, reduce the impact of potential problems, and drive successful project implementation.