搜索结果：Develop

Software development builds digital tools to automate processes, yet its initial phases, up to deployment, remain largely manual. There are two reasons: Development tasks are often under-specified and transitions between tasks usually require a translator. These reasons are mutually reinforcing: it makes little sense to specify tasks when you cannot connect them and writing a translator requires a specification. LLMs change this cost equation: they can handle under-specified systems and they excel at translation. Thus, they can act as skeleton keys that unlock the automation of tasks and transitions that were previously too expensive to interlink. We introduce a recipe for writing development workflows as software (polymer) to further automate the initial phases of development. We show how adopting polymer at Volvo, a large automotive manufacturer, to automate testing saved 2--3 FTEs at the cost of two months to develop and deploy. We close with open challenges when polymerizing development workflows.

The operation of humanoid robotics is an essential field of research with many practical and competitive applications. Many of these systems, however, do not invest heavily in developing a non-expert-centered graphical user interface (GUI) for operation. The focus of this research is to develop a scalable GUI that is tailored to be simple and intuitive so non-expert operators can control the robot through a FIRA-regulated obstacle course. Using common practices from user interface development (UI) and understanding concepts described in human-robot interaction (HRI) and other related concepts, we will develop a new interface with the goal of a non-expert teleoperation system.

This paper serves as a practical guide for individuals and organisations seeking to design, implement, and evaluate astronomy-for-development initiatives, as well as those preparing proposals for the International Astronomical Union's Office of Astronomy for Development (IAU OAD) annual Call for Proposals. The paper aims to outline how systematic evidence collection can strengthen project design, enhance accountability, and increase the likelihood of measurable impact. It explains the distinction between monitoring and evaluation, provides guidance on when and how evaluation should be undertaken, and summarises key evaluation types - process, feasibility, impact, outcome, economic, and summative, relevant to astronomy-based interventions. In addition to conceptual discussion, the paper presents a set of practical steps, reflective questions, and examples to help project teams develop a clear theory of change, define appropriate indicators, and anticipate risks and unintended consequences. By contextualising M&E within the broader goals of the OAD and the Sustainable Development Goals (SDGs), this work aims to empower practitioners to create evidence-informed, community-driven,

Category theory is the language of homological algebra, allowing us to state broadly applicable theorems and results without needing to specify the details for every instance of analogous objects. However, authors often stray from the realm of pure abstract category theory in their development of the field, leveraging the Freyd-Mitchell embedding theorem or similar results, or otherwise using set-theoretic language to augment a general categorical discussion. This paper seeks to demonstrate that - while it is not necessary for most mathematicians' purposes - a development of homological concepts can be contrived from purely categorical notions. We begin by outlining the categories we will work within, namely Abelian categories (building off additive categories). We continue to develop cohomology groups of sequences, eventually culminating in a development of right derived functors. This paper is designed to be a minimalist construction, supplying no examples or motivation beyond what is necessary to develop the ideas presented.

As Large Language Models (LLMs), including ChatGPT and analogous systems, continue to advance, their robust natural language processing capabilities and diverse applications have garnered considerable attention. Nonetheless, despite the increasing acknowledgment of the convergence of Artificial Intelligence (AI) and Software Engineering (SE), there is a lack of studies involving the impact of this convergence on the practices and perceptions of software developers. Understanding how software developers perceive and engage with AI tools, such as ChatGPT, is essential for elucidating the impact and potential challenges of incorporating AI-driven tools in the software development process. In this paper, we conducted a survey with 207 software developers to understand the impact of ChatGPT on software quality, productivity, and job satisfaction. Furthermore, the study delves into developers' expectations regarding future adaptations of ChatGPT, concerns about potential job displacement, and perspectives on regulatory interventions.

Agile methods have transformed the way software is developed, emphasizing active end-user involvement, tolerance to change, and evolutionary delivery of products. The first special issue on agile development described the methods as focusing on "feedback and change". These methods have led to major changes in how software is developed. Scrum is now the most common framework for development in most countries, and other methods like extreme programming (XP) and elements of lean software development and Kanban are widely used. What started as a bottom-up movement amongst software practitioners and consultants has been taken up by major international consulting companies who prescribe agile development, particularly for contexts where learning and innovation are key. Agile development methods have attracted interest primarily in software engineering, but also in a number of other disciplines including information systems and project management. The agile software development methods were originally targeted towards small, co-located development teams, but are increasingly applied in other contexts. They were initially used to develop Web systems and internal IT systems, but are now use

Test-driven Development (TDD) is an incremental approach to software development. Despite it is claimed to improve both quality of software and developers' productivity, the research on the claimed effects of TDD has so far shown inconclusive results. Some researchers have ascribed these inconclusive results to the negative affective states that TDD would provoke. A previous (baseline) experiment has, therefore, studied the affective reactions of (novice) developers---i.e., 29 third-year undergraduates in Computer Science (CS)---when practicing TDD to implement software. To validate the results of the baseline experiment, we conducted a replicated experiment that studies the affective reactions of novice developers when applying TDD to develop software. Developers in the treatment group carried out a development task using TDD, while those in the control group used a non-TDD approach. To measure the affective reactions of developers, we used the Self-Assessment Manikin instrument complemented with a liking dimension. The most important differences between the baseline and replicated experiments are: (i) the kind of novice developers involved in the experiments---third-year vs. seco

The Winograd Schema Challenge (WSC), a seemingly well-thought-out test for machine intelligence, has been proposed to shed light on developing systems that exhibit human behavior. Since its introduction, it aimed to pivot the focus of the AI community from the technology to the science of AI. While common and trivial for humans, studies show that it is still challenging for machines, especially when they have to deal with novel schemas, that is, well-designed sentences that require the resolving of definite pronouns. As researchers have become increasingly interested in the challenge itself, this presumably necessitates the availability of an extensive collection of Winograd schemas, which goes beyond what human experts can reasonably develop themselves, especially after proposed ways of utilizing them as novel forms of CAPTCHAs. To address this necessity, we propose a novel framework that explicitly focuses on how humans and machines can collaborate as teammates to design novel schemas from scratch. This is being accomplished by combining two recent studies from the literature: i) Winventor, a machine-driven approach for the development of large amounts of Winograd schemas, albeit

To improve the quality of programs we provide an approach to guidance in the process of program development. At the higher level the various activities and their dependencies to structure the process are identified. At the lower level, detailed, practical rules are given for the decision-making in the development steps during these activities. The approach concentrates on structure and behavior of a single class. It includes design and specification and is compatible with methodologies for programming in the large. Informal specifications are introduced to help develop correct and robust code as well as corresponding tests. A strict distinction is made between external design and specification on one hand and internal design and specification on the other hand, which helps in keeping control over complexity. The approach also exploits the separation of success and failure scenarios. A worked-out example is provided.

Dynamic program analysis (also known as profiling) is well-known for its powerful capabilities of identifying performance inefficiencies in software packages. Although a large number of dynamic program analysis techniques are developed in academia and industry, very few of them are widely used by software developers in their regular software developing activities. There are three major reasons. First, the dynamic analysis tools (also known as profilers) are disjoint from the coding environments such as IDEs and editors; frequently switching focus between them significantly complicates the entire cycle of software development. Second, mastering various tools to interpret their analysis results requires substantial efforts; even worse, many tools have their own design of graphical user interfaces (GUI) for data presentation, which steepens the learning curves. Third, most existing tools expose few interfaces to support user-defined analysis, which makes the tools less customizable to fulfill diverse user demands. We develop EasyView, a general solution to integrate the interpretation and visualization of various profiling results in the coding environments, which bridges software dev

To build secure software, developers often work together during software development and maintenance to find, fix, and prevent security vulnerabilities. Examining the nature of developer interactions during their security activities regarding security introducing and fixing activities can provide insights for improving current practices. In this work, we conduct a large-scale empirical study to characterize and understand developers' interactions during their security activities regarding security introducing and fixing, which involves more than 16K security fixing commits and over 28K security introducing commits from nine large-scale open-source software projects. For our analysis, we first examine whether a project is a hero-centric project when assessing developers' contribution in their security activities. Then we study the interaction patterns between developers, explore how the distribution of the patterns changes over time, and study the impact of developers' interactions on the quality of projects. In addition, we also characterize the nature of developer interaction in security activities in comparison to developer interaction in non-security activities (i.e., introducin

In this research paper of secure software systems, authors have discussed what the proper development process is when it comes to creating a secure software, which will be suited for developers and relevent stakeholders alike. Secure Software Development Process for Developers is of crucial importance for software engineers as more and more software-based devices are becoming commonly available, and cloud services are evolving which require for the software to be constantly connected to the internet. With this in mind, Secure Software Development needs to be transformed to something most developers can rely upon to make applied software safe and have the capability to mitigate against potential attacks by hackers. Furthermore, in this paper, existing Secure Software Development Process ideas and implementations are reviewed and investigated using the research paper pool available online. Thereafter, an approach is proposed to enhance the security aspect in software development process to resolve security issues. Lastly, the paper concludes with final remarks on practical implementation of security features in software development phases for production of secure and reliable softwar

Computer system creativity is a key step on the pathway to artificial general intelligence (AGI). It is elusive, however, due to the fact that human creativity is not fully understood and, thus, it is difficult to develop this capability in software. Large language models (LLMs) provide a facsimile of creativity and the appearance of sentience, while not actually being either creative or sentient. While LLMs have created bona fide new content, in some cases - such as with harmful hallucinations - inadvertently, their deliberate creativity is seen by some to not match that of humans. In response to this challenge, this paper proposes a technique for enhancing LLM output creativity via an iterative process of concept injection and refinement. Initial work on the development of the Creative Artificial Intelligence through Recurring Developments and Determinations (CAIRDD) system is presented and the efficacy of key system components is evaluated.

The use of software applications is inevitable as they provide different services to users. The software applications collect, store users' data, and sometimes share with the third party, even without the user consent. One can argue that software developers do not implement privacy into the software applications they develop or take GDPR (General Data Protection Law) law into account. Failing to do this, may lead to software applications that open up privacy breaches (e.g. data breach). The GDPR law provides a set of guidelines for developers and organizations on how to protect user data when they are interacting with software applications. Previous research has attempted to investigate what hinders developers from embedding privacy into software systems. However, there has been no detailed investigation on why they cannot develop privacy-preserving systems taking GDPR into consideration, which is imperative to develop software applications that preserve privacy. Therefore, this paper investigates the issues that hinder software developers from implementing software applications taking GDPR law on-board. Our study findings revealed that developers are not familiar with GDPR princip

To perform their daily tasks, developers intensively make use of existing resources by consulting open-source software (OSS) repositories. Such platforms contain rich data sources, e.g., code snippets, documentation, and user discussions, that can be useful for supporting development activities. Over the last decades, several techniques and tools have been promoted to provide developers with innovative features, aiming to bring in improvements in terms of development effort, cost savings, and productivity. In the context of the EU H2020 CROSSMINER project, a set of recommendation systems has been conceived to assist software programmers in different phases of the development process. The systems provide developers with various artifacts, such as third-party libraries, documentation about how to use the APIs being adopted, or relevant API function calls. To develop such recommendations, various technical choices have been made to overcome issues related to several aspects including the lack of baselines, limited data availability, decisions about the performance measures, and evaluation approaches. This paper is an experience report to present the knowledge pertinent to the set of r

This paper argues that modelling the development methodologies can improve the multi-agents systems software engineering. Such modelling allows applying methods, techniques and practices used in the software development to the methodologies themselves. The paper discusses then the advantages of the modelling of development methodologies. It describes a model of development methodologies, uses such a model to develop a system of their partial validation, and applies such a system to multi-agent methodologies. Several benefits can be gained from such modelling, such as the improvement of the works on the development, evaluation and comparison of multi-agent development methodologies.

Low/No-code development is a software development method that provides users with a platform for visually creating applications with little or no coding. Companies and organizations need software applications and information systems for various business purposes like management in the technology era. Low/No-code development gives non-IT professionals a convenient tool for rapidly building simple business applications they need without or with little coding. In this paper, we explored the benefits & limitations of Low/No-Code development and modern Low/No-Code development platforms in the industry. In addition, we analyzed how it can be improved and prospected the impacts of Low/No-Code development on society and related industries in the future. In conclusion, we find that Low/No-code development is a promising trend that can significantly impact future software development and digital transformation.

A new workflow for software development (proof-driven development) is presented. An extension of test-driven development, the new workflow utilizes the paradigm of dependently typed programming. The differences in design, complexity and provability of software are discussed, based on the technique used to create the system. Furthermore, the difference in what properties can be expressed in a proof-driven development workflow versus a traditional test-driven development workflow or using test-last development.

With recent advances in the development of more powerful quantum computers, the research area of quantum software engineering is emerging, having the goal to provide concepts, principles, and guidelines to develop high-quality quantum applications. In classical software engineering, lifecycles are used to document the process of designing, implementing, maintaining, analyzing, and adapting software. Such lifecycles provide a common understanding of how to develop and operate an application, which is especially important due to the interdisciplinary nature of quantum computing. Since today`s quantum applications are, in most cases, hybrid, consisting of quantum and classical programs, the lifecycle for quantum applications must involve the development of both kinds of programs. However, the existing lifecycles only target the development of quantum or classical programs in isolation. Additionally, the various programs must be orchestrated, e.g., using workflows. Thus, the development of quantum applications also incorporates the workflow lifecycle. In this chapter, we analyze the software artifacts usually comprising a quantum application and present their corresponding lifecycles.