Related papers: Testability Measurement Model for Object Oriented …
Product metrics, such as size or complexity, are often used to identify defect-prone parts or to focus quality assurance activities. In contrast, quality information that is available early, such as information provided by inspections, is…
Undeniably, the advent of mobile applications has brought new frontiers to usability engineering. To date, ongoing research has shown significant efforts to adopt and adapt usability principles to the mobile computing environment. One of…
\textit{Background:} The use of large language models in software testing is growing fast as they support numerous tasks, from test case generation to automation, and documentation. However, their adoption often relies on informal…
Given a set of pre-trained models, how can we quickly and accurately find the most useful pre-trained model for a downstream task? Transferability measurement is to quantify how transferable is a pre-trained model learned on a source task…
Software quality-in-use comprehends the quality from user's perspectives. It has gained its importance in e-learning applications, mobile service based applications and project management tools. User's decisions on software acquisitions are…
This paper describes first results from the AutoMoDe (Automotive Model-Based Development) project. The overall goal of the project is to develop an integrated methodology for model-based development of automotive control software, based on…
The workshop is devoted to model-based testing of both software and hardware. Model-based testing uses models describing the required behavior of the system under consideration to guide such efforts as test selection and test results…
Validation is one of the software engineering disciplines that help build quality into software. The major objective of software validation process is to determine that the software performs its intended functions correctly and provide…
The assumption of no unmeasured confounders is a critical but unverifiable assumption required for causal inference yet quantitative sensitivity analyses to assess robustness of real-world evidence remains underutilized. The lack of use is…
Reliability prediction is crucial for ensuring the safety and security of software systems, especially in the context of industry practices. While various metrics and measurements are employed to assess software reliability, the complexity…
Test case maintainability is an important concern, especially in open source and distributed development environments where projects typically have high contributor turnover with varying backgrounds and experience, and where code ownership…
Despite its importance, software testing is, arguably, the least understood part of the software life cycle and still the toughest to perform correctly. Many researchers and practitioners have been working to address the situation. However,…
Software quality is critical in modern software engineering, especially in large and evolving codebases. This study analyzes the evolution of software quality metrics in five successive versions of the open-source Java testing framework…
This research describes the initial effort of building a prediction model for defects in system testing carried out by an independent testing team. The motivation to have such defect prediction model is to serve as early quality indicator…
Context: Modern software development increasingly relies on software testing for an ever more frequent delivery of high quality software. This puts high demands on the quality of the central artifacts in software testing, test suites and…
Background. Defect prediction has been a highly active topic among researchers in the Empirical Software Engineering field. Previous literature has successfully achieved the most accurate prediction of an incoming fault and identified the…
Machine learning (ML) - based software systems are rapidly gaining adoption across various domains, making it increasingly essential to ensure they perform as intended. This report presents best practices for the Test and Evaluation (T&E)…
A/B testing is gaining attention in the automotive sector as a promising tool to measure causal effects from software changes. Different from the web-facing businesses, where A/B testing has been well-established, the automotive domain…
In safety-critical deep learning applications, robustness measures the ability of neural models that handle imperceptible perturbations in input data, which may lead to potential safety hazards. Existing pre-deployment robustness assessment…
The complexity of software in embedded systems has increased significantly over the last years so that software verification now plays an important role in ensuring the overall product quality. In this context, SAT-based bounded model…