Luiz Fernando Capretz

Personality types in software engineering

Software engineering is forecast to be among the fastest growing employment field in the next decades. The purpose of this investigation is two-fold: Firstly, empirical studies on the personality types of software professionals are reviewed. Secondly, this work provides an up-to-date personality profile of software engineers according to the Myers-Briggs Type Indicator.

Making Sense of Software Development and Personality Types

Its common sense to state that the production of any software product involves a human element, at least to some extent. We all have different personality traits, and the way we perceive, plan, and execute any activity is influenced by these characteristics. Typically, software development is a product of teamwork, involving several people performing various tasks. The success and failure of software projects reveal the human factor as one of vital importance. Not everyone can excel at every task, thus better results are achieved if people with particular personality traits are assigned to different aspects of a project, especially the roles best suited to their ability. The authors mapped some opposing psychological traits, such as extroversion-introversion, sensing-intuition, thinking-feeling, and judging-perceiving, to the main stages of a software development life cycle. Consequently, they concluded that assigning a person with specific psychological characteristics to the stage of the software life cycle best suited for his or her traits increases the chances of a successful outcome for the project.

Improving the COCOMO model using a neuro-fuzzy approach

Accurate software development cost estimation is important for effective project management such as budgeting, project planning and control. So far, no model has proved to be successful at effectively and consistently predicting software development cost. A novel neuro-fuzzy Constructive Cost Model (COCOMO) is proposed for software cost estimation. This model carries some of the desirable features of a neuro-fuzzy approach, such as learning ability and good interpretability, while maintaining the merits of the COCOMO model. Unlike the standard neural network approach, the proposed model can be interpreted and validated by experts, and has good generalization capability. The model deals effectively with imprecise and uncertain input and enhances the reliability of software cost estimates. In addition, it allows input to have continuous rating values and linguistic values, thus avoiding the problem of similar projects having large different estimated costs. A detailed learning algorithm is also presented in this work. The validation using industry project data shows that the model greatly improves estimation accuracy in comparison with the well-known COCOMO model.

Towards an early software estimation using log-linear regression and a multilayer perceptron model

Software estimation is a tedious and daunting task in project management and software development. Software estimators are notorious in predicting software effort and they have been struggling in the past decades to provide new models to enhance software estimation. The most critical and crucial part of software estimation is when estimation is required in the early stages of the software life cycle where the problem to be solved has not yet been completely revealed. This paper presents a novel log-linear regression model based on the use case point model (UCP) to calculate the software effort based on use case diagrams. A fuzzy logic approach is used to calibrate the productivity factor in the regression model. Moreover, a multilayer perceptron (MLP) neural network model was developed to predict software effort based on the software size and team productivity. Experiments show that the proposed approach outperforms the original UCP model. Furthermore, a comparison between the MLP and log-linear regression models was conducted based on the size of the projects. Results demonstrate that the MLP model can surpass the regression model when small projects are used, but the log-linear regression model gives better results when estimating larger projects.

Component-based software development

Component-based software development (CBSD) strives to achieve a set of pre-built, standardized software components available to fit a specific architectural style for some application domain; the application is then assembled using these components. Component-based software reusability will be at the forefront of software development technology in the next few years. This paper describes a software life cycle that supports component-based development under an object-oriented framework. Development time versus software life cycle phases, which is an important assessment of the component-based development model put forward, is also mentioned.

A brief history of the object-oriented approach

Unlike other fads, the object-oriented paradigm is here to stay. The road towards an object-oriented approach is described and several object-oriented programming languages are reviewed. Since the object-oriented paradigm promised to revolutionize software development, in the 1990s, demand for object-oriented software systems increased dramatically; consequently, several methodologies have been proposed to support software development based on that paradigm. Also presented are a survey and a classification scheme for object oriented methodologies.

Forty years of research on personality in software engineering: A mapping study

In this article, we present a systematic mapping study of research on personality in software engineering. The goal is to plot the landscape of current published empirical and theoretical studies that deal with the role of personality in software engineering. We applied the systematic review method to search and select published articles, and to extract and synthesize data from the selected articles that reported studies about personality. Our search retrieved more than 19,000 articles, from which we selected 90 articles published between 1970 and 2010. Nearly 72% of the studies were published after 2002 and 83% of the studies reported empirical research findings. Data extracted from the 90 studies showed that education and pair programming were the most recurring research topics, and that MBTI was the most used test. Research related to pair programming, education, team effectiveness, software process allocation, software engineer personality characteristics, and individual performance concentrated over 88% of the studies, while team process, behavior and preferences, and leadership performance were the topics with the smallest number of studies. We conclude that the number of articles has grown in the last few years, but contradictory evidence was found that might have been caused by differences in context, research method, and versions of the tests used in the studies. While this raises a warning for practitioners that wish to use personality tests in practice, it shows several opportunities for the research community to improve and extend findings in this field.

Why do we need personality diversity in software engineering

Diversity of skills is good for society, it is also good in problem solving because different people see a problem from several pers-pectives, so diversity should be good for software engineering too. This study tackles a difficult to study aspect of software engineer-ing, that is, how to best associate personnel with the various tasks in a software project. The approach uses psychological types to determine who is best suited to particular development roles. The article has four main objectives: (1) to arouse awareness of human factors among software engineers; (2) to investigate how psycho-logical factors can contribute to their effectiveness at work; (3) to catalyze effort among software engineers leading towards a deeper understanding and broader applications of human factors in the light of the activities involving the engineering of software; and (4) to emphasize the important of skill diversity in the software engi-neering field. This article provides conceptual knowledge, reports findings, and presents both real and hypothesized beliefs from the software engineering community. Likewise, it is hoped that the article will motivate software engineers and psychologists to con-duct more research in the area of software psychology, so as to understand more profoundly the possibilities for increased effec-tiveness and fulfilment among software engineers

A neuro-fuzzy model for software cost estimation

A novel neuro-fuzzy constructive cost model (COCOMO) for software estimation is proposed. The model carries some of the desirable features of the neuro-fuzzy approach, such as learning ability and good interpretability, while maintaining the merits of the COCOMO model. Unlike the standard neural network approach, this model is easily validated by experts and capable of generalization. In addition, it allows inputs to be continuous-rating values and linguistic values, therefore avoiding the problem of similar projects having different estimated costs. Also presented in this paper is a detailed learning algorithm. The validation, using industry project data, shows that the model greatly improves the estimation accuracy in comparison with the well-known COCOMO model.

Estimating Software Effort Based on Use Case Point Model Using Sugeno Fuzzy Inference System

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.