Related papers: Customer Validation, Feedback and Collaboration in…
Large Language Models (LLMs) have shown great potential in automating software testing tasks, including test generation. However, their rapid evolution poses a critical challenge for companies implementing DevSecOps - evaluations of their…
When interacting with their software systems, users may have to deal with problems like crashes, failures, and program instability. Faulty software running in the field is not only the consequence of ineffective in-house verification and…
DevOps is a cultural movement that aims the collaboration of all the stakeholders involved in the development, deployment and operation of soft-ware to deliver a quality product or service in the shortest possible time. DevOps is relatively…
In the ever-evolving field of Deep Learning (DL), ensuring project quality and reliability remains a crucial challenge. This research investigates testing practices within DL projects in GitHub. It quantifies the adoption of testing…
User feedback has grown in importance for organizations to improve software products. Prior studies focused primarily on feedback collection and reported a high-level overview of the processes, often overlooking how practitioners reason…
The development process of scientific applications is largely dependent on scientific progress and the experimental research results. Thus, dealing with frequent changes is one of the main problems faced by the developers of scientific…
Model driven development is an effective method due to its benefits such as code transformation, increasing productivity and reducing human based error possibilities. Meanwhile, agile software development increases the software flexibility…
This study explores the application of deep learning technologies in software development processes, particularly in automating code reviews, error prediction, and test generation to enhance code quality and development efficiency. Through…
This paper considers how a formal mathematically-based model can be used in support of evolutionary software development, and in particular how such a model can be kept consistent with the implementation as it changes to meet new…
Continuous Integration and Continuous Deployment (CI/CD) pipeline automates software development to speed up and enhance the efficiency of engineering software. These workflows consist of various jobs, such as code validation and testing,…
Context: The complexity of modern safety-critical systems in industries keep on increasing due to the rising number of features and functionalities. This calls for formal methods in order to entrust confidence in such systems. Nevertheless,…
Integrating security activities into the software development lifecycle to detect security flaws is essential for any project. These activities produce reports that must be managed and looped back to project stakeholders like developers to…
Development effort is an undeniable part of the project management which considerably influences the success of project. Inaccurate and unreliable estimation of effort can easily lead to the failure of project. Due to the special…
A large number of computational scientific research projects make use of open source software packages. However, the development process of such tools frequently differs from conventional software development; partly because of the nature…
User experience (UX) has undergone a revolution in collaborative practices, due to tools that enable quick feedback and continuous collaboration with a varied team across a design's lifecycle. However, it is unclear how this shift in…
The use of agile principles and practices in software development is becoming a powerful force in today's workplace. In our quest to develop better products, therefore, it is imperative that we strive to learn and understand the application…
Successful software projects depend on the quality of software requirements. Creating high-quality requirements is a crucial step toward successful software development. Effective support in this area can significantly reduce development…
The technology of formal software verification has made spectacular advances, but how much does it actually benefit the development of practical software? Considerable disagreement remains about the practicality of building systems with…
Researchers have been highly active to investigate the classical machine learning workflow and integrate best practices from the software engineering lifecycle. However, deep learning exhibits deviations that are not yet covered in this…
Context: Domain-Driven Design (DDD) has gained significant attention in software development for its potential to address complex software challenges, particularly in the areas of system refactoring, reimplementation, and adoption. Using…