Contextualizing and generalizing drivers and barriers of urban livings labs for climate resilience

Urban Living Labs are open innovation ecosystems that integrate research and innovation activities within urban communities. However, while solutions co-created and tested in the Urban Living Labs must be contextualized and tailored to each city's uniqueness, broader impact requires generalization and systematic replication across geographical, institutional, and sectoral boundaries. This article examines nine Living Labs in European coastal cities, identifying several barriers and drivers for mainstreaming and upscaling solutions to increase climate resilience through the Living Lab Integrative Process. Our analysis focuses on three main categories. First, social and cultural aspects highlighted include stakeholder engagement and awareness, communication, and dissemination. Second, we assess institutional and political aspects, such as silos, bureaucracy, and resources. Last, we investigate technical factors as knowledge and experience, technical and internal capacity, data availability and accessibility, climate-related policies and actions, and long-term perspective. The results suggest that while some barriers and drivers are common across the cases, providing generalizable patterns, there are also specific differences requiring tailored solutions at the local scale. Nonetheless, the diversity in drivers indicates the potential for sharing knowledge across cases to translate, embed, and scale solutions, enhancing the transition toward climate resilience. Learning and innovation in real-life contexts are fundamental in the Living Lab approach, and our findings demonstrate that cross-case learning can enhance an iterative process of contextualizing and generalizing innovative climate solutions

Efeitos de um programa de orientação para adultos com lombalgia

OBJETIVO: Implantar um programa de "Escola da Postura" para pacientes com lombalgia crônica. MÉTODOS: Foram avaliados 41 sujeitos (46,81 ± 13,35 anos), de ambos os gêneros, com idade entre 25-65 anos que possuíam dor lombar há mais de 6 meses. Inicialmente, foi realizado a avaliação da qualidade de vida (Medical Outcomes Study 36- Item Short-Form Health Survey- SF-36) e capacidade funcional (Oswestry Low Back Pain Disability Questionnaire - ODQ). Em seguida, todos os sujeitos participaram de cinco encontros semanais de 60 minutos, nos quais foram desenvolvidos as capacitações teórico-práticas. Após uma semana, os sujeitos foram reavaliados. Os dados obtidos nas avaliações foram analisados utilizando o teste estatístico não-paramétrico de Wilcoxon, com nível de significância de 5% (pOBJECTIVE: To implement a "Back School" program for low-back chronic pain. METHODS: Forty one subjects were evaluated (46,81 + 13,35 years old), from both genders, with the age from 25-65 years who had low-back pain for more than 6 months. Initially, the quality of life evaluation was made (Medical Outcomes Study 36- Item Short-Form Health Survey- SF-36), functional capacity (Oswestry Low Back Pain Disability Questionnaire - ODQ). Following that, every subject participated of five 60-minute weekly meetings, in which the theoretical-practical capacities were developed. After a week, the subjects were re-evaluated. The obtained data over the evaluations were analyzed using the Wilcoxon non-parametric statistics test, with a significance level of 5% (p<0,05). RESULTS: A significant improvement was observed over the functional capacity (ODQ, p<0,0001).The QV, was observed over the domains functional capacity (p=0,0016), pain (p=0,0035), general health state (p<0,0001), vitality (p<0,0001), social aspects (p<0,0001) and mental health (p=0,0007). Over the physical and emotional aspects items were a significant difference were not observed. CONCLUSION: Back School program was capable of improving the quality of life and functional capacity of the participants

Comprehending test code: An empirical study

Developers spend a large portion of their time and effort on comprehending source code. While many studies have investigated how developers approach these comprehension tasks and what factors influence their success, less is known about how developers comprehend test code specifically, despite the undisputed importance of testing. In this paper, we report on the results of an empirical study with 44 developers to understand which factors influence developers when comprehending Java test code. We measured three dependent variables: the total time spent reading a test suite, the ability to identify the overall purpose of a test suite, and the ability to produce additional test cases to extend a test suite. The main findings of our study, with several implications for future research and practitioners, are that (i) prior knowledge of the software project decreases the total reading time, (ii) experience with Java affects the proportion of time spent on the Arrange and Assert sections of test cases, (iii) experience with Java and prior knowledge of the software project positively influence the ability to produce additional test cases of certain categories, and (iv) experience with automated tests is an influential factor towards understanding and extending an automated test suite.Chak Shun Yu, Christoph Treude, Maurício Anich

Selecting third-party libraries: the practitioners' perspective

The selection of third-party libraries is an essential element of virtually any software development project. However, deciding which libraries to choose is a challenging practical problem. Selecting the wrong library can severely impact a software project in terms of cost, time, and development effort, with the severity of the impact depending on the role of the library in the software architecture, among others. Despite the importance of following a careful library selection process, in practice, the selection of third-party libraries is still conducted in an ad-hoc manner, where dozens of factors play an influential role in the decision. In this paper, we study the factors that influence the selection process of libraries, as perceived by industry developers. To that aim, we perform a cross-sectional interview study with 16 developers from 11 different businesses and survey 115 developers that are involved in the selection of libraries. We systematically devised a comprehensive set of 26 technical, human, and economic factors that developers take into consideration when selecting a software library. Eight of these factors are new to the literature. We explain each of these factors and howthey play a role in the decision. Finally, we discuss the implications of our work to library maintainers, potential library users, package manager developers, and empirical software engineering researchers.Enrique Larios Vargas, Maurício Aniche, Christoph Treude, Magiel Bruntink, Georgios Gousio

Contextualizing and generalizing drivers and barriers of urban livings labs for climate resilience

Urban Living Labs are open innovation ecosystems that integrate research and innovation activities within urban communities. However, while solutions co-created and tested in the Urban Living Labs must be contextualized and tailored to each city's uniqueness, broader impact requires generalization and systematic replication across geographical, institutional, and sectoral boundaries. This article examines nine Living Labs in European coastal cities, identifying several barriers and drivers for mainstreaming and upscaling solutions to increase climate resilience through the Living Lab Integrative Process. Our analysis focuses on three main categories. First, social and cultural aspects highlighted include stakeholder engagement and awareness, communication, and dissemination. Second, we assess institutional and political aspects, such as silos, bureaucracy, and resources. Last, we investigate technical factors as knowledge and experience, technical and internal capacity, data availability and accessibility, climate-related policies and actions, and long-term perspective. The results suggest that while some barriers and drivers are common across the cases, providing generalizable patterns, there are also specific differences requiring tailored solutions at the local scale. Nonetheless, the diversity in drivers indicates the potential for sharing knowledge across cases to translate, embed, and scale solutions, enhancing the transition toward climate resilience. Learning and innovation in real-life contexts are fundamental in the Living Lab approach, and our findings demonstrate that cross-case learning can enhance an iterative process of contextualizing and generalizing innovative climate solutions

Search-Based Test Data Generation for SQL Queries

Database-centric systems strongly rely on SQL queries to manage and manipulate their data. These SQL commands can range from very simple selections to queries that involve several tables, subqueries, and grouping operations. And, as with any important piece of code, developers should properly test SQL queries. In order to completely test a SQL query, developers need to create test data that exercise all possible coverage targets in a query, e.g., JOINs and WHERE predicates. And indeed, this task can be challenging and time-consuming for complex queries. Previous studies have modeled the problem of generating test data as a constraint satisfaction problem and, with the help of SAT solvers, generate the required data. However, such approaches have strong limitations, such as partial support for queries with JOINs, subqueries, and strings (which are commonly used in SQL queries). In this paper, we model test data generation for SQL queries as a search-based problem. Then, we devise and evaluate three different approaches based on random search, biased random search, and genetic algorithms (GAs). The GA, in particular, uses a fitness function based on information extracted from the physical query plan of a database engine as search guidance. We then evaluate each approach in 2,135 queries extracted from three open source software and one industrial software system. Our results show that GA is able to completely cover 98.6% of all queries in the dataset, requiring only a few seconds for each query. Moreover, it does not suffer from the limitations affecting state-of-the art techniques.Software EngineeringSoftware Technolog

A Collaborative Approach to Teaching Software Architecture

Teaching software architecture is hard. The topic is abstract and is best understood by experiencing it, which requires proper scale to fully grasp its complexity. Furthermore, students need to practice both technical and social skills to become good software architects. To overcome these teaching challenges, we developed the Collaborative Software Architecture Course. In this course, participants work together to study and document a large, open source software system of their own choice. In the process, all communication is transparent in order to foster an open learning environment, and the end-result is published as an online book to benefit the larger open source community. We have taught this course during the past four years to classes of 50-100 students each. Our experience suggests that: (1) open source systems can be successfully used to let students gain experience with key software architecture concepts, (2) students are capable of making code contributions to the open source projects, (3) integrators (architects) from open source systems are willing to interact with students about their contributions, (4) working together on a joint book helps teams to look beyond their own work, and study the architectural descriptions produced by the other teams.Software TechnologySoftware Engineerin