Thunderstorms are one of the most amazing meteorological phenomena of nature, but, unfortunately, lightnings can be dangerous for people, fauna and infrastructure. America is one of the regions in the world with the most intense convective systems, and Argentina is one of the countries with most electrical storms. In this context, a web and mobile application called GeoRayos was created as an interdisciplinary project to study and detect lightning strikes in real time, and visualize electric field, to raise awareness and prevent accidents and fatalities to the general public. Nowadays, GeoRayos is currently used by decision makers from various institutions such as Civil Defense, National Fire Management Service, and National Parks, as well as meteorologists from the Argentine National Meteorological Service.

Multi-Agent Systems became a powerful solution to model and solve problems in complex and dynamic environments. While research in this area grew exponentially before 2009, there is a need to understand the status quo of the field from 2009 to June 2017 in order to comprehend the general evolution. The results of a SLR related to Multi-Agent Systems, its applications and research gaps, following Kitchenham and Wholin guidelines are presented in this paper. From the analysis of279 papers (out of3522 candidates), our findings suggest that: a) there is a general decreasing trend of publications (but it is increasing for specific domains), b) only 15% of the papers portrayed a real case study, c) the top 20 were formed by 67 authors, d) the papers were mostly published in journals and conferences, e) there is no unified methodology or framework, f) the top 3 application domains were transport/traffic, healthcare/biology, and logistics/manufacturing, g) MAS interact with different disciplines like machine learning. Finally, the MAS community should work together to close the gaps and unify the field, bridging with other disciplines and industry.

The measurement of Function Points is based on Base Functional Components. The process of identifying and weighting Base Functional Components is hardly automatable, due to the informality of both the Function Point method and the requirements documents being measured. So, Function Point measurement generally requires a lengthy and costly process. We investigate whether it is possible to take into account only subsets of Base Functional Components so as to obtain functional size measures that simplify Function Points with the same effort estimation accuracy as the original Function Points measure. Simplifying the definition of Function Points would imply a reduction of measurement costs and may help spread the adoption of this type of measurement practices. Specifically, we empirically investigate the following issues: whether available data provide evidence that simplified software functionality measures can be defined in a way that is consistent with Function Point Analysis; whether simplified functional size measures by themselves can be used without any appreciable loss in software development effort prediction accuracy; whether simplified functional size measures can be used as software development effort predictors in models that also use other software requirements measures. We analyze the relationships between Function Points and their Base Functional Components. We also analyze the relationships between Base Functional Components and development effort. Finally, we built effort prediction models that contain both the simplified functional measures and additional requirements measures. Significant statistical models correlate Function Points with Base Functional Components. Basic Functional Components can be used to build models of effort that are equivalent, in terms of accuracy, to those based on Function Points. Finally, simplified Function Points measures can be used as software development effort predictors in models that also use other requirements measures. The definition and measurement processes of Function Points can be dramatically simplified by taking into account a subset of the Base Functional Components used in the original definition of the measure, thus allowing for substantial savings in measurement effort, without sacrificing the accuracy of software development effort estimates.

An empirical study was conducted in order to evaluate the simplicity of FPA, COSMIC and Paths, from the IT practitioners' viewpoint. The results have shown that P are the simplest measure because they presented a significantly lower measurement time. The study has also been useful to see which aspects of Paths should be clarified in order to facilitate the practitioners' application of this measure and to demonstrate in a mathematical form how the complexity of an application which is measured with P increases if the number of "transactions" increases. The results obtained cannot be generalized because the number of measurements performed was small, and the subjects had particular characteristics, but a new empirical study using use case textual descriptions of different domains and subjects with different characteristics is expected to solve this limitation.

This paper presents a methodology to detect and measure the complexity of traceable transactions from requirements (use cases) to code (source code) of a system.

Functional Size Measures are often used for effort estimation. However, these measures do not take into account the amount and complexity of elaboration required, concentrating instead on the amount of data accessed or moved. Methods for measuring the functional complexity have been proposed, but, being based on the textual description of requirements, are not very easy to apply. In this paper we show that measurement-oriented UML modeling can support the measurement of both functional size and functional complexity. We show, by means of a case study, that it is reasonably easy to derive different types of functional size measures, as well as complexity measures, from UML models. We show also that it is possible to build models for effort estimation that use the functional size and complexity measures as independent variables.

The fact that Albrecht's function point method must be frequently improved or adjusted to suit new development contexts shows that there is a need for a new approach to early estimate effort. Such approach should reduce the estimation error and it is convenient for it to be based on use cases. The authors defined two simple metrics which capture two key aspects of software applications, size and complexity, which are called transactions (T) and paths (P). Also, in order to demonstrate that it is possible to reduce the error of effort estimation using these two new metrics, a case study was developed.

Function points are a standard method frequently used to calculate size and to estimate effort in applications. Although it has been used with good results in the development of industrial software, it is still necessary to improve some aspects such as: the time at which the estimation of effort is performed and the margin of error in the effort estimation. In this article an alternative method for early effort estimation based on use cases is presented. Two new alternative notions of size are used for effort estimation: transactions and entity objects. A case study developed in order to compare the estimations obtained with the two methods for actual projects is described. The result shows that by using number of transactions as a notion of size and the technique mean productivity value to perform the estimation, the current way of estimating effort can be improved.