Abstract
Context: Software testing is a very relevant step in quality assurance, but developers frequently overlook it. We pursued testing automation to minimize the impact of missing test cases in a software project. Problem: However, for Python programs, there are not many tools able to fully automate the generation of unit test sets, and the one available demands studies to provide evidence of the quality of the generated test set. Solution: This work aims to evaluate the quality of different unit test generation algorithms for Python, implemented in a tool named Pynguin. Method: In the analysis of the selected programs, the Pynguin test generation tool is executed with each of its algorithms, including random, as a way to generate complete unit test sets. Then, we evaluate each generated test set's efficacy, efficiency, and cost. We use four different fault models, implemented by four mutation testing tools, to measure efficacy. We use line and branch coverage to measure efficiency, the number of test cases, and test set execution time to measure cost. Summary of Results: We identified that RANDOM test set performed worst concerning all evaluated aspects, DYNAMOSA and MOSA, the two algorithms that generate the best test sets regarding efficacy, efficiency, and cost. By combining all Pynguin smart algorithms (DYNAMOSA, MIO, MOSA, WHOLE-SUITE), the resultant test set overcomes the individual test sets efficiency by around 1%, for coverage and efficacy by 4.5% on average, concerning previous mutation score, at a reasonable cost, without a test set minimization.

Abstract
Licensing technologies are one of the main ways to produce and bring academic research to society. Despite previous studies' dedicated efforts to identify licensing probabilities, the question of how the expertise and prestige that a university has in a given technological field influences the licensing probabilities is still little addressed. This article aims to identify information in patent documents to estimate the probabilities of licensing technologies produced at the university. For that, we performed a data mining of licensed and unlicensed patents from an important Brazilian University (n = 1,578). We estimated the licensing probabilities using the Logistic Regression technique, based on the Maximum Likelihood Estimation. The results suggest that the variables of know-how in the main field and Technological strength in the main field are the most important/influential variables in estimating the probabilities of licensing a given patent. The main conclusion obtained from the results is that: universities, to obtain more licenses, must increase their know-how (expertise) in some technological fields, maintaining a reasonable level between specialization and diversification. Additionally, the higher the citations received (prestige/recognition) by a university in a given technological field, the greater the probability of patent licensing in that technological field. In terms of practical contributions, this study suggests that: investments in specific technological fields generate more competitive advantages for the university and, thus, more technological successes.

Abstract

Abstract
Bogota, the largest urban center and capital city of Colombia, is located within the Bogota savanna, which originated as a lake in the central part of the Colombian Eastern Cordillera. Over time, the lake transformed into a gently undulating plain with horizontally deposited sediments that formed around five million years ago. Over the last few decades, the region has undergone significant population growth and rapid urban development, largely driven by migration from rural areas. This development has substantially impacted the subsidence observed in the city, primarily due to the extraction of groundwater. A previous study by the Servicio Geologico Colombiano (SGC) utilized data from GNSS stations and synthetic aperture radar interferometry (InSAR) with TerraSAR-X SAR between 2011 and 2017 to identify a subsidence pattern in the central region of Bogota. The purpose of the study was to evaluate the risks and potential disasters associated with the subsidence phenomenon. Our study investigates both the subsidence in Bogota, previously studied, as well as the rural savanna area, which is currently undergoing significant residential and industrial development. We utilized multi-temporal InSAR (MT-InSAR) techniques with Sentinel-1 SAR images from 2014 to 2021. The analysis results indicate that the outer regions of the city display the most significant subsidence, extending from the center to the north. The subsidence velocities in these areas reach approximately 5-6 cm/year.

Abstract
The Accessibility Requirements Tool for Information and Communication Technologies (FRATIC) was developed within the work of a doctoral project, at the University of Tras-os-Montes and Alto Douro, and may be used at various stages of public procurement processes as well as projects and developments that include ICT products and services. This tool helps to consult, determine and assess the accessibility requirements for ICT products and services in European Standard EN 301 549 supporting the legislation in the field of public procurement for the countries of the European Union - Directive 2014/24/EU. This paper focuses on the implementation of contributions, improvements, and suggestions from 25 experts in the fields of accessibility, assistive technologies and public procurement, gathered from usability tests and semi-structured interviews, which were conducted on FRATIC version 1.1. The implementation of these has resulted in an improved version of the tool: FRATIC 1.2.

Abstract
The transport and logistics sector, which include freight forwarders companies, constitutes a vast network of entities that are central to a good performance in services. With the COVID-19 pandemic and its effects on the global economy, there was a huge shortage in the number of containers available, thus creating the need to optimize the loading of available equipment to avoid waste and maximize profits from each export. The present work presents a novel approach where a set of restrictions were created that, applied in synergy with the Non-Linear GRG algorithm, aim to allocate the boxes in different consecutive lines until forming a wall, and, therefore, the walls complete the container, in order to maximize the occupancy on it. To validate the proposed approach a prototype was developed and studied in real-world problem where the solutions resulted in occupations around 80% to 90%. Thus, we can foresee the importance of the proposed approach in decision-making regarding container consolidation services. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.