Luis G. Martínez

Building Fuzzy Inference Systems with the Interval Type-2 Fuzzy Logic Toolbox

This paper presents the development and design of a graphical user interface and a command line programming Toolbox for construction, edition and simulation of Interval Type-2 Fuzzy Inference Systems. The Interval Type-2 Fuzzy Logic System Toolbox (IT2FLS), is an environment for interval type-2 fuzzy logic inference system development. Tools that cover the different phases of the fuzzy system design process, from the initial description phase, to the final implementation phase, constitute the Toolbox. The Toolbox’s best qualities are the capacity to develop complex systems and the flexibility that allows the user to extend the availability of functions for working with the use of type-2 fuzzy operators, linguistic variables, interval type-2 membership functions, defuzzification methods and the evaluation of Interval Type-2 Fuzzy Inference Systems.

Big five patterns for software engineering roles using an ANFIS learning approach with RAMSET

This paper proposes an ANFIS (Adaptive Network Based Fuzzy Inference System) Learning Approach where we have found patterns of personality types using Big Five Personality Tests for Software Engineering Roles in Software Development Project Teams as part of RAMSET (Role Assignment Methodology for Software Engineering Teams) methodology. An ANFIS model is applied to a set of role traits resulting from Big Five personality tests in our case studies obtaining a Takagi-Sugeno-Kang (TSK) Fuzzy Inference System (FIS) type model with rules that helps us recommend best suited roles for performing in software engineering teams.

Experiences in software engineering courses using psychometrics with RAMSET

Lately Programming Psychology has opened up a vast area of study, where human, social and psychological factors of the programmer are studied in different computational areas. His behavior and how to relate with others are important aspects that influence performance of a developing team. In our daily work in education we have an obligation of shaping human resources to build a society with professionals participating in companies and corporations dedicated to industrial, social and economic development. Thus in searching for strategies to shape human resources and improve these group corporations we propose RAMSET a Role Assignment Methodology for Software Engineering Teams where we acknowledge the importance of relating personality with team roles, using sociometric techniques and psychometrics to aid in forming high performing teams for software development projects.

Teaching mobile and wireless information systems development in engineering courses

MADEE (Mobile Application Development and Execution Environment) is a platform that supports the development of small and middle size mobile and wireless information systems for handheld devices. MADEE allows a student to develop applications faster and easier than using conventional development tools. This study presents the results and experience obtained using MADEE to support the introduction of mobile and wireless information systems development concepts in the context of computer engineering courses.

Using MatLab's fuzzy logic toolbox to create an application for RAMSET in software engineering courses

Role Assignment Methodology for Software Engineering Teams (RAMSET) methodology relates personality, abilities, and software roles for building Software Engineering Teams, applying sociometric, and psychometric techniques. This paper presents the results and experience of applying RAMSETs software supporting tool developed under a fuzzy approach. This software facilitates the role assignment decision making process, which results in a choice of role selection for individuals in working team projects. It has been applied in Software Engineering Courses of our Computer Engineering Program with great success giving students a practical experience in learning objectives, functions, responsibilities, and tasks of a member in a specific role during the Software Engineering Process.

Developing programming tools to reach a deeper understanding of advanced programming concepts

This article describes the experience and results obtained teaching non‐common Java features, in advanced undergraduate object‐oriented programming courses. The teaching approach proposed helps students to reach a deeper level of programming expertise, while accomplishing specific assignments that integrate a class framework that supports implementation of medium size client–server applications.

Experiences using PSP and XP to support teaching in undergraduate programming courses

Computer programming has a technological part and a creative part; it involves specific technical aspects of programming languages and creative aspects to find the best solutions for different problem domains. The programming learning process encompasses a group of different teacher–student techniques that are put into practice. These techniques have the object of learning a programming language to solve real problems; in this learning process we must include good software development practices of analysis and design so the novice programmer disciplines himself into developing quality software. To improve the learning programming process we use techniques and methods of software development adapting them to the context of courses in programs of the curricula. There are different methods to help us develop quality software; this article is a case study of using PSP (Personal Software Process) method and XP (eXtreme Programming) techniques on curriculas first programming course for engineering students, as support of the learning process of a programming language, and acquiring good software development habits.

Towards a Fuzzy Model for RAMSET: Role Assignment Methodology for Software Engineering Teams

Current studies related to performance and integration of Software Engineering teams, focus on efficiency boarding different factors such as team abilities, management, tools, methodologies, personality and roles. The present work is a follow up of RAMSET (Role Assignment Methodology for Software Engineering Teams) methodology that relates personality, abilities and software roles for integration of Software Engineering Teams, applying sociometric and psychometric techniques under a Fuzzy Approach due measurements’ subjective appreciation. A Fuzzy Model System is proposed to identify the best Role to be performed by a Software Engineer in Software Development Project Teams.

Towards a personality fuzzy model based on big five patterns for engineers using an ANFIS learning approach

This paper proposes an ANFIS (Adaptive Network Based Fuzzy Inference System) Learning Approach where we have found patterns of personality types using Big Five Personality Tests for students in Engineering Programs. An ANFIS model is applied to the personality traits of the Big Five Personality Model obtaining a Takagi-Sugeno-Kang (TSK) Fuzzy Inference System (FIS) type model with rules that are helping us identify Big Five Patterns for students that are studying Engineering Programs.

Decision making fuzzy model for software engineering role assignment based on fuzzy logic and big five patterns using RAMSET

The choice of role selection for individuals in working team software developing projects is the basis of all Software Developing Process for organizations to be competitive in the industry. This paper proposes a Decision Making Fuzzy Model for Software Engineering Role Assignment based on Fuzzy Logic with Big Five Patterns using our RAMSET methodology. This model facilitates the role assignment decision making process and is a first approach for support toward assisting any organization or human resource personnel to select adequate new candidates for software engineering roles or reassign personnel already working in the organization to their best suited role for satisfactory performance.