Related papers: Customer Validation, Feedback and Collaboration in…
Effective issue resolution is crucial for maintaining software quality. Yet developers frequently encounter challenges such as low-quality issue reports, limited understanding of real-world workflows, and a lack of automated support. This…
DevOps is a collaborative and multidisciplinary organizational effort to automate continuous delivery of new software updates while guaranteeing their correctness and reliability. The present survey investigates and discusses DevOps…
Industry in all sectors is experiencing a profound digital transformation that puts software at the core of their businesses. In order to react to continuously changing user requirements and dynamic markets, companies need to build robust…
We see that the collaborative and participatory nature of software development continues to evolve, shape and be shaped by communication channels that are used by developer communities of practice--both by traditional communication channels…
It can be insightful to extend qualitative studies with a secondary quantitative analysis (where the former suggests insightful questions that the latter can answer). Documenting developer beliefs should be the start, not the end, of…
In large scale agile systems development, the lack of a unified requirements engineering (RE) process is a major challenge, exacerbated by the absence of high level guiding principles for effective requirements management. To address this…
Purpose: Continuous Software Engineering (CSE) promises improved efficiency, quality, and responsiveness in software-intensive organizations. However, fully adopting CSE is often constrained by complex products, legacy systems,…
Context: Continuous integration (CI) is a software engineering technique that proclaims a set of frequent activities to assure the health of the software product. Researchers and practitioners mention several benefits related to CI.…
Purpose: The introduction of artificial intelligence / machine learning (AI/ML) products to the regulated fields of pharmaceutical research and development (R&D) and drug manufacture, and medical devices (MD) and in-vitro diagnostics (IVD),…
Real-world software applications must constantly evolve to remain relevant. This evolution occurs when developing new applications or adapting existing ones to meet new requirements, make corrections, or incorporate future functionality.…
Deep-Learning(DL) applications have been widely employed to assist in various tasks. They are constructed based on a data-driven programming paradigm that is different from conventional software applications. Given the increasing popularity…
Deep learning (DL) becomes increasingly pervasive, being used in a wide range of software applications. These software applications, named as DL based software (in short as DL software), integrate DL models trained using a large data corpus…
Background: It has long been suggested that user feedback, typically written in natural language by end-users, can help issue detection. However, for large-scale online service systems that receive a tremendous amount of feedback, it…
Converting customer survey feedback data into usable insights has always been a great challenge for large software enterprises. Despite the improvements on this field, a major obstacle often remains when drawing the right conclusions out of…
The introduction of machine learning (ML) components in software projects has created the need for software engineers to collaborate with data scientists and other specialists. While collaboration can always be challenging, ML introduces…
As part of our larger research effort to improve support for diverse end user human-centric aspects during software development, we wanted to better understand how developers currently go about addressing these challenging human-centric…
It is well known that the software process in place impacts the quality of the resulting product. However, the specific way in which this effect occurs is still mostly unknown and reported through anecdotes. To gather a better understanding…
DevOps (development and operations), has significantly changed the way to overcome deficiencies for delivering high-quality software to production environments. Past years witnessed an increased interest in embedding DevOps with…
Deep learning (DL) has become a key component of modern software. In the "big model" era, the rich features of DL-based software substantially rely on powerful DL models, e.g., BERT, GPT-3, and the recently emerging GPT-4, which are trained…
Software testing is a crucial phase in the software development lifecycle (SDLC), ensuring that products meet necessary functional, performance, and quality benchmarks before release. Despite advancements in automation, traditional methods…