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- Title
- VoIP Network Security and Forensic Models using Patterns.
- Creator
- Pelaez, Juan C., Fernandez, Eduardo B., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Voice over Internet Protocol (VoIP) networks is becoming the most popular telephony system in the world. However, studies of the security of VoIP networks are still in their infancy. VoIP devices and networks are commonly attacked, and it is therefore necessary to analyze the threats against the converged network and the techniques that exist today to stop or mitigate these attacks. We also need to understand what evidence can be obtained from the VoIP system after an attack has occurred....
Show moreVoice over Internet Protocol (VoIP) networks is becoming the most popular telephony system in the world. However, studies of the security of VoIP networks are still in their infancy. VoIP devices and networks are commonly attacked, and it is therefore necessary to analyze the threats against the converged network and the techniques that exist today to stop or mitigate these attacks. We also need to understand what evidence can be obtained from the VoIP system after an attack has occurred. Many of these attacks occur in similar ways in different contexts or environments. Generic solutions to these issues can be expressed as patterns. A pattern can be used to guide the design or simulation of VoIP systems as an abstract solution to a problem in this environment. Patterns have shown their value in developing good quality software and we expect that their application to VoIP will also prove valuable to build secure systems. This dissertation presents a variety of patterns (architectural, attack, forensic and security patterns). These patterns will help forensic analysts as well, as secure systems developers because they provide a systematic approach to structure the required information and help understand system weaknesses. The patterns will also allow us to specify, analyze and implement network security investigations for different architectures. The pattern system uses object-oriented modeling (Unified Modeling Language) as a way to formalize the information and dynamics of attacks and systems.
Show less - Date Issued
- 2007
- PURL
- http://purl.flvc.org/fau/fd/FA00012576
- Subject Headings
- Internet telephony--Security measures, Computer network protocols, Global system for mobile communications, Software engineering
- Format
- Document (PDF)
- Title
- Tree-based classification models for analyzing a very large software system.
- Creator
- Bullard, Lofton A., Florida Atlantic University, Khoshgoftaar, Taghi M.
- Abstract/Description
-
Software systems that control military radar systems must be highly reliable. A fault can compromise safety and security, and even cause death of military personnel. In this experiment we identify fault-prone software modules in a subsystem of a military radar system called the Joint Surveillance Target Attack Radar System, JSTARS. An earlier version was used in Operation Desert Storm to monitor ground movement. Product metrics were collected for different iterations of an operational...
Show moreSoftware systems that control military radar systems must be highly reliable. A fault can compromise safety and security, and even cause death of military personnel. In this experiment we identify fault-prone software modules in a subsystem of a military radar system called the Joint Surveillance Target Attack Radar System, JSTARS. An earlier version was used in Operation Desert Storm to monitor ground movement. Product metrics were collected for different iterations of an operational prototype of the subsystem over a period of approximately three years. We used these metrics to train a decision tree model and to fit a discriminant model to classify each module as fault-prone or not fault-prone. The algorithm used to generate the decision tree model was TREEDISC, developed by the SAS Institute. The decision tree model is compared to the discriminant model.
Show less - Date Issued
- 1996
- PURL
- http://purl.flvc.org/fcla/dt/15315
- Subject Headings
- Computer software--Quality control, Computer software--Reliability, Software engineering
- Format
- Document (PDF)
- Title
- Software reliability engineering: An evolutionary neural network approach.
- Creator
- Hochman, Robert., Florida Atlantic University, Khoshgoftaar, Taghi M.
- Abstract/Description
-
This thesis presents the results of an empirical investigation of the applicability of genetic algorithms to a real-world problem in software reliability--the fault-prone module identification problem. The solution developed is an effective hybrid of genetic algorithms and neural networks. This approach (ENNs) was found to be superior, in terms of time, effort, and confidence in the optimality of results, to the common practice of searching manually for the best-performing net. Comparisons...
Show moreThis thesis presents the results of an empirical investigation of the applicability of genetic algorithms to a real-world problem in software reliability--the fault-prone module identification problem. The solution developed is an effective hybrid of genetic algorithms and neural networks. This approach (ENNs) was found to be superior, in terms of time, effort, and confidence in the optimality of results, to the common practice of searching manually for the best-performing net. Comparisons were made to discriminant analysis. On fault-prone, not-fault-prone, and overall classification, the lower error proportions for ENNs were found to be statistically significant. The robustness of ENNs follows from their superior performance over many data configurations. Given these encouraging results, it is suggested that ENNs have potential value in other software reliability problem domains, where genetic algorithms have been largely ignored. For future research, several plans are outlined for enhancing ENNs with respect to accuracy and applicability.
Show less - Date Issued
- 1997
- PURL
- http://purl.flvc.org/fcla/dt/15474
- Subject Headings
- Neural networks (Computer science), Software engineering, Genetic algorithms
- Format
- Document (PDF)
- Title
- Software reliability engineering with genetic programming.
- Creator
- Liu, Yi., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Software reliability engineering plays a vital role in managing and controlling software quality. As an important method of software reliability engineering, software quality estimation modeling is useful in defining a cost-effective strategy to achieve a reliable software system. By predicting the faults in a software system, the software quality models can identify high-risk modules, and thus, these high-risk modules can be targeted for reliability enhancements. Strictly speaking, software...
Show moreSoftware reliability engineering plays a vital role in managing and controlling software quality. As an important method of software reliability engineering, software quality estimation modeling is useful in defining a cost-effective strategy to achieve a reliable software system. By predicting the faults in a software system, the software quality models can identify high-risk modules, and thus, these high-risk modules can be targeted for reliability enhancements. Strictly speaking, software quality modeling not only aims at lowering the misclassification rate, but also takes into account the costs of different misclassifications and the available resources of a project. As a new search-based algorithm, Genetic Programming (GP) can build a model without assuming the size, shape, or structure of a model. It can flexibly tailor the fitness functions to the objectives chosen by the customers. Moreover, it can optimize several objectives simultaneously in the modeling process, and thus, a set of multi-objective optimization solutions can be obtained. This research focuses on building software quality estimation models using GP. Several GP-based models of predicting the class membership of each software module and ranking the modules by a quality factor were proposed. The first model of categorizing the modules into fault-prone or not fault-prone was proposed by considering the distinguished features of the software quality classification task and GP. The second model provided quality-based ranking information for fault-prone modules. A decision tree-based software classification model was also proposed by considering accuracy and simplicity simultaneously. This new technique provides a new multi-objective optimization algorithm to build decision trees for real-world engineering problems, in which several trade-off objectives usually have to be taken into account at the same time. The fourth model was built to find multi-objective optimization solutions by considering both the expected cost of misclassification and available resources. Also, a new goal-oriented technique of building module-order models was proposed by directly optimizing several goals chosen by project analysts. The issues of GP , bloating and overfitting, were also addressed in our research. Data were collected from three industrial projects, and applied to validate the performance of the models. Results indicate that our proposed methods can achieve useful performance results. Moreover, some proposed methods can simultaneously optimize several different objectives of a software project management team.
Show less - Date Issued
- 2003
- PURL
- http://purl.flvc.org/fau/fd/FADT12047
- Subject Headings
- Computer software--Quality control, Genetic programming (Computer science), Software engineering
- Format
- Document (PDF)
- Title
- Software decomposition for multicore architectures.
- Creator
- Jain, Ankit., Florida Atlantic University, Shankar, Ravi
- Abstract/Description
-
Current multicore processors attempt to optimize consumer experience via task partitioning and concurrent execution of these (sub)tasks on the cores. Conversion of sequential code to parallel and concurrent code is neither easy, nor feasible with current methodologies. We have developed a mapping process that synergistically uses top-down and bottom-up methodologies. This process is amenable to automation. We use bottom-up analysis to determine decomposability and estimate computation and...
Show moreCurrent multicore processors attempt to optimize consumer experience via task partitioning and concurrent execution of these (sub)tasks on the cores. Conversion of sequential code to parallel and concurrent code is neither easy, nor feasible with current methodologies. We have developed a mapping process that synergistically uses top-down and bottom-up methodologies. This process is amenable to automation. We use bottom-up analysis to determine decomposability and estimate computation and communication metrics. The outcome is a set of proposals for software decomposition. We then build abstract concurrent models that map these decomposed (abstract) software modules onto candidate multicore architectures; this resolves concurrency issues. We then perform a system level simulation to estimate concurrency gain and/or cost, and QOS (Qualify-of-Service) metrics. Different architectural combinations yield different QOS metrics; the requisite system architecture may then be chosen. We applied this 'middle-out' methodology to optimally map a digital camera application onto a processor with four cores.
Show less - Date Issued
- 2006
- PURL
- http://purl.flvc.org/fcla/dt/13349
- Subject Headings
- Optimal designs (Statistics), Software architecture, Software engineering, Computer architecture, System design, Computer networks--Security measures
- Format
- Document (PDF)
- Title
- Rough Set-Based Software Quality Models and Quality of Data.
- Creator
- Bullard, Lofton A., Khoshgoftaar, Taghi M., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
In this dissertation we address two significant issues of concern. These are software quality modeling and data quality assessment. Software quality can be measured by software reliability. Reliability is often measured in terms of the time between system failures. A failure is caused by a fault which is a defect in the executable software product. The time between system failures depends both on the presence and the usage pattern of the software. Finding faulty components in the development...
Show moreIn this dissertation we address two significant issues of concern. These are software quality modeling and data quality assessment. Software quality can be measured by software reliability. Reliability is often measured in terms of the time between system failures. A failure is caused by a fault which is a defect in the executable software product. The time between system failures depends both on the presence and the usage pattern of the software. Finding faulty components in the development cycle of a software system can lead to a more reliable final system and will reduce development and maintenance costs. The issue of software quality is investigated by proposing a new approach, rule-based classification model (RBCM) that uses rough set theory to generate decision rules to predict software quality. The new model minimizes over-fitting by balancing the Type I and Type II niisclassiflcation error rates. We also propose a model selection technique for rule-based models called rulebased model selection (RBMS). The proposed rule-based model selection technique utilizes the complete and partial matching rule sets of candidate RBCMs to determine the model with the least amount of over-fitting. In the experiments that were performed, the RBCMs were effective at identifying faulty software modules, and the RBMS technique was able to identify RBCMs that minimized over-fitting. Good data quality is a critical component for building effective software quality models. We address the significance of the quality of data on the classification performance of learners by conducting a comprehensive comparative study. Several trends were observed in the experiments. Class and attribute had the greatest impact on the performance of learners when it occurred simultaneously in the data. Class noise had a significant impact on the performance of learners, while attribute noise had no impact when it occurred in less than 40% of the most significant independent attributes. Random Forest (RF100), a group of 100 decision trees, was the most, accurate and robust learner in all the experiments with noisy data.
Show less - Date Issued
- 2008
- PURL
- http://purl.flvc.org/fau/fd/FA00012567
- Subject Headings
- Computer software--Quality control, Computer software--Reliability, Software engineering, Computer arithmetic
- Format
- Document (PDF)
- Title
- A pattern-driven process for secure service-oriented applications.
- Creator
- Delessy, Nelly A., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
During the last few years, Service-Oriented Architecture (SOA) has been considered to be the new phase in the evolution of distributed enterprise applications. Even though there is a common acceptance of this concept, a real problem hinders the widespread use of SOA : A methodology to design and build secure service-oriented applications is needed. In this dissertation, we design a novel process to secure service-oriented applications. Our contribution is original not only because it applies...
Show moreDuring the last few years, Service-Oriented Architecture (SOA) has been considered to be the new phase in the evolution of distributed enterprise applications. Even though there is a common acceptance of this concept, a real problem hinders the widespread use of SOA : A methodology to design and build secure service-oriented applications is needed. In this dissertation, we design a novel process to secure service-oriented applications. Our contribution is original not only because it applies the MDA approach to the design of service-oriented applications but also because it allows their securing by dynamically applying security patterns throughout the whole process. Security patterns capture security knowledge and describe security mechanisms. In our process, we present a structured map of security patterns for SOA and web services and its corresponding catalog. At the different steps of a software lifecycle, the architect or designer needs to make some security decisions., An approach using a decision tree made of security pattern nodes is proposed to help making these choices. We show how to extract a decision tree from our map of security patterns. Model-Driven Architecture (MDA) is an approach which promotes the systematic use of models during a system's development lifecycle. In the dissertation we describe a chain of transformations necessary to obtain secure models of the service-oriented application. A main benefit of this process is that it decouples the application domain expertise from the security expertise that are both needed to build a secure application. Security knowledge is captured by pre-defined security patterns, their selection is rendered easier by using the decision trees and their application can be automated. A consequence is that the inclusion of security during the software development process becomes more convenient for the architects/designers., A second benefit is that the insertion of security is semi-automated and traceable. Thus, the process is flexible and can easily adapt to changing requirements. Given that SOA was developed in order to provide enterprises with modular, reusable and adaptable architectures, but that security was the principal factor that hindered its use, we believe that our process can act as an enabler for service-oriented applications.
Show less - Date Issued
- 2008
- PURL
- http://purl.flvc.org/FAU/58003
- Subject Headings
- Computer network architectures, Web servers, Management, Software engineering, Expert systems (Computer science)
- Format
- Document (PDF)
- Title
- Multivariate modeling of software engineering measures.
- Creator
- Lanning, David Lee., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
One goal of software engineers is to produce software products. An additional goal, that the software production must lead to profit, releases the power of the software product market. This market demands high quality products and tight cycles in the delivery of new and enhanced products. These market conditions motivate the search for engineering methods that help software producers ship products quicker, at lower cost, and with fewer defects. The control of software defects is key to...
Show moreOne goal of software engineers is to produce software products. An additional goal, that the software production must lead to profit, releases the power of the software product market. This market demands high quality products and tight cycles in the delivery of new and enhanced products. These market conditions motivate the search for engineering methods that help software producers ship products quicker, at lower cost, and with fewer defects. The control of software defects is key to meeting these market conditions. Thus, many software engineering tasks are concerned with software defects. This study considers two sources of variation in the distribution of software defects: software complexity and enhancement activity. Multivariate techniques treat defect activity, software complexity, and enhancement activity as related multivariate concepts. Applied techniques include principal components analysis, canonical correlation analysis, discriminant analysis, and multiple regression analysis. The objective of this study is to improve our understanding of software complexity and software enhancement activity as sources of variation in defect activity, and to apply this understanding to produce predictive and discriminant models useful during testing and maintenance tasks. These models serve to support critical software engineering decisions.
Show less - Date Issued
- 1994
- PURL
- http://purl.flvc.org/fcla/dt/12383
- Subject Headings
- Software engineering, Computer software--Testing, Computer software--Quality control
- Format
- Document (PDF)
- Title
- Modeling software quality with TREEDISC algorithm.
- Creator
- Yuan, Xiaojing, Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Software quality is crucial both to software makers and customers. However, in reality, improvement of quality and reduction of costs are often at odds. Software modeling can help us to detect fault-prone software modules based on software metrics, so that we can focus our limited resources on fewer modules and lower the cost but still achieve high quality. In the present study, a tree classification modeling technique---TREEDISC was applied to three case studies. Several major contributions...
Show moreSoftware quality is crucial both to software makers and customers. However, in reality, improvement of quality and reduction of costs are often at odds. Software modeling can help us to detect fault-prone software modules based on software metrics, so that we can focus our limited resources on fewer modules and lower the cost but still achieve high quality. In the present study, a tree classification modeling technique---TREEDISC was applied to three case studies. Several major contributions have been made. First, preprocessing of raw data was adopted to solve the computer memory problem and improve the models. Secondly, TREEDISC was thoroughly explored by examining the roles of important parameters in modeling. Thirdly, a generalized classification rule was introduced to balance misclassification rates and decrease type II error, which is considered more costly than type I error. Fourthly, certainty of classification was addressed. Fifthly, TREEDISC modeling was validated over multiple releases of software product.
Show less - Date Issued
- 1999
- PURL
- http://purl.flvc.org/fcla/dt/15718
- Subject Headings
- Computer software--Quality control, Computer simulation, Software engineering
- Format
- Document (PDF)
- Title
- Modeling software quality with classification trees using principal components analysis.
- Creator
- Shan, Ruqun., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Software quality models often have raw software metrics as the input data for predicting quality. Raw metrics are usually highly correlated with one another and thus may result in unstable models. Principal components analysis is a statistical method to improve model stability. This thesis presents a series of studies on a very large legacy telecommunication system. The system has significantly more than ten million lines of code written in a high level language similar to Pascal. Software...
Show moreSoftware quality models often have raw software metrics as the input data for predicting quality. Raw metrics are usually highly correlated with one another and thus may result in unstable models. Principal components analysis is a statistical method to improve model stability. This thesis presents a series of studies on a very large legacy telecommunication system. The system has significantly more than ten million lines of code written in a high level language similar to Pascal. Software quality models were developed to predict the class of each module either as fault-prone or as not fault-prone. We found out that the models based on principal components analysis were more robust than those based on raw metrics. We also found out that software process metrics can significantly improve the predictive accuracy of software quality models.
Show less - Date Issued
- 1999
- PURL
- http://purl.flvc.org/fcla/dt/15714
- Subject Headings
- Principal components analysis, Computer software--Quality control, Software engineering
- Format
- Document (PDF)
- Title
- Modeling fault-prone modules of subsystems.
- Creator
- Thaker, Vishal Kirit., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
In software engineering software quality has become a topic of major concern. It has also been recognized that the role of maintenance organization is to understand and estimate the cost of maintenance releases of software systems. Planning the next release so as to maximize the increase in functionality and the improvement in quality are essential to successful maintenance management. With the growing collection of software in organizations this cost is becoming substantial. In this research...
Show moreIn software engineering software quality has become a topic of major concern. It has also been recognized that the role of maintenance organization is to understand and estimate the cost of maintenance releases of software systems. Planning the next release so as to maximize the increase in functionality and the improvement in quality are essential to successful maintenance management. With the growing collection of software in organizations this cost is becoming substantial. In this research we have compared two software quality models. We tried to see whether a model built on entire system which predicts subsystem and a model built on subsystem which predicts the same subsystem has similar, better or worst classification results. We used Classification And Regression Tree algorithm (CART) to build classification models. A case study is based on a very large telecommunication system.
Show less - Date Issued
- 2000
- PURL
- http://purl.flvc.org/fcla/dt/12700
- Subject Headings
- Computer software--Quality control, Software engineering
- Format
- Document (PDF)
- Title
- Model-Driven Architecture and the Secure Systems Methodology.
- Creator
- Morrison, Patrick, Fernandez, Eduardo B., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
As a compamon and complement to the work being done to build a secure systems methodology, this thesis evaluates the use of Model-Driven Architecture (MDA) in support of the methodology's lifecycle. The development lifecycle illustrated follows the recommendations of this secure systems methodology, while using MDA models to represent requirements, analysis, design, and implementation information. In order to evaluate MDA, we analyze a well-understood distributed systems security problem,...
Show moreAs a compamon and complement to the work being done to build a secure systems methodology, this thesis evaluates the use of Model-Driven Architecture (MDA) in support of the methodology's lifecycle. The development lifecycle illustrated follows the recommendations of this secure systems methodology, while using MDA models to represent requirements, analysis, design, and implementation information. In order to evaluate MDA, we analyze a well-understood distributed systems security problem, remote access, as illustrated by the internet "secure shell" protocol, ssh. By observing the ability of MDA models and transformations to specify remote access in each lifecycle phase, MDA's strengths and weaknesses can be evaluated in this context. A further aim of this work is to extract concepts that can be contained in an MDA security metamodel for use in future projects.
Show less - Date Issued
- 2007
- PURL
- http://purl.flvc.org/fau/fd/FA00012537
- Subject Headings
- Expert systems (Computer science), Software engineering, Computer-aided design, Computer network architectures
- Format
- Document (PDF)
- Title
- INTEGRATING DESIGN THINKING MODEL AND ITEMS PRIORITIZATION DECISION SUPPORT SYSTEMS INTO REQUIREMENTS MANAGEMENT IN SCRUM.
- Creator
- Alhazmi, Alhejab Shawqi, Huang, Shihong, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
-
The Agile methodologies have attracted the software development industry's attention due to their capability to overcome the limitations of the traditional software development approaches and to cope with increasing complexity in system development. Scrum is one of the Agile software development processes broadly adopted by industry. Scrum promotes frequent customer involvement and incremental short releases. Despite its popular use, Scrum’s requirements engineering stage is inadequately...
Show moreThe Agile methodologies have attracted the software development industry's attention due to their capability to overcome the limitations of the traditional software development approaches and to cope with increasing complexity in system development. Scrum is one of the Agile software development processes broadly adopted by industry. Scrum promotes frequent customer involvement and incremental short releases. Despite its popular use, Scrum’s requirements engineering stage is inadequately defined which can lead to increase development time and cost, along with low quality or failure for the end products. This research shows the importance of activity planning of requirements engineering in improving the product quality, cost, and scheduling as well as it points out some drawbacks of Agile practices and available solutions. To improve the Scrum requirements engineering by overcoming its challenges in cases, such as providing a comprehensive understanding of the customer’s needs and addressing the effects of the challenges in other cases, such as frequent changes of requirements, the Design Thinking model is integrated into the Scrum framework in the context of requirements engineering management. The use of the Design Thinking model, in the context of requirements engineering management, is validated through an in-depth scientific study of the IBM Design Thinking framework. In addition, this research presents an Items Prioritization dEcision Support System (IPESS) which is a tool to assist the Product Owners for requirements prioritization. IPESS is built on information collected in the Design Thinking model. The IPESS tool adopts Analytic Hierarchy Process (AHP) technique and PageRank algorithm to deal with the specified factors and to achieve the optimal order for requirements items based on the prioritization score. IPESS is a flexible and comprehensive tool that focuses on different important aspects including customer satisfaction and product quality. The IPESS tool is validated through an experiment that was conducted in a real-world project
Show less - Date Issued
- 2021
- PURL
- http://purl.flvc.org/fau/fd/FA00013699
- Subject Headings
- Scrum (Computer software development), Computer software--Development--Management, Software engineering
- Format
- Document (PDF)
- Title
- Information theory and software measurement.
- Creator
- Allen, Edward B., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Development of reliable, high quality, software requires study and understanding at each step of the development process. A basic assumption in the field of software measurement is that metrics of internal software attributes somehow relate to the intrinsic difficulty in understanding a program. Measuring the information content of a program attempts to indirectly quantify the comprehension task. Information theory based software metrics are attractive because they quantify the amount of...
Show moreDevelopment of reliable, high quality, software requires study and understanding at each step of the development process. A basic assumption in the field of software measurement is that metrics of internal software attributes somehow relate to the intrinsic difficulty in understanding a program. Measuring the information content of a program attempts to indirectly quantify the comprehension task. Information theory based software metrics are attractive because they quantify the amount of information in a well defined framework. However, most information theory based metrics have been proposed with little reference to measurement theory fundamentals, and empirical validation of predictive quality models has been lacking. This dissertation proves that representative information theory based software metrics can be "meaningful" components of software quality models in the context of measurement theory. To this end, members of a major class of metrics are shown to be regular representations of Minimum Description Length or Variety of software attributes, and are interval scale. An empirical validation case study is presented that predicted faults in modules based on Operator Information. This metric is closely related to Harrison's Average Information Content Classification, which is the entropy of the operators. New general methods for calculating synthetic complexity at the system level and module level are presented, quantifying the joint information of an arbitrary set of primitive software measures. Since all kinds of information are not equally relevant to software quality factors, components of synthetic module complexity are also defined. Empirical case studies illustrate the potential usefulness of the proposed synthetic metrics. A metrics data base is often the key to a successful ongoing software metrics program. The contribution of any proposed metric is defined in terms of measured variation using information theory, irrespective of the metric's usefulness in quality models. This is of interest when full validation is not practical. Case studies illustrate the method.
Show less - Date Issued
- 1995
- PURL
- http://purl.flvc.org/fcla/dt/12412
- Subject Headings
- Software engineering, Computer software--Quality control, Information theory
- Format
- Document (PDF)
- Title
- An improved neural net-based approach for predicting software quality.
- Creator
- Guasti, Peter John., Florida Atlantic University, Khoshgoftaar, Taghi M., Pandya, Abhijit S.
- Abstract/Description
-
Accurately predicting the quality of software is a major problem in any software development project. Software engineers develop models that provide early estimates of quality metrics which allow them to take action against emerging quality problems. Most often the predictive models are based upon multiple regression analysis which become unstable when certain data assumptions are not met. Since neural networks require no data assumptions, they are more appropriate for predicting software...
Show moreAccurately predicting the quality of software is a major problem in any software development project. Software engineers develop models that provide early estimates of quality metrics which allow them to take action against emerging quality problems. Most often the predictive models are based upon multiple regression analysis which become unstable when certain data assumptions are not met. Since neural networks require no data assumptions, they are more appropriate for predicting software quality. This study proposes an improved neural network architecture that significantly outperforms multiple regression and other neural network attempts at modeling software quality. This is demonstrated by applying this approach to several large commercial software systems. After developing neural network models, we develop regression models on the same data. We find that the neural network models surpass the regression models in terms of predictive quality on the data sets considered.
Show less - Date Issued
- 1995
- PURL
- http://purl.flvc.org/fcla/dt/15134
- Subject Headings
- Neural networks (Computer science), Computer software--Development, Computer software--Quality control, Software engineering
- Format
- Document (PDF)
- Title
- Impact of best manufacturing engineering practices on software engineering practices.
- Creator
- Akhter, Shahina., Florida Atlantic University, Coulter, Neal S.
- Abstract/Description
-
This thesis involves original research in the area of semantic analysis of textual databases (content analysis). The main intention of this study is to examine how software engineering practices can benefit from the best manufacturing practices. There is a deliberate focus and emphasis on competitive effectiveness worldwide. The ultimate goal of the U.S. NAVY's Best Manufacturing Practices Program is to strengthen the U.S. industrial base and reduce the cost of defense systems by solving...
Show moreThis thesis involves original research in the area of semantic analysis of textual databases (content analysis). The main intention of this study is to examine how software engineering practices can benefit from the best manufacturing practices. There is a deliberate focus and emphasis on competitive effectiveness worldwide. The ultimate goal of the U.S. NAVY's Best Manufacturing Practices Program is to strengthen the U.S. industrial base and reduce the cost of defense systems by solving manufacturing problems and improving quality and reliability. Best manufacturing practices can assist software engineering practices in a way that when software companies use these practices they can: (1) Improve both software quality and staff productivity; (2) Determine the current status of the organization's software process; (3) Set goals for process improvement; (4) Create effective plans for reaching those goals; (5) Implement the major elements of the plans.
Show less - Date Issued
- 1997
- PURL
- http://purl.flvc.org/fcla/dt/15445
- Subject Headings
- Software engineering, Production engineering, Production management--Computer softwares
- Format
- Document (PDF)
- Title
- Fuzzy logic techniques for software reliability engineering.
- Creator
- Xu, Zhiwei., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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Modern people are becoming more and more dependent on computers in their daily lives. Most industries, from automobile, avionics, oil, and telecommunications to banking, stocks, and pharmaceuticals, require computers to function. As the tasks required become more complex, the complexity of computer software and hardware has increased dramatically. As a consequence, the possibility of failure increases. As the requirements for and dependence on computers increases, the possibility of crises...
Show moreModern people are becoming more and more dependent on computers in their daily lives. Most industries, from automobile, avionics, oil, and telecommunications to banking, stocks, and pharmaceuticals, require computers to function. As the tasks required become more complex, the complexity of computer software and hardware has increased dramatically. As a consequence, the possibility of failure increases. As the requirements for and dependence on computers increases, the possibility of crises caused by computer failures also increases. High reliability is an important attribute for almost any software system. Consequently, software developers are seeking ways to forecast and improve quality before release. Since many quality factors cannot be measured until after the software becomes operational, software quality models are developed to predict quality factors based on measurements collected earlier in the life cycle. Due to incomplete information in the early life cycle of software development, software quality models with fuzzy characteristics usually perform better because fuzzy concepts deal with phenomenon that is vague in nature. This study focuses on the usage of fuzzy logic in software reliability engineering. Discussing will include the fuzzy expert systems and the application of fuzzy expert systems in early risk assessment; introducing the interval prediction using fuzzy regression modeling; demonstrating fuzzy rule extraction for fuzzy classification and its usage in software quality models; demonstrating the fuzzy identification, including extraction of both rules and membership functions from fuzzy data and applying the technique to software project cost estimations. The following methodologies were considered: nonparametric discriminant analysis, Z-test and paired t-test, neural networks, fuzzy linear regression, fuzzy nonlinear regression, fuzzy classification with maximum matched method, fuzzy identification with fuzzy clustering, and fuzzy projection. Commercial software systems and the COCOMO database are used throughout this dissertation to demonstrate the usefulness of concepts and to validate new ideas.
Show less - Date Issued
- 2001
- PURL
- http://purl.flvc.org/fcla/dt/11948
- Subject Headings
- Software engineering, Fuzzy logic, Computer software--Quality control, Fuzzy systems
- Format
- Document (PDF)
- Title
- A framework for an icon-based software engineering environment.
- Creator
- Huang, Qinxi., Florida Atlantic University, Larrondo-Petrie, Maria M.
- Abstract/Description
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Current computer technologies and demands bring new challenges to the software engineering tools. This thesis includes a survey of software engineering environments, standards and technologies. It also examines the features needed to support rigorous object-oriented software development. The main contributions of the thesis are descriptions of innovative concepts and a high-level framework for a next-generation object-oriented software system development, management and maintenance...
Show moreCurrent computer technologies and demands bring new challenges to the software engineering tools. This thesis includes a survey of software engineering environments, standards and technologies. It also examines the features needed to support rigorous object-oriented software development. The main contributions of the thesis are descriptions of innovative concepts and a high-level framework for a next-generation object-oriented software system development, management and maintenance environment, called IconSEE++, an Icon-based Software Engineering Environment.
Show less - Date Issued
- 1998
- PURL
- http://purl.flvc.org/fcla/dt/15576
- Subject Headings
- Software engineering, Object-oriented methods (Computer science), Icon (Computer program language)
- Format
- Document (PDF)
- Title
- Developing accurate software quality models using a faster, easier, and cheaper method.
- Creator
- Lim, Linda., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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Managers of software development need to know which components of a system are fault-prone. If this can be determined early in the development cycle then resources can be more effectively allocated and significant costs can be reduced. Case-Based Reasoning (CBR) is a simple and efficient methodology for building software quality models that can provide early information to managers. Our research focuses on two case studies. The first study analyzes source files and classifies them as fault...
Show moreManagers of software development need to know which components of a system are fault-prone. If this can be determined early in the development cycle then resources can be more effectively allocated and significant costs can be reduced. Case-Based Reasoning (CBR) is a simple and efficient methodology for building software quality models that can provide early information to managers. Our research focuses on two case studies. The first study analyzes source files and classifies them as fault-prone or not fault-prone. It also predicts the number of faults in each file. The second study analyzes the fault removal process, and creates models that predict the outcome of software inspections.
Show less - Date Issued
- 2001
- PURL
- http://purl.flvc.org/fcla/dt/12746
- Subject Headings
- Computer software--Development, Computer software--Quality control, Software engineering
- Format
- Document (PDF)
- Title
- Detection of change-prone telecommunications software modules.
- Creator
- Weir, Ronald Eugene., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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Accurately classifying the quality of software is a major problem in any software development project. Software engineers develop models that provide early estimates of quality metrics which allow them to take actions against emerging quality problems. The use of a neural network as a tool to classify programs as a low, medium, or high risk for errors or change is explored using multiple software metrics as input. It is demonstrated that a neural network, trained using the back-propagation...
Show moreAccurately classifying the quality of software is a major problem in any software development project. Software engineers develop models that provide early estimates of quality metrics which allow them to take actions against emerging quality problems. The use of a neural network as a tool to classify programs as a low, medium, or high risk for errors or change is explored using multiple software metrics as input. It is demonstrated that a neural network, trained using the back-propagation supervised learning strategy, produced the desired mapping between the static software metrics and the software quality classes. The neural network classification methodology is compared to the discriminant analysis classification methodology in this experiment. The comparison is based on two and three class predictive models developed using variables resulting from principal component analysis of software metrics.
Show less - Date Issued
- 1995
- PURL
- http://purl.flvc.org/fcla/dt/15183
- Subject Headings
- Computer software--Evaluation, Software engineering, Neural networks (Computer science)
- Format
- Document (PDF)