Related papers: Test Smell: A Parasitic Energy Consumer in Softwar…
Background: Research software plays an important role in solving real-life problems, empowering scientific innovations, and handling emergency situations. Therefore, the correctness and trustworthiness of research software are of absolute…
Accurate and reliable measurement of energy consumption is critical for making well-informed design choices when choosing and training large scale NLP models. In this work, we show that existing software-based energy measurements are not…
Code samples play a pivotal role in open-source ecosystems (OSSECO), serving as lightweight artifacts that support knowledge transfer, onboarding, and framework adoption. Despite their instructional relevance, these samples are often…
The optimisation of software energy consumption is of growing importance across all scales of modern computing, i.e., from embedded systems to data-centres. Practitioners in the field of Search-Based Software Engineering and Genetic…
Software testing is crucial for ensuring software quality, yet developers' engagement with it varies widely. Identifying the technical, organizational and social factors that lead to differences in engagement is required to remove barriers…
Architectural decay imposes real costs in terms of developer effort, system correctness, and performance. Over time, those problems are likely to be revealed as explicit implementation issues (defects, feature changes, etc.). Recent…
Defect prediction models can be beneficial to prioritize testing, analysis, or code review activities, and has been the subject of a substantial effort in academia, and some applications in industrial contexts. A necessary precondition when…
Technology use has grown rapidly in recent years. It is infused in virtually every aspect of organizational and individual life. This technology runs on servers, typically in data centers. As workloads grow, more serves are required. Each…
Energy consumption is a growing concern in several fields, from mobile devices to large data centers. Developers need detailed data on the energy consumption of their software to mitigate consumption issues. Previous approaches have a…
Building energy efficient software is an increasingly important task for mobile developers. However, a cumulative body of knowledge of techniques that support this goal does not exist. We conduct a systematic literature review to gather…
The scale of scientific High Performance Computing (HPC) and High Throughput Computing (HTC) has increased significantly in recent years, and is becoming sensitive to total energy use and cost. Energy-efficiency has thus become an important…
Improving software performance through configuration parameter tuning is a common activity during software maintenance. Beyond traditional performance metrics like latency, mobile app developers are interested in reducing app energy usage.…
Unlike most other software quality attributes, testability cannot be evaluated solely based on the characteristics of the source code. The effectiveness of the test suite and the budget assigned to the test highly impact the testability of…
Software testing is a critical element of software quality assurance and represents the ultimate review of specification, design and coding. Software testing is the process of testing the functionality and correctness of software by running…
The low cost and rapid provisioning capabilities have made open-source cloud a desirable platform to launch industrial applications. However, as open-source cloud moves towards maturity, it still suffers from quality issues like code…
Test smells indicate poor development practices in test code, reducing maintainability and reliability. While developers often struggle to prevent or refactor these issues, existing tools focus primarily on detection rather than automated…
Code smells indicate the potential problems of software quality so that developers can identify refactoring opportunities by detecting code smells. State-of-the-art approaches leverage heuristics, machine learning, and deep learning to…
The accuracy reported for code smell-detecting tools varies depending on the dataset used to evaluate the tools. Our survey of 45 existing datasets reveals that the adequacy of a dataset for detecting smells highly depends on relevant…
This study addresses the challenge of detecting code smells in large-scale software systems using machine learning (ML). Traditional detection methods often suffer from low accuracy and poor generalization across different datasets. To…
Test smells are coding issues that typically arise from inadequate practices, a lack of knowledge about effective testing, or deadline pressures to complete projects. The presence of test smells can negatively impact the maintainability and…