Continuous Risk Management Guidebook.

Dorofee, Audrey; Walker, Julie; Alberts, Christopher; Higuera, Ronald P.; Murphy, Richard L.

doi:10.21236/ada319533

Cited by 119 publications

(75 citation statements)

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“…There are many works whose goal is to study and propose mechanisms for risk management in general [8,4,9,27,28]. Among these works, it is worth to mention the efforts of the Software Engineering Institute (SEI), [8] that offers a wide set of works and technical reports about risks, and defines a model for the management of software development risks, which controls the quality, cost, and schedule of software products. This risk management paradigm follows five cyclic activities: Identification, Analysis, Planning, Track and Control.…”

Section: Risks Of Requirement Engineeringmentioning

confidence: 99%

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Requirement Risk Level Forecast Using Bayesian Networks Classifiers

Cano

2011

Int. J. Soft. Eng. Knowl. Eng.

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Requirement engineering is a key issue in the development of a software project. Like any other development activity is not without risks. This work is about the empirical study of risks of requirements by applying machine learning techniques, specifically Bayesian networks classifiers. We have defined several models to predict the risk level for a given requirement using three dataset that collect metrics taken from the requirement specifications of different projects. The classification accuracy of the Bayesian models obtained is evaluated and compared using several classification performance measures. The results of the experiments show that the Bayesians networks allow obtaining valid predictors. Specifically, a tree augmented network structure shows a competitive experimental performance in all datasets. Besides, the relations established between the variables collected to determine the level of risk in a requirement, match with those set by requirement engineers. We show that Bayesian networks are valid tools for the automation of risks assessment in requirement engineering.

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Section: Risks Of Requirement Engineeringmentioning

confidence: 99%

“…The most used methods for the identification of the risky software development components are qualitative [8,9]. Potential risks are assessed by applying subjective risk assessment techniques that are qualitative, human-intensive and error-prone [10].…”

Section: Introductionmentioning

confidence: 99%

Requirement Risk Level Forecast Using Bayesian Networks Classifiers

Cano

2011

Int. J. Soft. Eng. Knowl. Eng.

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“…This causes huge loss for companies. The first steps in risk management is identifying and analyzing the risks in the maintenance project [6]. To support professionals' work, we have conducted a formal study of the risks affecting the ERP maintenance.…”

Section: Erp Maintenance Risksmentioning

confidence: 99%

“…This is a process of evaluating attributes, classifying and prioritizing the risks identified [6]. The risk classification phase consists of grouping the risks identified according to their characteristics.…”

Section: Erp Maintenance Risksmentioning

confidence: 99%

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Exploring Risk Factors in ERP Maintenance Projects

López¹,

Salmeron²

2011

Scientific Journal of Riga Technical University. Computer Sciences

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-In recent decades, companies across the world have implemented Enterprise Resource Planning (ERP) systems. The proper ERPs implementation has been a much explored issue. In contrast, ERP systems maintenance has been treated with less depth. ERP maintenance is necessary to achieve the system's maximum performance. Nevertheless, these projects are often managed intuitively and without taking into account the existing risks. To address this need, we have studied ERP maintenance risks. In this way, we have identified and classified the risks affecting the performance of ERP maintenance projects. Moreover, we have applied a multicriteria decision making methodology to assess them. The results will help practitioners to manage ERP maintenance project risks in a better way.

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Risk Management

Charette

2002

Encyclopedia of Software Engineering

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The art of management has been defined as the distribution of current resources to shape a more desirable future state. However, the future is not always as envisioned, because the path to the future is neither immutable nor totally predictable. How well one manages the risks, as well as the opportunities, that materialize along the way will determine whether a more desirable state is achieved. Thus risk management can be described as the continuous analysis of the current situation to realign current resources and management policies against current and future threats, or to maximize the opportunities that are present, thus helping to ensure that the state originally envisioned or one that is better occurs. The following basic questions: The prime motivation for the currently rising interest in risk management and software engineering can be directly traced to two overriding business, as opposed to technology, considerations. The first is the ever increasing complexity and cost of developing software‐intensive systems, coupled with the intensifying negative impact on businesses and individuals when they go awry. The second is that software‐intensive systems have finally achieved the long promised state of becoming the paramount strategic element in an organization's short‐term and long‐term competitive success equation. The risk management field as it applies specifically to software engineering is currently experiencing a period of rapid growth and increased stature, with many governmental and commercial initiatives being pursued to codify the many diverse aspects of the subject into a unified whole. Current research and application efforts undertaken in software engineering related risk management have been concentrated in three overlapping provinces: theory, mechanics, and practice. An overview of each is provided here with the main concentration placed on risk management mechanics. International standards are detailed.

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Continuous Risk Management Guidebook.

Cited by 119 publications

References 0 publications

Requirement Risk Level Forecast Using Bayesian Networks Classifiers

Requirement Risk Level Forecast Using Bayesian Networks Classifiers

Exploring Risk Factors in ERP Maintenance Projects

Risk Management

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