Integrating Empirical Software Engineering practice in South America

Empirical software engineering (ESE) is a sub-domain of software engineering which focuses on experiments on software systems. Its main interest lies on devising software experiments, on collecting data from these experiments, and on formulating laws and theories from these data. In South America there is a group of researchers that are involved in this topic and have interests in common. This project propose the integration of their work in order to reply the experimentation done in different countries contributing to the increase of empirical software engineering body of knowledge. At this time several publications have been done with the collaboration of master students.Eje: Ingeniería de SoftwareRed de Universidades con Carreras en Informática (RedUNCI

Integrating Empirical Software Engineering practice in South America

Empirical software engineering (ESE) is a sub-domain of software engineering which focuses on experiments on software systems. Its main interest lies on devising software experiments, on collecting data from these experiments, and on formulating laws and theories from these data. In South America there is a group of researchers that are involved in this topic and have interests in common. This project propose the integration of their work in order to reply the experimentation done in different countries contributing to the increase of empirical software engineering body of knowledge. At this time several publications have been done with the collaboration of master students.Eje: Ingeniería de SoftwareRed de Universidades con Carreras en Informática (RedUNCI

Using Functional Complexity Measures in Software Development Effort Estimation

Several definitions of measures that aim at representing the size of software requirements are currently available. These measures have gained a quite relevant role, since they are one of the few types of objective measures upon which effort estimation can be based. However, traditional Functional Size Measures do not take into account the amount and complexity of elaboration required, concentrating instead on the amount of data accessed or moved. This is a problem since the amount and complexity of the required data elaboration affect the implementation effort, but are not adequately represented by the current size measures, including the standardized ones. Recently, a few approaches to measuring aspects of user requirements that are supposed to be related with functional complexity and/or data elaboration have been proposed by researchers. In this paper, we take into consideration some of these proposed measures and compare them with respect to their ability to predict the development effort, especially when used in combination with measures of functional size. A few methods for estimating software development effort \u2013both based on model building and on analogy\u2013 are experimented with, using different types of functional size and elaboration complexity measures. All the most significant models obtained were based on a notion of computation density that is based on the number of computation flows in functional processes. When using estimation by analogy, considering functional complexity in the selection of analogue projects improved accuracy in all the evaluated cases. In conclusion, it appears that functional complexity is a factor that affects development effort; accordingly, whatever method is used for effort estimation, it is advisable to take functional complexity into due consideration

An Empirical Evaluation of Effort Prediction Models Based on Functional Size Measures

Software development effort estimation is among the most interesting issues for project managers, since reliable estimates are at the base of good planning and project control. Several different techniques have been proposed for effort estimation, and practitioners need evidence, based on which they can choose accurate estimation methods. The work reported here aims at evaluating the accuracy of software development effort estimates that can be obtained via popular techniques, such as those using regression models and those based on analogy. The functional size and the development effort of twenty software development projects were measured, and the resulting dataset was used to derive effort estimation models and evaluate their accuracy. Our data analysis shows that estimation based on the closest analogues provides better results for most models, but very bad estimates in a few cases. To mitigate this behavior, the correction of regression toward the mean proved effective. According to the results of our analysis, it is advisable that regression to the mean correction is used when the estimates are based on closest analogues. Once corrected, the accuracy of analogy-based estimation is not substantially different from the accuracy of regression based models

Integrating Empirical Software Engineering practice in South America

Empirical software engineering (ESE) is a sub-domain of software engineering which focuses on experiments on software systems. Its main interest lies on devising software experiments, on collecting data from these experiments, and on formulating laws and theories from these data. In South America there is a group of researchers that are involved in this topic and have interests in common. This project propose the integration of their work in order to reply the experimentation done in different countries contributing to the increase of empirical software engineering body of knowledge. At this time several publications have been done with the collaboration of master students.Eje: Ingeniería de SoftwareRed de Universidades con Carreras en Informática (RedUNCI

Towards a simplified definition of Function Points

3Background. COSMIC Function Points and traditional Function Points (i.e., IFPUG Function points and more recent variation of Function Points, such as NESMA and FISMA) are probably the best known and most widely used Functional Size Measurement methods. The relationship between the two kinds of Function Points still needs to be investigated. If traditional Function Points could be accurately converted into COSMIC Function Points and vice versa, then, by measuring one kind of Function Points, one would be able to obtain the other kind of Function Points, and one might measure one or the other kind interchangeably. Several studies have been performed to evaluate whether a correlation or a conversion function between the two measures exists. Specifically, it has been suggested that the relationship between traditional Function Points and COSMIC Function Points may not be linear, i.e., the value of COSMIC Function Points seems to increase more than proportionally to an increase of traditional Function Points. Objective. This paper aims at verifying this hypothesis using available datasets that collect both FP and CFP size measures. Method. Rigorous statistical analysis techniques are used, specifically Piecewise Linear Regression, whose applicability conditions are systematically checked. The Piecewise Linear Regression curve is a series of interconnected segments. In this paper, we focused on Piecewise Linear Regression curves composed of two segments. We also used Linear and Parabolic Regressions, to check if and to what extent Piecewise Linear Regression may provide an advantage over other regression techniques. We used two categories of regression techniques: Ordinary Least Squares regression is based on the usual minimization of the sum of squares of the residuals, or, equivalently, on the minimization of the average squared residual; Least Median of Squares regression is a robust regression technique that is based on the minimization of the median squared residual. Using a robust regression technique helps filter out the excessive influence of outliers. Results. It appears that the analysis of the relationship between traditional Function Points and COSMIC Function Points based on the aforementioned data analysis techniques yields valid significant models. However, different results for the various available datasets are achieved. In practice, we obtained statistically valid linear, piecewise linear, and non-linear conversion formulas for several datasets. In general, none of these is better than the others in a statistically significant manner. Conclusions. Practitioners interested in the conversion of FP measures into CFP (or vice versa) cannot just pick a conversion model and be sure that it will yield the best results. All the regression models we tested provide good results with some datasets. In practice, all the models described in the paper –in particular, both linear and non-linear ones– should be evaluated in order to identify the ones that are best suited for the specific dataset at hand.openLavazza, L.; Morasca, S.; Robiolo, G.Lavazza, LUIGI ANTONIO; Morasca, Sandro; Robiolo, G

Method of Estimating Costs of a Software Web Product

The costing of a product is a key factor in the marketing process. Its proper calculation can attract customers, which will ensure a company’s life and its business expansion. These considerations have driven the Centre for the Study of software Engineering at Universidad de la Frontera (CEIS-UFRO) to develop a method to define the cost of a web software product, based on use cases and productivity. This method is adaptable to the particular characteristics of any development process, any development team, any product and any company.This article describes the method and performs an initial validation by describing a quasi-experiment designed for Web applications developed by groups of three to five people. We have proved that: a. the method may be reproduced,b. effort estimation is sensitive to the definition of productivity, c. the subjectivity introduced by the estimators does not invalidate the method. For a complete validation of this method, different web products and a larger number of estimatorswith different levels of experience should be incorporated in a future replication.Sociedad Argentina de Informática e Investigación Operativ

Estimación de proyectos de software pequeños basada en el juicio de expertos: un caso de estudio

El Juicio de Expertos es el método de estimación de proyectos de software más comúnmente utilizado entre los desarrolladores. En la actualidad existen pocos estudios empíricos relativos a la estimación de esfuerzo de proyectos de software. En este trabajo presentamos un caso de estudio desarrollado en una empresa internacional donde surge la necesidad de mejorar la estimación de proyectos pequeños de software. Con este motivo se formaliza la definición de los requerimientos y se aplica un método de estimación basado en el juicio de expertos. El resultado obtenido puso en evidencia la necesidad de considerar una contingencia del 39% para evitar errores de más del 10% en las estimaciones.Sociedad Argentina de Informática e Investigación Operativa (SADIO

PQEMw, applying weighted sums to software quality measurement

Product owners and quality leaders need to understand the quality level of a software product through its life cycle in order to achieve appropriate decision making to remain in the same iteration or to continue to the next one. Product Quality Evaluation Method (PQEM) evaluates and monitors the quality of a software product within each iteration. The present article introduces the extension of the method, PQEMwi to include the definition and calculation of weights for each quality characteristic measured. PQEMwi allows the stakeholder to set their point of view and importance of each quality characteristic, and we carried out an illustrative example of two apps, comparing the decisionmaking of the weights selection and the results of applying PQEMwi.Sociedad Argentina de Informática e Investigación Operativ