Promoting Bright Patterns

User experience designers are facing increasing scrutiny and criticism for creating harmful technologies, leading to a pushback against unethical design practices. While clear-cut harmful practices such as dark patterns have received attention, trends towards automation, personalization, and recommendation present more ambiguous ethical challenges. To address potential harm in these "gray" instances, we propose the concept of "bright patterns" - persuasive design solutions that prioritize user goals and well-being over their desires and business objectives. The ambition of this paper is threefold: to define the term "bright patterns", to provide examples of such patterns, and to advocate for the adoption of bright patterns through policymaking.Comment: For associated website, see https://brightpatterns.org/. Published to the CHI '23 Workshop: Designing Technology and Policy Simultaneousl

Software Engineering Applications enabled by Blockchain Technology: A Systematic Mapping Study

The novel, yet disruptive blockchain technology has witnessed growing attention, due to its intrinsic potential. Besides the conventional domains that benefit from such potential, such as finance, supply chain and healthcare, blockchain use cases in software engineering have emerged recently. In this study, we aim to contribute to the body of knowledge of blockchain-oriented software engineering by providing an adequate overview of the software engineering applications enabled by blockchain technology. To do so, we carried out a systematic mapping study and identified 22 primary studies. Then, we extracted data within the research type, research topic and contribution type facets. Findings suggest an increasing trend of studies since 2018. Additionally, findings reveal the potential of using blockchain technologies as an alternative to centralized systems, such as GitHub, Travis CI, and cloud-based package managers, and also to establish trust between parties in collaborative software development. We also found out that smart contracts can enable the automation of a variety of software engineering activities that usually require human reasoning, such as the acceptance phase, payments to software engineers, and compliance adherence. In spite of the fact that the field is not yet mature, we believe that this systematic mapping study provides a holistic overview that may benefit researchers interested in bringing blockchain to the software industry, and practitioners willing to understand how blockchain can transform the software development industry.publishedVersio

Requirements Engineering that Balances Agility of Teams and System-level Information Needs at Scale

Context: Motivated by their success in software development, large-scale systems development companies are increasingly adopting agile methods and their practices. Such companies need to accommodate different development cycles of hardware and software and are usually subject to regulation and safety concerns. Also, for such companies, requirements engineering is an essential activity that involves upfront and detailed analysis which can be at odds with agile development methods. Objective: The overall aim of this thesis is to investigate the challenges and solution candidates of performing effective requirements engineering in an agile environment, based on empirical evidence. Illustrated with studies on safety and system-level information needs, we explore RE challenges and solutions in large-scale agile development, both in general and from the teams’ perspectives. Method: To meet our aim, we performed a secondary study and a series of empirical studies based on case studies. We collected qualitative data using interviews, focus groups and workshops to derive challenges and potential solutions from industry. Findings: Our findings show that there are numerous challenges of conducting requirements engineering in agile development especially where systems development is concerned. The challenges discovered sprout from an integration problem of working with agile methods while relying on established plan-driven processes for the overall system. We highlight the communication challenge of crossing the boundary of agile methods and system-level (or plan-driven) development, which also proves the coexistence of both methods. Conclusions: Our results highlight the painful areas of requirements engineering in agile development and propose solutions that can be explored further. This thesis contributes to future research, by establishing a holistic map of challenges and candidate solutions that can be further developed to make RE more efficient within agile environments

Action-based recommendation in pull-request development

Pull requests (PRs) selection is a challenging task faced by integrators in pull-based development (PbD), with hundreds of PRs submitted on a daily basis to large open-source projects. Managing these PRs manually consumes integrators' time and resources and may lead to delays in the acceptance, response, or rejection of PRs that can propose bug fixes or feature enhancements. On the one hand, well-known platforms for performing PbD, like GitHub, do not provide built-in recommendation mechanisms for facilitating the management of PRs. On the other hand, prior research on PRs recommendation has focused on the likelihood of either a PR being accepted or receive a response by the integrator. In this paper, we consider both those likelihoods, this to help integrators in the PRs selection process by suggesting to them the appropriate actions to undertake on each specific PR. To this aim, we propose an approach, called CARTESIAN (aCceptance And Response classificaTion-based requESt IdentificAtioN) modeling the PRs recommendation according to PR actions. In particular, CARTESIAN is able to recommend three types of PR actions: accept, respond, and reject. We evaluated CARTESIAN on the PRs of 19 popular GitHub projects. The results of our study demonstrate that our approach can identify PR actions with an average precision and recall of about 86%. Moreover, our findings also highlight that CARTESIAN outperforms the results of two baseline approaches in the task of PRs selection

Challenges and Success Factors for Metrics in Large-Scale Agile Development

Contemporary organizations widely use agile software development to react to unpredictable changes in their business environment. Due to the success of agile methods in contexts similar to the agile sweet spot, organizations have been applying them on a larger scale. However, maintaining oversight in large-scale agile development remains a problem. Metrics can tackle this problem by increasing transparency, but organizations have struggled with their adoption. Furthermore, extant research on large-scale agile development lacks publications investigating metric challenges and success factors. Against this backdrop, we conducted an expert interview study with 23 experts from 13 organizations. The most mentioned challenges are data collection challenges, lack of metric usefulness, and metric calculation challenges. On the other hand, the most occurring success factors are context-dependent metric adoption, implementing an agile metric management process, and ensuring understanding of the metric purpose

GLOBAL-MANAGER: A Serious Game for Providing Training in Project Manager Skills

The emergence of Global Software Development (GSD) has led to certain difficulties in the life cycle of global projects, in addition to the traditional challenges of collocated development, particularly as regards Project Management (PM). These difficulties are caused by the geographical, linguistic and cultural distance among the members of the team, signifying that the project manager requires special skills with which to mitigate these issues. Bearing this in mind, this paper describes a serious game (SG), denominated as GLOBAL-MANAGER, whose objective is to provide training in the management of GSD projects. The game attempts to develop several skills in its players whilst simultaneously providing them with an immersive, pleasant and attractive experience. The skills developed are related to coordination, communication and control, which are three of the principal challenges in GSD

“Won’t we fix this issue?” : qualitative characterization and automated identification of wontfix issues on GitHub

Context: Addressing user requests in the form of bug reports and Github issues represents a crucial task of any successful software project. However, user-submitted issue reports tend to widely differ in their quality, and developers spend a considerable amount of time handling them. Objective: By collecting a dataset of around 6,000 issues of 279 GitHub projects, we observe that developers take significant time (i.e., about five months, on average) before labeling an issue as a wontfix. For this reason, in this paper, we empirically investigate the nature of wontfix issues and methods to facilitate issue management process. Method: We first manually analyze a sample of 667 wontfix issues, extracted from heterogeneous projects, investigating the common reasons behind a “wontfix decision”, the main characteristics of wontfix issues and the potential factors that could be connected with the time to close them. Furthermore, we experiment with approaches enabling the prediction of wontfix issues by analyzing the titles and descriptions of reported issues when submitted. Results and conclusion: Our investigation sheds some light on the wontfix issues’ characteristics, as well as the potential factors that may affect the time required to make a “wontfix decision”. Our results also demonstrate that it is possible to perform prediction of wontfix issues with high average values of precision, recall, and F-measure (90%-93%)

Automated identification and qualitative characterization of safety concerns reported in UAV software platforms

Unmanned Aerial Vehicles (UAVs) are nowadays used in a variety of applications. Given the cyber-physical nature of UAVs, software defects in these systems can cause issues with safety-critical implications. An important aspect of the lifecycle of UAV software is to minimize the possibility of harming humans or damaging properties through a continuous process of hazard identification and safety risk management. Specifically, safety-related concerns typically emerge during the operation of UAV systems, reported by end-users and developers in the form of issue reports and pull requests. However, popular UAV systems daily receive tens or hundreds of reports of varying types and quality. To help developers timely identifying and triaging safety-critical UAV issues, we (i) experiment with automated approaches (previously used for issue classification) for detecting the safety-related matters appearing in the titles and descriptions of issues and pull requests reported in UAV platforms, and (ii) propose a categorization of the main hazards and accidents discussed in such issues. Our results (i) show that shallow machine learning-based approaches can identify safety-related sentences with precision, recall, and F-measure values of about 80\%; and (ii) provide a categorization and description of the relationships between safety issue hazards and accidents

Requirements engineering challenges and practices in large-scale agile system development

Context: Agile methods have become mainstream even in large-scale systems engineering companies that need to accommodate different development cycles of hardware and software. For such companies, requirements engineering is an essential activity that involves upfront and detailed analysis which can be at odds with agile development methods. Objective: This paper presents a multiple case study with seven large-scale systems companies, reporting their challenges, together with best practices from industry. We also analyze literature about two popular large-scale agile frameworks, SAFe (R) and LeSS, to derive potential solutions for the challenges. Methods: Our results are based on 20 qualitative interviews, five focus groups, and eight cross company workshops which we used to both collect and validate our results. Results: We found 24 challenges which we grouped in six themes, then mapped to solutions from SAFe (R), LeSS, and our companies, when available. Conclusion: In this way, we contribute a comprehensive overview of RE challenges in relation to largescale agile system development, evaluate the degree to which they have been addressed, and outline research gaps. We expect these results to be useful for practitioners who are responsible for designing processes, methods, or tools for large scale agile development as well as guidance for researchers