large language models

Making Sense out of a Jungle of JavaScript Frameworks: towards a Practitioner-friendly Comparative Analysis

The field of Web development is entering the HTML5 and CSS3 era and JavaScript is becoming increasingly influential. A large number of JavaScript frameworks have been recently promoted. Practitioners applying the latest technologies need to choose a suitable JavaScript framework (JSF) in order to abstract the frustrating and complicated coding steps and to provide a cross-browser compatibility. Apart from benchmark suites and recommendation from experts, there is little research helping practitioners to select the most suitable JSF to a given situation. The few proposals employ software metrics on the JSF, but practitioners are driven by different concerns when choosing a JSF. As an answer to the critical needs, this paper is a call for action. It proposes a research design towards a comparative analysis framework of JSF, which merges researcher needs and practitioner needs.

A framework for systematic analysis of open access journals and its application in software engineering and information systems

This article is a contribution towards an understanding of open access (OA) publishing. It proposes an analysis framework of 18 core attributes, divided into the areas of bibliographic information, activity metrics, economics, accessibility, and predatory issues. The framework has been employed in a systematic analysis of 30 OA journals in software engineering (SE) and information systems (IS), which were selected from among 386 OA journals in Computer Science from the Directory of OA Journals. An analysis was performed on the sample of the journals, to provide an overview of the current situation of OA journals in the fields of SE and IS. The journals were then compared between-group, according to the presence of article processing charges. A within-group analysis was performed on the journals requesting article processing charges from authors, in order to understand what is the value added according to different price ranges. This article offers several contributions. It presents an overview of OA definitions and models. It provides an analysis framework born from the observation of data and the existing literature. It raises the need to study OA in the fields of SE and IS while offering a first analysis. Finally, it provides recommendations to readers of OA journals. This paper highlights several concerns still threatening the adoption of OA publishing in the fields of SE and IS. Among them, it is shown that high article processing charges are not sufficiently justified by the publishers, which often lack transparency and may prevent authors from adopting OA.

Lean startup: why large software companies should care

Hunter-gatherer cycle: a conceptual model of the evolution of software startups

Towards an Early Stage Software Startups Evolution Model

What leads developers towards the choice of a JavaScript framework?

Context: The increasing popularity of JavaScript (JS) has lead to a variety of frameworks that aim to help developers to address programming tasks. However, the number of JS Frameworks (JSF) has risen rapidly to thousands and more. It is difficult for practitioners to identify the frameworks that best fit to their needs and to develop new frameworks that fit such needs. Existing research has focused in proposing software metrics for the frameworks, which do not carry a high value to practitioners. While benchmarks, technical reports, and experts' opinions are available, they suffer the same issue that they do not carry much value. In particular, there is a lack of knowledge regarding the processes and reasons that drive developers towards the choice. Objective: This paper explores the human aspects of software development behind the decision-making process that leads to a choice of a JSF. Method: We conducted a qualitative interpretive study, following the grounded theory data analysis methodology. We interviewed 18 participants who are decision makers in their companies or entrepreneurs, or are able to motivate the JSF decision-making process. Results: We offer a model of factors that are desirable to be found in a JSF and a representation of the decision makers involved in the frameworks selection. The factors are usability (attractiveness, learnability, understandability), cost, efficiency (performance, size), and functionality (automatisation, extensibility, flexibility, isolation, modularity, suitability, updated). These factors are evaluated by a combination of four possible decision makers, which are customer, developer, team, and team leader. Conclusion: Our model contributes to the body of knowledge related to the decision-making process when selecting a JSF. As a practical implication, we believe that our model is useful for (1) Web developers and (2) JSF developers.

The Essence Theory of Software Engineering - Large-Scale Classroom Experiences from 450+ Software Engineering BSc Students

Software Engineering as an industry is highly diverse in terms of development methods and practices. Practitioners employ a myriad of methods and tend to further tailor them by e.g. omitting some practices or rules. This diversity in development methods poses a challenge for software engineering education, creating a gap between education and industry. General theories such as the Essence Theory of Software Engineering can help bridge this gap by presenting software engineering students with higher-level frameworks upon which to build an understanding of software engineering methods and practical project work. In this paper, we study Essence in an educational setting to evaluate its usefulness for software engineering students while also investigating barriers to its adoption in this context. To this end, we observe 102 student teams utilize Essence in practical software engineering projects during a semester long, project-based course.

Do software firms collaborate or compete? A model of coopetition in community-initiated OSS projects

[Background] An increasing number of commercial firms are participating in Open Source Software (OSS) projects to reduce their development cost and increase technical innovativeness. When collaborating with other firms whose sought values are conflicts of interests, firms may behave uncooperatively leading to harmful impacts on the common goal. [Aim] This study explores how software firms both collaborate and compete in OSS projects. [Method] We adopted a mixed research method on three OSS projects. [Result] We found that commercial firms participating in community-initiated OSS projects collaborate in various ways across the organizational boundaries. While most of firms contribute little, a small number of firms that are very active and account for large proportions of contributions. We proposed a conceptual model to explain for coopetition among software firms in OSS projects. The model shows two aspects of coopetition can be managed at the same time based on firm gatekeepers. [Conclusion] Firms need to operationalize their coopetition strategies to maximize value gained from participating in OSS projects.

A Tool-Based Approach for Essentializing Software Engineering Practices

Software Engineers work using highly diverse methods and practices, and general theories in software engineering are lacking. A recent attempt at creating a common ground in the area of software engineering methodologies has been the Essence Theory of Software Engineering. Essence is a method-agnostic progress management framework and a meta-method for Software Engineering (SE). However, tooling for Essence is still lacking. Without dedicated tools and other instruments, a meta-method such as Essence is cumbersome to utilize by practitioners and students. Indeed, Essence currently suffers from a lack of widespread practitioner adoption. In this paper, we thus present an Open Source tool for essentializing methods and practices: Essencery. We conduct a qualitative evaluation of the tool through a quasi-formal experiment and a set of semi-structured interviews. Based on this data, we improve Essencery iteratively before it is utilized in a large-scale project-based course as a proof of concept.

Implementing Ethics in AI: An industrial multiple case study

Solutions in artificial intelligence (AI) are becoming increasingly widespread in system development endeavors. As the AI systems affect various stakeholders due to their unique nature, the growing influence of these systems calls for eth-ical considerations. Academic discussion and practical examples of autonomous system failures have highlighted the need for implementing ethics in software development. However, research on methods and tools for implementing ethics into AI system design and development in practice is still lacking. This paper be-gins to address this focal problem by providing a baseline for ethics in AI based software development. This is achieved by reporting results from an industrial multiple case study on AI systems development in the health care sector. In the context of this study, ethics were perceived as interplay of transparency, re-sponsibility and accountability, upon which research model is outlined. Through these cases, we explore the current state of practice out on the field in the ab-sence of formal methods and tools for ethically aligned design. Based on our data, we discuss the current state of practice and outline existing good practic-es, as well as suggest future research directions in the area.

Continuous experimentation on artificial intelligence software: a research agenda

Moving from experiments to industrial level AI software development requires a shift from understanding AI/ ML model attributes as a standalone experiment to know-how integrating and operating AI models in a large-scale software system. It is a growing demand for adopting state-of-the-art software engineering paradigms into AI development, so that the development efforts can be aligned with business strategies in a lean and fast-paced manner. We describe AI development as an “unknown unknown” problem where both business needs and AI models evolve over time. We describe a holistic view of an iterative, continuous approach to develop industrial AI software basing on business goals, requirements and Minimum Viable Products. From this, five areas of challenges are presented with the focus on experimentation. In the end, we propose a research agenda with seven questions for future studies.

Time for AI (Ethics) Maturity Model Is Now

There appears to be a common agreement that ethical concerns are of high importance when it comes to systems equipped with some sort of Artificial Intelligence (AI). Demands for ethical AI are declared from all directions. As a response, in recent years, public bodies, governments, and universities have rushed in to provide a set of principles to be considered when AI based systems are designed and used. We have learned, however, that high-level principles do not turn easily into actionable advice for practitioners. Hence, also companies are publishing their own ethical guidelines to guide their AI development. This paper argues that AI software is still software and needs to be approached from the software development perspective. The software engineering paradigm has introduced maturity model thinking, which provides a roadmap for companies to improve their performance from the selected viewpoints known as the key capabilities. We want to voice out a call for action for the development of a maturity model for AI software. We wish to discuss whether the focus should be on AI ethics or, more broadly, the quality of an AI system, called a maturity model for the development of AI systems.