arXiv subjects

Luiz Fernando Capretz

Publications and source records attributed to Luiz Fernando Capretz.

At least 109 records · Page 6Linked to original sources

arXiv2015

Extending UML-RT for Control System Modeling

There is a growing interest in adopting object technologies for the development of real-time control systems. Several commercial tools, currently available, provide object-oriented modeling and design support for real-time control systems. While these products provide many useful facilities, such as visualization tools and automatic code generation, they are all weak in addressing the central characteristic of real-time control systems design, i.e., providing support for a designer to reason about timeliness properties. We believe an approach that integrates the advancements in both object modeling and design methods and real-time scheduling theory is the key to successful use of object technology for real-time software. Surprisingly several past approaches to integrate the two either restrict the object models, or do not allow sophisticated schedulability analysis techniques. This study shows how schedulability analysis can be integrated with UML for Real-Time (UML-RT) to deal with timing properties in real time control systems. More specifically, we develop the schedulability and feasibility analysis modeling for the external messages that may suffer release jitter due to being dispatched by a tick driven scheduler in real-time control system and we also develop the scheduliablity modeling for sporadic activities, where messages arrive sporadically then execute periodically for some bounded time. This method can be used to cope with timing constraints in realistic and complex real-time control systems. Using this method, a designer can quickly evaluate the impact of various implementation decisions on schedulability. In conjunction with automatic code-generation, we believe that this will greatly streamline the design and development of real-time control systems software.

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arXiv2015

Calibrating Function Points Using Neuro-Fuzzy Technique

The concepts of calibrating Function Points are discussed, whose aims are to fit specific software application, to reflect software industry trend, and to improve cost estimation. Neuro-Fuzzy is a technique which incorporates the learning ability from neural network and the ability to capture human knowledge from fuzzy logic. The empirical validation using ISBSG data repository Release 8 shows a 22% improvement in software effort estimation after calibration using Neuro-Fuzzy technique.

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arXiv2015

A Neuro-Fuzzy Model with SEER-SEM for Software Effort Estimation

Software effort estimation is a critical part of software engineering. Although many techniques and algorithmic models have been developed and implemented by practitioners, accurate software effort prediction is still a challenging endeavor. In order to address this issue, a novel soft computing framework was previously developed. Our study utilizes this novel framework to develop an approach combining the neuro-fuzzy technique with the System Evaluation and Estimation of Resource - Software Estimation Model (SEER-SEM). Moreover, our study assesses the performance of the proposed model by designing and conducting evaluation with published industrial project data. After analyzing the performance of our model in comparison to the SEER-SEM effort estimation model alone, the proposed model demonstrates the ability of improving the estimation accuracy, especially in its ability to reduce the large Mean Relative Error (MRE). Furthermore, the results of this research indicate that the general neuro-fuzzy framework can work with various algorithmic models for improving the performance of software effort estimation.

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arXiv2015

An Intelligent Approach to Software Cost Prediction

Good software cost prediction is important for effective project management such as budgeting, project planning and control. In this paper, we present an intelligent approach to software cost prediction. By integrating the neuro-fuzzy technique with the well-accepted COCOMO model, our approach can make the best use of both expert knowledge and historical project data. Its major advantages include learning ability, good interpretability, and robustness to imprecise and uncertain inputs. The validation using industry project data shows that the model greatly improves prediction accuracy in comparison with the COCOMO model.

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arXiv2015

Neuro-Fuzzy Algorithmic (NFA) Models and Tools for Estimation

Accurate estimation such as cost estimation, quality estimation and risk analysis is a major issue in management. We propose a patent pending soft computing framework to tackle this challenging problem. Our generic framework is independent of the nature and type of estimation. It consists of neural network, fuzzy logic, and an algorithmic estimation model. We made use of the Constructive Cost Model (COCOMO), Analysis of Variance (ANOVA), and Function Point Analysis as the algorithmic models and validated the accuracy of the Neuro-Fuzzy Algorithmic (NFA) Model in software cost estimation using industrial project data. Our model produces more accurate estimation than using an algorithmic model alone. We also discuss the prototypes of our tools that implement the NFA Model. We conclude with our roadmap and direction to enrich the model in tackling different estimation challenges.

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arXiv2015

Media Usage Survey: Overall Comparison of Faculty and Students

Recent developments in the use of technologies in education have provided unique opportunities for teaching and learning. This paper describes the results of a survey conducted at Western University (Canada) in 2013, regarding the use of media by students and instructors. The results of this study support the assumption that the media usage of students and instructors include a mixture of traditional and new media. The main traditional media continue to be important, and some new media have emerged as seemingly on equal footing or even more important than the traditional forms of media. Some new media that have recently been in the public spotlight do not seem to be as important as expected. These new media may still be emerging but it is not possible to know their ultimate importance at this point. There was some variation in media usage across different Faculties but perhaps not as much variation as might have been expected.

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arXiv2015

How Students Use Media: A Comparison across Faculties

The pervasiveness of online information services has led to substantial changes in higher education including changes in faculty members teaching methods and students study habits. This article presents the results of a survey about media use for teaching and learning conducted at a large Canadian university and highlights trends in the use of new and traditional media across university Faculties. The results of this study support the assumption that student media usage includes a mixture of traditional and new media.

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arXiv2015

Do Personality Profiles Differ in the Pakistani Software Industry and Academia - A Case Study

Effects of personality profiles and human factors in software engineering (SE) have been studied from different perspectives, such as: software life cycle, team performance, software quality attributes, and so on. This study intends to compare personality profiles of software engineers in academia and industry. In this survey we have collected personality profiles of software engineers from academia and the local industry in Pakistan. According to the Myers- Briggs Type Indicator (MBTI) instrument, the most prominent personality type among Pakistani academicians is a combination of Introversion, Sensing, Thinking, and Judging (ISTJ). However the most dominant personality type among software engineers in the Pakistani software industry is a combination of Extroversion, Sensing, Thinking, and Judging (ESTJ). The results of study establish that software engineers working in industry are mostly Extroverts as compared to those in academia who tend to be Introverts. The dimensions: Sensing, Thinking, and Judging (STJ), however, remain common in the dominant personality types of software engineers, both in Pakistani software industry and academia.

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arXiv2015

Do Open Source Software Developers Listen to Their Users?

In application software, the satisfaction of target users makes the software more acceptable. Open Source Software (OSS) systems have neither the physical nor the commercial boundaries of proprietary software, thus users from all over the world can interact with them. This free access is advantageous, as increasing numbers of users are able to access OSS; there are more chances of improvement. This study examines the way users feedback is handled by OSS developers. In our survey, we have also inquired whether OSS developers consult professional usability experts to improve their projects. According to the results, majority of OSS developers neither consider usability as their top priority nor do they consult usability experts.

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arXiv2015

Personality Dimensions and Temperaments of Engineering Professors and Students - A Survey

This research work aims to study personality profiles and temperaments of Pakistani software engineering professors and students. In this survey we have collected personality profiles of 18 professors and 92 software engineering students. According to the Myers-Briggs Type Indicator (MBTI) instrument, the most prominent personality type among professors as well as among students is a combination of Introversion, Sensing, Thinking, and Judging (ISTJ). The study shows ITs (Introverts and Thinking) and IJs (Introverts and Judging) are the leading temperaments among the professors. About the students data, the results of the study indicate SJs (Sensing and Judging) and ISs (Introverts and Sensing) as the dominant temperaments.

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arXiv2015

Exploratory Analysis of Quality Practices in Open Source Domain

Software quality assurance has been a heated topic for several decades, but relatively few analyses were performed on open source software (OSS). As OSS has become very popular in our daily life, many researchers have been keen on the quality practices in this area. Although quality management presents distinct patterns compared with those in closed-source software development, some widely used OSS products have been implemented. Therefore, quality assurance of OSS projects has attracted increased research focuses. In this paper, a survey is conducted to reveal the general quality practices in open source communities. Exploratory analysis has been carried out to disclose those quality related activities. The results are compared with those from closed-source environments and the distinguished features of the quality assurance in OSS projects have been confirmed. Moreover, this study suggests potential directions for OSS developers to follow.

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arXiv2015

Improving Software Effort Estimation Using Neuro-Fuzzy Model with SEER-SEM

The aims of our research are to evaluate the prediction performance of the proposed neuro-fuzzy model with System Evaluation and Estimation of Resource Software Estimation Model (SEER-SEM) in software estimation practices and to apply the proposed architecture that combines the neuro-fuzzy technique with different algorithmic models. In this paper, an approach combining the neuro-fuzzy technique and the SEER-SEM effort estimation algorithm is described. This proposed model possesses positive characteristics such as learning ability, decreased sensitivity, effective generalization, and knowledge integration for introducing the neuro-fuzzy technique. Moreover, continuous rating values and linguistic values can be inputs of the proposed model for avoiding the large estimation deviation among similar projects. The performance of the proposed model is accessed by designing and conducting evaluation with published projects and industrial data. The evaluation results indicate that estimation with our proposed neuro-fuzzy model containing SEER-SEM is improved in comparison with the estimation results that only use SEER-SEM algorithm. At the same time, the results of this research also demonstrate that the general neuro-fuzzy framework can function with various algorithmic models for improving the performance of software effort estimation.

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arXiv2015

Building an OSS Quality Estimation Model with CATREG

Open Source Software (OSS) has been a popular form in software development. In this paper, we use statistical approaches to derive OSS quality estimation models. Our objective is to build estimation models for the number of defects with metrics at project levels. First CATREG (Categorical regression with optimal scaling) is used to obtain quantifications of the qualitative variables. Then the independent variables are validated using the stepwise linear regression. The process is repeated to acquire optimal quantifications and final regression formula. This modeling process is performed based on data from the OSS communities and is proved to be practically valuable.

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arXiv2015

A Neuro-Fuzzy Model for Function Point Calibration

The need to update the calibration of Function Point (FP) complexity weights is discussed, whose aims are to fit specific software application, to reflect software industry trend, and to improve cost estimation. Neuro-Fuzzy is a technique that incorporates the learning ability from neural network and the ability to capture human knowledge from fuzzy logic. The empirical validation using ISBSG data repository Release 8 shows a 22% improvement in software effort estimation after calibration using Neuro-Fuzzy technique.

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arXiv2015

A Decision Support Tool for Assessing the Maturity of Software Product Line Process

The software product line aims at the effective utilization of software assets, reducing the time required to deliver a product, improving the quality, and decreasing the cost of software products. Organizations trying to incorporate this concept require an approach to assess the current maturity level of the software product line process in order to make management decisions. A decision support tool for assessing the maturity of the software product line process is developed to implement the fuzzy logic approach, which handles the imprecise and uncertain nature of software process variables. The proposed tool can be used to assess the process maturity level of a software product line. Such knowledge will enable an organization to make crucial management decisions. Four case studies were conducted to validate the tool, and the results of the studies show that the software product line decision support tool provides a direct mechanism to evaluate the current software product line process maturity level within an organization.

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arXiv2015

Clues on Software Engineers Learning Styles

The Myers-Briggs Type Indicator (MBTI) has proved to be a useful instrument for understanding student learning preferences and has enable comparisons of the learning preferences for various personality types. Regarding learning styles, there is no one best combination of characteristics, since each preference has its own advantages and disadvantages. Therefore, it is a fallacy to think that professors can devise a single teaching technique that would always appeal to all students at the same time. The ideas presented in this paper have been taken into account in two 4th year courses, named Software Requirements and Software Design in which the students develop their capstone projects. The results of this investigation may help college instructors to understanding the preferred leaning style of software engineers.

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arXiv2015

A Framework for Process Assessment of Software Product Line

Software product line has emerged as an attractive phenomenon within organizations dealing with software development process. It involves assembly of products from existing core assets, commonly known as components, and continuous growth in the core assets as production proceeds. Organizations trying to incorporate the concept of software product line to reduce development time and cost require certain rules to be followed for successful development and management, they also require a direct procedure to evaluate the current maturity level of the process. In this work certain rules for developing and managing a software product line are put forward. Additionally, a fuzzy logic based software product line process assessment tool (SPLPAT) has been designed and implemented on the basis of developed rules for software product line process assessment. SPLPAT can be used to assess the process maturity level of software product line, and it provides an opportunity to handle imprecision and uncertainty present in software process variables. Four case studies were conducted to validate the framework, and results show that SPLPAT provides a direct mechanism to evaluate current software product line process maturity level within an organization. The results of the developed software product line process assessment approach were compared with the existing CMM-level of the organization in order to evaluate the reliability of the presented approach and to find out how effectively an organization can execute software product line process when it has already achieved a certain CMM level.

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arXiv2015

C# Traceability System

Traceability information is a valuable asset that software development teams can leverage to minimise their risk during production and maintenance of software projects. When maintainers are added to a software project post-production, they have to learn the system from scratch and understand its dynamics before they can begin making appropriate modifications to the source code. The system outlined in this paper extracts traceability information directly from the source code of C# projects, and presents it in such a way that it can be easily used to understand the logic and validate changes to the system.

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