1,721,018 research outputs found
Civic participation powered by Ethereum: A proposal
No full textIn the last decade, ICT infrastructures for smart cities have become a reality and the number of projects affecting citizens' lives is growing. In particular, the technology supporting civic participation is mature, although many systems do not reach the needed critical mass, as they are not able to capture the interest of their intended target. To overcome this difficulty, we describe a proposal for encouraging citizens' participation by a reward mechanism based on a civic currency, powered by blockchain tokens, used to recognize civic engagement.
This paper briefly sketches the main features of the system and discusses the development of its proof-of-concept in the context of a university course following an agile process, highlighting the lessons so learned
Enlisting Students in Gamifying Software Testing Education: Results and Key Insights
No full textGamification aims to enhance motivation for a variety of routine tasks by incorporating game elements, such as scoring. In educational settings, students are often the players, and gamification can create a more engaging learning environment that motivates them to achieve academic success. In this paper, we describe an experimental software engineering course where we asked students enrolled in a Master's degree program in Computer Science to play the role of game designers and develop software prototypes for the gamification of software testing education. We outline and compare their three proposals to gamify learning in software testing, which reflect team members' diverse interests and inclinations. As a result, the proposals vary in nature, ranging from a gamified standard web application delivering exercises to a fully-fledged game. User testing provided a preliminary evaluation of their playability. Our lessons learned can guide other academics in designing similar assignments for software engineering students to develop gamification prototypes
COVID-19 hits the job market: An 88 million job ads analysis
No full textThe impact of the Covid-19 pandemic has been relevant in all economic sectors. Job loss and decrease in hiring are among the most severe immediate financial impact of Covid-19, while lower economic growth will be the long-term effect. To get a better understanding of what happened, in this work, we have studied the trends of the job market through a massive analysis of job ads taken from LinkUp, a popular Web job-search platform. In particular, we analysed 88 million advertisements to overview the effects of Covid-19 on the entire job market. Results show the Covid-19 crisis to have affected the job market in the 2020 first and especially second quarter, drastically reducing the number of ads in all the sectors (except one). The number of ads has dropped between 4% and 48%, depending on the specific professional figure, with the only exception of the Food Preparation and Serving Related, that has gained 16%
COVID-19 Impacts on the IT Job Market: A Massive Job Ads Analysis
No full textThe Covid-19 pandemic has had a significant impact on many economic sectors. The most severe immediate financial effects of Covid-19 include job losses and decreased hiring, and we can expect generalized lower economic growth in the long term. While such phenomena are there for all to see, measuring their scope is complex. In this work, we performed a massive analysis of job postings (ads) taken from LinkUp, a popular job search web platform, to better understand the occupational trends in IT. We analyzed about nine million ads for computer and mathematical experts to measure the impact of the virus on the IT job market. We also extended our investigations to almost 109 million advertisements (about 300 GB of data) for all kinds of positions to overview the effects of Covid-19 on the job market at large. The results show that the Covid-19 crisis hit the job market during the first two quarters of 2020, causing the number of job advertisements to drop across all sectors (except one). Specifically, the IT sector lost between 15% and 48% of the ads, depending on the specific professional figure. Since the last quarter of 2020, the ad numbers have recovered for some sectors, and by the first 2021 quarter, all of them have more job ads than in the last five years. Finally, we used text analysis to understand the trends of interest in teleworking. We found that in the second quarter of 2020, the number of ads explicitly mentioning telework was almost three times the average of the previous quarters
What 5 million job advertisements tell us about testing: A preliminary empirical investigation
No full textSoftware testing is a crucial part of business success to ensure final product quality. However, little concrete data exists on technical demands about it in the industry, mostly collected through personal opinion surveys on a restricted sample of professionals. In this paper, we used a different approach: we applied content analysis to a set of about five million job advertisements taken from a popular Web job-search engine. The analysis of job advertisements is more promising than surveys because the data are by far more numerous and distributed geographically. The content analysis results revealed four essential findings on the current practice of software testing: a) Companies search for about six times more Coders than Testers, b) Unit testing is the most required skill for Coders while Acceptance testing is the most popular for Testers, c) Automated testing dominates the job advertisement scene compared to Manual testing and, d) the most valuable testing tools and frameworks are Selenium, JUnit, and Cucumber for both Testers and Coders. We believe that these findings (and other related results from the content analysis study) will be useful for professionals, instructors, and researchers dealing with software testing
On the Deployment of IoT Systems: An Industrial Survey
No full textInternet of Things (IoT) systems are complex and multifaceted, and the design of their architectures needs to consider many aspects at a time. Design decisions concern, for instance, the modeling of software components and their interconnections, as well as where to deploy the components within the available hardware infrastructure in the Edge-Cloud continuum. A relevant and challenging task, in this context, is to identify optimal deployment models due to all the different aspects involved, such as extra-functional requirements of the system, heterogeneity of the hardware resources concerning their processing and storage capabilities, and constraints like legal issues and operational cost limits. To gain insights about the deployment decisions concerning IoT systems in practice, and the factors that influence those decisions, we report about an industrial survey we conducted with 66 IoT architects from 18 countries across the world. Each participant filled in a questionnaire that comprises 15 questions. By analyzing the collected data, we have two main findings: (i) architects rely on the Cloud more than the Edge for deploying the software components of IoT systems, in the majority of the IoT application domains; and (ii) the main factors driving deployment decisions are four: reliability, performance, security, and cost
What are IoT systems for real? An experts’ survey on software engineering aspects
No full textInternet of Things (IoT) systems are becoming ubiquitous, and their spread has had a significant impact on all aspects of society. Software is a key aspect of IoT systems, from firmware to cloud infrastructures. For this reason, Software Engineering (SE) is crucial to design, develop, deploy, and maintain high-quality IoT systems. Despite the high relevance of these systems, by analysing the literature from a Software Engineering perspective little emerges about their key elements and characteristics, including qualities as perceived by experts working in the IoT field. For this reason, the aim of this work is to understand from the practice, the main characteristics of IoT systems to improve the SE support for their development. We carried out a survey and received 433 practitioners answers from 53 countries across the world. By analysing the collected data, we found that so far: (i) experts working on (industrial) IoT systems only acknowledge in practice some of the main elements and characteristics of IoT systems that can be found in the literature; (ii) most IoT systems require human intervention while advanced learning and self-adaption features are not widely adopted yet; (iii) Smart Industry, Smart City, Smart Building, and Smart Home are by far the most relevant IoT systems application domains; (iv) deployment choices of IoT systems largely favour the Cloud for what concerns the computation (and thus the software); and finally (v) the most relevant quality attributes for IoT systems are reliability, availability, performance, scalability, and security
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Fight silent horror unit test methods by consulting a TestWizard
No full textTests, when not correctly implemented, can pass on incorrect system implementations rather than fail. In this case, they are named silent horrors or false-negative tests. They make releasing low-quality (buggy) versions of the software system more probable. Furthermore, faithfully implementing test specifications is crucial when they play the role of documentation, like when documenting components or services or driving legacy systems' re-engineering. This paper presents TestWizard, a novel approach and tool for automatically assessing individual tests' quality from the point of view of their coherence to specifications. TestWizard automatically assesses the quality of each individual test case w.r.t. its specification, providing detailed reports on why a single test is a false negative, hence helping testers fix them. Thus, TestWizard can help to automate the test code review process, which is still mainly manual today. The analysis of 1012 test implementations, developed by 123 students in three experiments, shows that TestWizard is (1) by far more accurate than code review performed by multiple students, (2) slightly better than code review performed by three senior experts, and (3) always able to detect a significant percentage of false-negative test methods (up to 21.22%)
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