Software Risk Management Research Articles

Radiation therapy facility risk analysis in Brazil with SEVRRA software

Risk assessment deals with processes, accident-initiating events, barriers and risk ratings to unveil the fragility and weakness of some processes; within this study, specifically related to radiation therapy facilities. Barriers are technical or organizational safety measures put in place to avoid, prevent, detect, control, reduce or mitigate the consequences of an accident once an initiating event has occurred. In this work, radiological risk analysis was performed for a set of 20 Brazilian radiotherapy facilities making use of the freeware sevrra risk-management software. The objective of this study was to define parameters that could be useful in creating an overall risk profile. This profile would be helpful for establishing priorities for decision making and support a risk-informed regulatory process. The most relevant missing barriers in facilities were identified according to three parameters: the ‘importance index’, ‘impacted facilities index’ and the ‘barrier-effectiveness index’. Barriers such as ‘in vivo dosimetry in the first treatment session’, ‘weekly in vivo dosimetry to detect errors in the dose delivering process’, ‘annual external audit for the control of reference dose rate’ and ‘independent verification of calibration by various medical physicists with a different dosimetry equipment’ were found to be the most effective in reducing the risk level of the facilities. The present investigation reinforces the need to strengthen the mechanisms that guarantee the effectiveness of such barriers in radiation therapy procedures.

A Critical Analysis of Software Risk Management Techniques in Large Scale Systems

Researchers in the software industry have focused on risk management systems for a long time. Software risk management is a software engineering practice that contains risk identification, risk estimation, mitigation, and monitoring. It delivers a disciplined environment for efficient decision-making to assess the problems in software development. Measuring risks in a large-scale system is comparatively difficult because of its complex nature. Large-scale systems are challenging since many risks can arise during system development. Risk factors in large-scale systems are relatively different from small systems, especially with respect to the independent components. This paper describes a difference between large-scale and small-scale systems along with an exhaustive list of risk factors. The tools from the literature are further divided into sub categories according to those that are best suited. We present a detailed comparative analysis for different software-related risk management models with some commonly identified features and further categorize them into classes based on the severity of their risks.

Analysis of advance software tools and techniques for software risk management and classification

Analysis of advance software tools and techniques for software risk management and classification

Управління ризиками розробки програмного забезпечення за умови обмеженості коштів виділених на усунення помилок безпеки

Управління ризиками розробки програмного забезпечення за умови обмеженості коштів виділених на усунення помилок безпеки

The risk matrix: uncertain results?

AbstractThe consequence/likelihood risk matrix is a widely used risk analysis and reporting technique, often incorporated into risk and safety management software, and often relied on to help make decisions about the tolerability of risk. However, decision makers may not be aware of matrix design features that give rise to uncertainty, or of errors in its use causing further uncertainty. This paper builds on prior evidence to argue that poorly designed or inappropriately used risk matrices result in an increase in uncertainty and, potentially, adverse effects on people and organizational objectives. It is further argued that risk matrices should be designed for reporting as part of an overall risk assessment, and not used on their own. The evidence is reframed as a goal tree to show where design and use of the matrix might reduce, but not eliminate, uncertainty in risk assessments. Suggestions are given for reducing uncertainty in the design and use of risk matrices that may enable more effective risk ass...

A Review of Risk Management Planning and Reporting in South Africa’s Public Institutions

This exploratory work attempts to review the risk management planning and reporting practices applied in South Africa’s public institutions by defining variables that were deemed indicators of risk management planning and reporting practices, namely: the timing of the institutions’ strategic and combined assurance planning, documentation and active management of risks appearing in strategic risk registers and operational risk registers and the availability of risk management software (including its nature and usefulness).The results point to the fact that there is confusion regarding the timing of both strategic and combined assurance planning sessions. Some institutions conduct these in the preceding year, whereas others appear to be conducting these during the year of implementation. Results further suggest that the practice of implementing combined assurance has not yet been embedded in the majority of public institutions, pointing to uncoordinated assurance activities that could lead to ‘assurance fatigue’. Results further point to the fact that there are still public institutions that are unable to prepare the strategic and operational risk registers. This raises the question of how these risks are managed if they have not been measured and documented.

Analyzing and Resolving Issues in Software Project Risk Management

In last decade the main reason for projects failure is poormanagement of software. But now a day’s most of the organizations arefocusing on software project management for making project successful.Software project management provides overall management of softwarefrom project planning phase to project execution. In software projectmanagement we also deal with risks that may occur during developmentof projects. In this paper we analyze risks during management ofsoftware and we resolve issues that come in software project riskmanagement. We introduce some approaches by which we can resolveall the issues regarding software risk management. Risk managementalso suggests us that how we can avoid risks and if risks occur then howwe can control those risks. By analyzing software risk management, wecome to know that what factors affect risk management and how we canremove them. Software risk management manages all risks efficientlyand makes our project successful.

Software Project Risk Management Practice in Ethiopia

AbstractIn 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.

Framework for Risk Management Software System for SMEs in the Engineering Construction Sector

Small and medium-sized enterprises (SMEs) in construction sector are vulnerable and face exposure to risks whilst operating without risk management system in place. Evidence from market research and industry surveys confirm that SMEs underperform due to inability to manage operational risk challenges facing them. The objective of this study is to develop risk management software enabling SMEs in the construction sector to proactively identify, analyse and manage risks facing them to enhance business performance. Performance in the construction sector is assessed in terms of completion time, project execution cost and overall quality of delivery. Research framework based on balanced score card highlights risk indicators affecting performance. The risk software guides operator to avoid, minimise, mitigate or manage the relevant risks to enable successful performance outcome. The system will enable systematic risk management to achieve minimum cost and time overrun while optimising quality of delivery in a project management environment.

Top Fifty Software Risk Factors and the Best Thirty Risk Management Techniques in Software Development Lifecycle for Successful Software Projects

The concern of this study is to identify software risks and controls in the software development lifecycle. The aim of this study is to rank the software risks factors according to their importance and occurrence frequency based on the data source. The survey questionnaire is used to collect data and method of sample selection referred to as ‘snowball’ and distribution personal regular sampling was used. The seventy six software project managers have participated in this study who works in the Palestinian software development. Fifty software risk factors in all phases SDLC and thirty risk management techniques were presented to respondents. The results show that all risks in software projects were significant and important in software project manager's perspective. However, the ranking of the importance of the risks is assigned according to it: Analysis, planning, maintenance, design, and implementation. In addition, the top ten software risk factors in software development are selected and used for further analysis such as: Risk13, Risk 14, Risk15, Risk16, Risk11, Risk18, Risk12, Risk50, Risk19, and Risk 9. The concern of this paper the top ten controls are used to model its relationship with the risk, such as: C29, C30, C20, C27, C21, C19, C28, C25, C26, and C23. Software risks can be modelled empirically with risk management control techniques. We recommended applying more studies in software risk management practices with real world companies and building tools to identification and analysis software risks based on quantitative and intelligent techniques.

УПРАВЛІННЯ РИЗИКОМ ЗАБЕЗПЕЧЕННЯ БАНКІВСЬКИХ ПОЗИЧОК НА ОСНОВІ МЕТОДІВ РИЗИК-МЕНЕДЖМЕНТУ

Стаття спрямована на дослідження методів та інструментів управління ризиком забезпечення банківських позичок. Обґрунтовано, що ефективність управління ризиком забезпечення банківських позичок залежить від системності, адекватності способів їх оцінки, методів контролю та своєчасності системи реагування з боку банків та регулятора.
 Метою статті є розробка рекомендацій щодо підвищення ефективності управління ризиком забезпеченням банківських позичок з урахуванням ризиків, що притаманні процесу супроводження заставного портфеля банків, в умовах значної невизначеності функціонування банків.
 Доведено, що ризик забезпечення банківських позичок в кредитному менеджменті доцільно розглядати через характеристику ризиків, які формують сукупний кредитний ризик.
 Обґрунтовано, що управління ризиком забезпечення відповідає класичному ризик-менеджменту, який виділяє чотири основні етапи: ідентифікація; оцінка ризику забезпечення; контроль ризику; мінімізація ризику.

Decision Analysis Tool for Small Satellite Risk Management

Risk management plans improve the likelihood of mission success by identifying potential failures early and planning mitigation methods to circumvent any issues. However, in the aerospace industry to date, risk management plans have typically only been used for larger and more expensive satellites and have rarely been applied to lower-cost satellites such as CubeSats. Furthermore, existing risk management plans typically require experienced personnel and significant time to perform the analysis. The CubeSat Decision Advisor tool uses components of decision theory such as decision trees, multi-attribute utility theory, and utility elicitation methods to determine the expected utilities of proposed mitigation techniques to a mission risk. Based on the user’s value preference system, assessment of success probabilities, and resources required for a given mitigation technique, the tool suggests the course of action that will normatively yield the most value for the COST, people, and time resources required. This research creates a risk management software tool never before available that is easily accessible and usable for low-cost small satellite missions due to its construction in Microsoft™ Excel. A demonstration analysis is conducted on a university CubeSat mission as a case study. The target audience for this tool is primarily university labs, which could not otherwise afford expensive software packages. However, the tool is broadly applicable to all organizations, including government, academic, and corporate, and is not constrained to university small satellite mission architectures.

Quantitative and Intelligent Risk Models in Risk Management for Constructing Software Development Projects: A Review

Techniques and models for mitigating risk in software development projects classified into three categories–namely, qualitative, quantitative, and intelligent approaches. This paper is to review the quantitative and intelligent risk models in software risk management for software development projects. Indeed, this area needs more effort from scholars and researchers in quantitative and intelligent risk models to mitigate risks. As future work, we will use these hybrid models of quantitative and intelligent for mitigating software risks in cloud computing such as neural network, genetic algorithm and others artificial intelligence techniques.

Involving user perspective in a software risk management process

AbstractMore and more user groups are using medical devices. Heart starters are, for example, available in public places and used by non‐professionals. Different mobile medical applications, designed to help people manage their own health, are now being added to the medical device spectra. Users handling medical devices make errors, but by involving users in the risk management process, it is possible to lower the risk of these errors. This paper presents an evaluation of the value of complementing a traditional risk management process with an emphasised user perspective. A medical device software risk management framework is being designed, and the risk management process should be regarded as the first part of the framework. The main goal of the evaluated risk management process is to integrate users and user perspective into the risk management process. The results indicate that the use of use cases as input at risk meetings makes the discussions more focused, saving effort and time. When users attend the risk meetings, user perspective and domain knowledge are brought into the process, affecting risk identification and risk assessment. The results also show that the use of usability testing gives valuable input to the risk management process. Copyright © 2015 John Wiley & Sons, Ltd.

Practical Applications of The Divergence of High- and Low-Frequency Estimation: Causes and Consequences

Surprising new evidence suggests that the “square root of time” rule for annualizing standard deviation—hard-coded into risk management and optimization software packages and embedded in the Black-Scholes equation—is often wrong. Will Kinlaw , Mark Kritzman and David Turkington explain why in The Divergence of High- and Low-Frequency Estimation: Causes and Consequences ( The Journal of Portfolio Management’s 40 th Anniversary Issue ). The article was named Outstanding Article in the 16 th Annual Bernstein/Fabozzi Jacobs Levy Awards . Their research is useful for portfolio managers and investors who are confronting the challenges of balancing short- and long-term investment outcomes. The authors advise caution when extrapolating high-frequency risk estimates to long-term scenarios, drawing on divergence between US and emerging-market stocks from 1990 to 2013 to illustrate the dangers of this approach.

Yazılım Projelerinde Karşılaşılan Risk Faktörleri ve Risk Yönetim Süreci

There are very important problems that occur nowdays in the field of software projects ever widespreading. The respective problems has influenced software being developed negatively. Therefore, “Software Risk Management” processes must be carried out successfully beyond a good coding in order to avoid or to minimize this situation. In this study, within the scope of the software project management, risk identification, risk factors, risk types, risk strategies and risk management process are discussed in details and comparative. By revealing the software risks and the methods of prevention of these risks, the necessasy actions has been clarified to eliminate or to reduce the risks resulting from any software. This study is aimed at being an important reference for the researches interested in this field

Classification and Identification of Risk Management Techniques for Mitigating Risks with Factor Analysis Technique in Software Risk Management

Regardless how much effort we put for the success of software projects, many software projects have a very high failure risk rate. The failure risk is not always avoidable, but it could be controllable by using risk management technique through the software development Lifecycle. The aim of this study is to present the factor analysis techniques to classify and identify the risk management techniques in the software development project. The best thirty risk management techniques were presented to respondents and all risk management techniques are used most of the time, and often. We have chosen three components: Planning and requirement techniques, communication techniques, models and tools for thirty risk management techniques. The study has been conducted on a group of software project managers in software development companies. We will intend to apply these study results on a real-world software project to verify the effectiveness of the risk management techniques on a software project for mitigating risks. Successful identifying of risk management techniques will greatly improve the probability of mitigating software risk.

A Probabilistic Software Risk Assessment and Estimation Model for Software Projects

Software risk management plays a vital role in successful software project management. In fact, all the phases of the software development life cycle (SDLC) are potential sources of software risks since it involves hardware, software, technology, people, cost, and schedule. There are a number of software risk factors that affect the whole software development process. However, finding the correlation between risk factors and project outcome is the main focus of present research on software risk analysis. In this paper, a probabilistic software risk estimation model is proposed using Bayesian Belief Network (BBN) that focuses on the top software risk indicators for risk assessment in software development projects. In order to assess the constructed model, an empirical experiment has been performed, based on the data collected from software development projects used by an organization.

A COMPARISON OF STEPWISE AND FUZZY MULTIPLE REGRESSION ANALYSIS TECHNIQUES FOR MANAGING SOFTWARE PROJECT RISKS: ANALYSIS PHASE

Risk is not always avoidable, but it is controllable. The aim of this study is to identify whether those techniques are effective in reducing software failure. This motivates the authors to continue the effort to enrich the managing software project risks with consider mining and quantitative approach with large data set. In this study, two new techniques are introduced namely stepwise multiple regression analysis and fuzzy multiple regression to manage the software risks. Two evaluation procedures such as MMRE and Pred (25) is used to compare the accuracy of techniques. The model’s accuracy slightly improves in stepwise multiple regression rather than fuzzy multiple regression. This study will guide software managers to apply software risk management practices with real world software development organizations and verify the effectiveness of the new techniques and approaches on a software project. The study has been conducted on a group of software project using survey questionnaire. It is hope that this will enable software managers improve their decision to increase the probability of software project success.

Risk Management in Software Projects with Microcontroller

The main motive to present this paper is to provide a secure management in software with the help of sense controlled device microcontroller This paper reviews the basic concepts, terminology, and techniques of Software Risk Management. It teaches readers how to identify and analyse software risks on their projects. Readers then learn techniques for planning indicting to mitigate risks so that the overall impact of those risks on their projects is minimized.