相关论文: SQAPlanner: Generating Data-Informed Software Qual…
Software Quality Assurance (SQA) is critical for delivering reliable, secure, and efficient software products. The Software Quality Assurance Process aims to provide assurance that work products and processes comply with predefined…
Software Quality Assurance (SQA) Engineers are responsible for assessing a product during every phase of the software development process to ensure that the outcomes of each phase and the final product possess the desired qualities. In…
Context: Software Quality Assurance (SQA) is a fundamental part of software engineering to ensure stakeholders that software products work as expected after release in operation. Machine Learning (ML) has proven to be able to boost SQA…
Signal quality assessment (SQA) is required for monitoring the reliability of data acquisition systems, especially in AI-driven Predictive Maintenance (PMx) application contexts. SQA is vital for addressing "silent failures" of data…
Quality assurance makes sure the project will be completed based on the previously approved specifications, standards and functionality. It is required without defects and possible problems. It monitors and tries to progress the development…
Planning quality assurance (QA) activities in a systematic way and controlling their execution are challenging tasks for companies that develop software or software-intensive systems. Both require estimation capabilities regarding the…
Traditional quality assurance (QA) methods face significant challenges in addressing the complexity, scale, and rapid iteration cycles of modern software systems and are strained by limited resources available, leading to substantial costs…
A software architect uses quality requirements to design the architecture of a system. However, it is essential to ensure that the system's final architectural design achieves the standard quality requirements. The existing architectural…
Accurately predicting faulty software units helps practitioners target faulty units and prioritize their efforts to maintain software quality. Prior studies use machine-learning models to detect faulty software code. We revisit past studies…
Speech quality assessment (SQA) refers to the evaluation of speech quality, and developing an accurate automatic SQA method that reflects human perception has become increasingly important, in order to keep up with the generative AI boom.…
Speech quality assessment (SQA) aims to predict the perceived quality of speech signals under a wide range of distortions. It is inherently connected to speech enhancement (SE), which seeks to improve speech quality by removing unwanted…
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…
The complexity of software is increasing day by day the requirement and need for a verity of softwareproducts increases, this necessitates the provision of a strong tool that will make a balance betweenproduction and quality. The practice…
Over the last years, machine learning techniques have been applied to more and more application domains, including software engineering and, especially, software quality assurance. Important application domains have been, e.g., software…
In the product business still battles with the hard assignment of creating programming applications that meet quality gauges, and spending limitations. The requirement for programming to be without mistake remained a test to the IT…
Quality assurance (QA) tools are receiving more and more attention and are widely used by developers. Given the wide range of solutions for QA technology, it is still a question of evaluating QA tools. Most existing research is limited in…
Background: Accessing relevant data on the product, process, and usage perspectives of software as well as integrating and analyzing such data is crucial for getting reliable and timely actionable insights aimed at continuously managing…
Software quality research increasingly relies on large-scale datasets that measure both the product and process aspects of software systems. However, existing resources often focus on limited dimensions, such as code smells, technical debt,…
Software defects consume 40% of the total budget in software development and cost the global economy billions of dollars every year. Unfortunately, despite the use of many software quality assurance (SQA) practices in software development…
Predicting the number of defects in a project is critical for project test managers to allocate budget, resources, and schedule for testing, support and maintenance efforts. Software Defect Prediction models predict the number of defects in…