Related papers: Are Comprehensive Quality Models Necessary for Eva…
Objective estimators of multimedia quality are often judged by comparing estimates with subjective "truth data," most often via Pearson correlation coefficient (PCC) or mean-squared error (MSE). But subjective test results contain noise, so…
Research shows, that the major issue in development of quality software is precise estimation. Further this estimation depends upon the degree of intricacy inherent in the software i.e. complexity. This paper attempts to empirically…
The research discusses how (open) data quality could be described, what should be considered developing a data quality management solution and how it could be applied to open data to check its quality. The proposed approach focuses on…
Quality and diversity are two critical metrics for the training data of large language models (LLMs), positively impacting performance. Existing studies often optimize these metrics separately, typically by first applying quality filtering…
The software development community has been using code quality metrics for the last five decades. Despite their wide adoption, code quality metrics have attracted a fair share of criticism. In this paper, first, we carry out a qualitative…
There is significant interest in developing evaluation metrics which accurately estimate the quality of generated text without the aid of a human-written reference text, which can be time consuming and expensive to collect or entirely…
Nowadays, quality definition, assessment, control and prediction cannot easily be missed in systems engineering. One common factor among these activities is quality quantification. Therefore, throughout this paper, the authors focus on the…
Recent advances in summary evaluation are based on model-based metrics to assess quality dimensions, such as completeness, conciseness, and faithfulness. However, these methods often require large language models, and predicted scores are…
In many contexts it is extremely costly to perform enough high quality experimental measurements to accurately parameterize a predictive quantitative model. However, it is often much easier to carry out large numbers of experiments that…
Assessing and predicting the complex concept of software quality is still challenging in practice as well as research. Activity-based quality models break down this complex con- cept into more concrete definitions, more precisely facts…
Seamless model based development aims to use models during all phases of the development process of a system. During the development process in a component-based approach, components of a system are described at qualitatively differing…
Text summarization models are often trained to produce summaries that meet human quality requirements. However, the existing evaluation metrics for summary text are only rough proxies for summary quality, suffering from low correlation with…
A good process model is expected not only to reflect the behavior of the process, but also to be as easy to read and understand as possible. Because preferences vary across different applications, numerous measures provide ways to reflect…
Automatic machine translation metrics typically rely on human translations to determine the quality of system translations. Common wisdom in the field dictates that the human references should be of very high quality. However, there are no…
Abstract- The vision of the Linked Open Data (LOD) initiative is to provide a distributed model for publishing and meaningfully interlinking open data. The realization of this goal depends strongly on the quality of the data that is…
Maintaining an acceptable level of quality of service in modern complex systems is challenging, particularly in the presence of various forms of uncertainty caused by changing execution context, unpredicted events, etc. Although…
In machine learning, research has traditionally focused on model development, with relatively less attention paid to training data. As model architectures have matured and marginal gains from further refinements diminish, data quality has…
Object-oriented software metrics provide a numerical characterization of software quality. They have also been used in the assessment and identification of technical debt. However, metrics generally need to be used with thresholds as…
Software development enterprises are under consistent pressure to improve their management techniques and development processes. These are comprised of several disciplines like requirements acquisition, design, coding, testing, etc. that…
Many problems related to the quality of requirements arise during elicitation and specification activities since they are written in natural language. The flexibility and inherent nature of language make requirements prone to…