The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Luiz Fernando Capretz - One of the best experts on this subject based on the ideXlab platform.
-
Software Effort Estimation from Use Case Diagrams Using Nonlinear Regression Analysis
2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2020Co-Authors: Ali Bou Nassif, Manar Abutalib, Luiz Fernando CapretzAbstract:Software effort estimation in the early stages of the Software Life Cycle is one of the most essential and daunting tasks for project managers. In this research, a new model based on nonlinear regression analysis is proposed to predict Software effort from use case diagrams. It is concluded that, where Software size is classified from small to very large, one linear or non-linear equation for effort estimation cannot be applied. Our model with three different non-linear regression equations can incorporate the different ranges in Software size.
-
Software effort estimation in the early stages of the Software Life Cycle using a cascade correlation neural network model
Software Engineering Artificial Intelligence Networking and Parallel Distributed Computing, 2012Co-Authors: Ali Bou Nassif, Luiz Fernando CapretzAbstract:Software cost estimation is a crucial element in project management. Failing to use a proper cost estimation method might lead to project failures. According to the Standish Chaos Report, 65% of Software projects are delivered over budget or after the delivery deadline. Conducting Software cost estimation in the early stages of the Software Life Cycle is important and this would be helpful to project managers to bid on projects. In this paper, we propose a novel model to predict Software effort from use case diagrams using a cascade correlation neural network approach. The proposed model was evaluated based on the MMER and PRED criteria using 214 industrial and 26 educational projects against a multiple linear regression model and the Use Case Point model. The results show that the proposed cascade correlation neural network can be used with promising results as an alternative approach to predict Software effort.
-
estimating Software effort based on use case point model using sugeno fuzzy inference system
International Conference on Tools with Artificial Intelligence, 2011Co-Authors: Ali Bou Nassif, Luiz Fernando CapretzAbstract:Software effort estimation is one of the most important tasks in Software engineering. Software developers conduct Software estimation in the early stages of the Software Life Cycle to derive the required cost and schedule for a project. In the requirements stage, where most Software estimation is conducted, the available information is usually imprecise or incomplete. In this paper, a new regression model is created for Software effort estimation based on use case point model. Furthermore, a Sugeno Fuzzy Inference System (FIS) approach is applied on this model to improve the estimation. Results show that an improvement of 11 % can be achieved in MMRE after applying the Sugeno fuzzy logic approach.
-
y a new component based Software Life Cycle model
Journal of Computer Science, 2005Co-Authors: Luiz Fernando CapretzAbstract:With the need to produce ever larger and more complex Software systems, the use of reusable components has become increasingly imperative. Of the many existing and proposed techniques for Software development, it seems clear that component-based Software development will be at the forefront of new approaches to the production of Software systems and holds the promise of substantially enhancing the Software production and maintenance process. Attempts to rationalize component-based development have to recognize that the construction of a Software system is a complex multifaceted activity that involves domain engineering, frame working, assembling, archiving and design of Software components. These activities, among others, are encompassed by a Software Life Cycle, named the Y model, put forward in this study. The Y model provides guidance for the major phases to be followed under its umbrella.
Laurie Williams - One of the best experts on this subject based on the ideXlab platform.
-
mapping the field of Software Life Cycle security metrics
Information & Software Technology, 2018Co-Authors: Patrick Morrison, David Moye, Rahul Pandita, Laurie WilliamsAbstract:Abstract Context: Practitioners establish a piece of Software’s security objectives during the Software development process. To support control and assessment, practitioners and researchers seek to measure security risks and mitigations during Software development projects. Metrics provide one means for assessing whether Software security objectives have been achieved. A catalog of security metrics for the Software development Life Cycle could assist practitioners in choosing appropriate metrics, and researchers in identifying opportunities for refinement of security measurement. Objective: The goal of this research is to support practitioner and researcher use of security measurement in the Software Life Cycle by cataloging security metrics presented in the literature, their validation, and the subjects they measure. Method: We conducted a systematic mapping study, beginning with 4818 papers and narrowing down to 71 papers reporting on 324 unique security metrics. For each metric, we identified the subject being measured, how the metric has been validated, and how the metric is used. We categorized the metrics, and give examples of metrics for each category. Results: In our data, 85% of security metrics have been proposed and evaluated solely by their authors, leaving room for replication and confirmation through field studies. Approximately 60% of the metrics have been empirically evaluated, by their authors or by others. The available metrics are weighted heavily toward the implementation and operations phases, with relatively few metrics for requirements, design, and testing phases of Software development. Some artifacts and processes remain unmeasured. Measured by phase, Testing received the least attention, with 1.5% of the metrics. Conclusions: At present, the primary application of security metrics to the Software development Life Cycle in the literature is to study the relationship between properties of source code and reported vulnerabilities. The most-cited and most used metric, vulnerability count, has multiple definitions and operationalizations. We suggest that researchers must check vulnerability count definitions when making comparisons between papers. In addition to refining vulnerability measurement, we see research opportunities for greater attention to metrics for the requirement, design, and testing phases of development. We conjecture from our data that the field of Software Life Cycle security metrics has yet to converge on an accepted set of metrics.
Mario Piattini - One of the best experts on this subject based on the ideXlab platform.
-
risk management in the Software Life Cycle a systematic literature review
Computer Standards & Interfaces, 2020Co-Authors: Jhon Masso, Francisco J Pino, Cesar Pardo, Felix Garcia, Mario PiattiniAbstract:Abstract Risk management (RM) plays a key role in project management, as it allows identification and prompt management of threats that may arise during project execution. Furthermore, project management within the Software industry is evolving rapidly nowadays, a fact that implies new challenges, because the emergence and use of fresh approaches has brought a greater degree of complexity to the RM process. The objective of this paper is to carry out a systematic literature review (SLR) in the field of Software risk, in an attempt to characterize and present the state of the art of this field, identifying gaps and opportunities for further research. From the analysis of the results of this SLR it could be observed that interest on the part of the scientific community has turned away from the definition of research work that addressed an integrated risk management process, to pay attention to work that concentrates on specific activities of this process. It was also possible to see that there is a clear lack of scientific rigour as regards the process of validation in the different studies, and a deficiency in the use of standards or of de facto models to define these.
-
psecgcm process for the development of secure grid computing based systems with mobile devices
Availability Reliability and Security, 2008Co-Authors: David G Rosado, E M Fernandez, Javier Lopez, Mario PiattiniAbstract:Mobile Grid, in relevance to both Grid and Mobile Computing, is a full inheritor of Grid with the additional feature of supporting mobile users and resources in a seamless, transparent, secure and efficient way. Security of these systems, due to their distributed and open nature, receives great interest. A formal approach to security in the Software Life Cycle is essential to protect corporate resources. However, little thought has been given to this aspect of Software development. Due to its criticality, security should be integrated as a formal approach in the Software Life Cycle. A methodology of development for secure mobile Grid computing based systems is defined, that is to say, an engineering process that defines the steps to follow so that starting from the necessities to solve, we can design and construct a secure Grid system with support for mobile devices that is able to solve and cover these necessities.
-
no redundant metrics for uml class diagram structural complexity
Conference on Advanced Information Systems Engineering, 2003Co-Authors: Ma Esperanza Manso, Marcela Genero, Mario PiattiniAbstract:In Software engineering it is widely acknowledged that the usage of metrics at the initial phases of the object oriented Software Life Cycle can help designers to make better decisions and to predict external quality attributes, such as maintainability. Following this idea we have carried out three controlled experiments to ascertain if any correlation exists between the structural complexity and the size of UML class diagrams and their maintainability. We used 8 metrics for measuring the structural complexity of class diagrams due to the usage of UML relationships, and 3 metrics to measure their size. With the aim of determining which of these metrics are really relevant to be used as class diagrams maintainability indicators, we present in this work a study based on Principal Component Analysis. The obtained results show that the metrics related to associations, aggregations, generalizations and dependencies, are the most relevant whilst those related to size seem to be redundant.
Georg Buchgeher - One of the best experts on this subject based on the ideXlab platform.
-
towards supporting the Software architecture Life Cycle
Journal of Systems and Software, 2012Co-Authors: Rainer Weinreich, Georg BuchgeherAbstract:Software architecture is a central element during the whole Software Life Cycle. Among other things, Software architecture is used for communication and documentation, for design, for reasoning about important system properties, and as a blueprint for system implementation. This is expressed by the Software architecture Life Cycle, which emphasizes architecture-related activities like architecture design, implementation, and analysis in the context of a Software Life Cycle. While individual activities of the Software architecture Life Cycle are supported very well, a seamless approach for supporting the whole Life Cycle is still missing. Such an approach requires the integration of disparate information, artifacts, and tools into one consistent information model and environment. In this article we present such an approach. It is based on a semi-formal architecture model, which is used in all activities of the architecture Life Cycle, and on a set of extensible and integrated tools supporting these activities. Such an integrated approach provides several benefits. Potentially redundant activities like the creation of multiple architecture descriptions are avoided, the captured information is always consistent and up-to-date, extensive tracing between different information is possible, and interleaving activities in incremental development and design are supported.
Patrick Morrison - One of the best experts on this subject based on the ideXlab platform.
-
mapping the field of Software Life Cycle security metrics
Information & Software Technology, 2018Co-Authors: Patrick Morrison, David Moye, Rahul Pandita, Laurie WilliamsAbstract:Abstract Context: Practitioners establish a piece of Software’s security objectives during the Software development process. To support control and assessment, practitioners and researchers seek to measure security risks and mitigations during Software development projects. Metrics provide one means for assessing whether Software security objectives have been achieved. A catalog of security metrics for the Software development Life Cycle could assist practitioners in choosing appropriate metrics, and researchers in identifying opportunities for refinement of security measurement. Objective: The goal of this research is to support practitioner and researcher use of security measurement in the Software Life Cycle by cataloging security metrics presented in the literature, their validation, and the subjects they measure. Method: We conducted a systematic mapping study, beginning with 4818 papers and narrowing down to 71 papers reporting on 324 unique security metrics. For each metric, we identified the subject being measured, how the metric has been validated, and how the metric is used. We categorized the metrics, and give examples of metrics for each category. Results: In our data, 85% of security metrics have been proposed and evaluated solely by their authors, leaving room for replication and confirmation through field studies. Approximately 60% of the metrics have been empirically evaluated, by their authors or by others. The available metrics are weighted heavily toward the implementation and operations phases, with relatively few metrics for requirements, design, and testing phases of Software development. Some artifacts and processes remain unmeasured. Measured by phase, Testing received the least attention, with 1.5% of the metrics. Conclusions: At present, the primary application of security metrics to the Software development Life Cycle in the literature is to study the relationship between properties of source code and reported vulnerabilities. The most-cited and most used metric, vulnerability count, has multiple definitions and operationalizations. We suggest that researchers must check vulnerability count definitions when making comparisons between papers. In addition to refining vulnerability measurement, we see research opportunities for greater attention to metrics for the requirement, design, and testing phases of development. We conjecture from our data that the field of Software Life Cycle security metrics has yet to converge on an accepted set of metrics.
