Software Testing and Quality Assurance on Sampling Inspection through Statistical Learning Theory
نویسنده
چکیده
In this paper, an engineering statistical model is proposed for the prediction of control and assurance in software engineering. This paper attempt statistical learning theory is to studies in a framework the properties of learning theory based on software engineering in quality testing using acceptance sampling statistical quality control and software testing and quality assurance on sampling inspection through
منابع مشابه
Factors Affecting Quality Assurance of Learning in Universities; a case in the Petroleum University of Technology
The purpose of the present study was to prioritize the main and sub-factors that affecting learning quality assurance in universities and higher education institutes in the case of Petroleum University of Technology (PUT). The statistical population of this study consisted of experts (professors, managers and staff) and students of PUT. Twenty one experts were identified and interviewed to dete...
متن کاملAssurance of Software Quality
This paper commences with a detailed Software Inspection is a method of static testing to discussion of the problems and difficulties associverify that software meets its requirements. It enated with software testing. It is shown that large gages the developers and others in a formal process software systems are so complex that software comof investigation that usually detects more defects in p...
متن کاملIntegration of Analytical Quality Assurance Methods into Agile Software Construction Practice Research Proposal for a Family of Controlled Experiments
Defects in early software development products, e.g., design specifications, can have a major impact on product quality. Analytical quality assurance methods, like Software Inspections and Testing are common practices for detecting non-conformities in software products. Often, these quality assurance (QA) activities are not seen as integral part of software construction process but rather as ti...
متن کاملExploiting Machine Learning Techniques for the Enhancement of Acceptance Sampling
This paper proposes an innovative methodology for Acceptance Sampling by Variables, which is a particular category of Statistical Quality Control dealing with the assurance of products quality. Our contribution lies in the exploitation of machine learning techniques to address the complexity and remedy the drawbacks of existing approaches. More specifically, the proposed methodology exploits Ar...
متن کاملEffective Defect Prevention Approach in Software Process for Achieving Better Quality Levels
Defect prevention is the most vital but habitually neglected facet of software quality assurance in any project. If functional at all stages of software development, it can condense the time, overheads and wherewithal entailed to engineer a high quality product. The key challenge of an IT industry is to engineer a software product with minimum post deployment defects. This effort is an analysis...
متن کامل