Software Quality Assurance: The underlying framework for achieving secure and reliable software systems

1996 ◽  
pp. 467-474
Author(s):  
Stelios A. Frangos
Keyword(s):  
Quality Assurance ◽  
Software Quality ◽  
Software Quality Assurance ◽  
Software Systems ◽  
Reliable Software

scholarly journals AI for Software Quality Assurance Blue Sky Ideas Talk

2020 ◽  
Vol 34 (09) ◽  
pp. 13529-13533
Author(s):  
Meir Kalech ◽  
Roni Stern
Keyword(s):  
Quality Assurance ◽  
Software Quality ◽  
Test Generation ◽  
Machine Learning Techniques ◽  
Software Quality Assurance ◽  
Software Systems ◽  
Automated Test Generation ◽  
Root Cause ◽  
Test Execution ◽  
Learning Techniques

Modern software systems are highly complex and often have multiple dependencies on external parts such as other processes or services. This poses new challenges and exacerbate existing challenges in different aspects of software Quality Assurance (QA) including testing, debugging and repair. The goal of this talk is to present a novel AI paradigm for software QA (AI4QA). A quality assessment AI agent uses machine-learning techniques to predict where coding errors are likely to occur. Then a test generation AI agent considers the error predictions to direct automated test generation. Then a test execution AI agent executes tests, that are passed to the root-cause analysis AI agent, which applies automatic debugging algorithms. The candidate root causes are passed to a code repair AI agent that tries to create a patch for correcting the isolated error.

scholarly journals Software Archeology: A Case Study in Software Quality Assurance and Design

2009 ◽  
Author(s):  
Cameron J. Turner ◽  
John M. MacDonald ◽  
Jane A. Lloyd
Keyword(s):  
Quality Assurance ◽  
Software Quality ◽  
National Laboratory ◽  
Quality Assurance Program ◽  
Software Quality Assurance ◽  
Software Systems ◽  
Legacy Systems ◽  
Los Alamos National Laboratory ◽  
Legacy Software

Ideally, quality is designed into software, just as quality is designed into hardware. However, when dealing with legacy systems, demonstrating that the software meets required quality standards may be difficult to achieve. Evolving customer needs, expressed by new operational requirements, resulted in the need to develop a legacy software quality assurance program at Los Alamos National Laboratory (LANL). This need led to the development of a reverse engineering approach referred to as software archaeology. This paper documents the software archaeology approaches used at LANL to demonstrate the software quality in legacy software systems. A case study for the Robotic Integrated Packaging System (RIPS) software is included to describe our approach.

Matrix-based component dependence representation and its applications in software quality assurance

2005 ◽  
Vol 40 (11) ◽  
pp. 29-36 ◽  
Author(s):  
Bixin Li ◽  
Ying Zhou ◽  
Yancheng Wang ◽  
Junhui Mo
Keyword(s):  
Quality Assurance ◽  
Software Quality ◽  
Software Quality Assurance

Benchmarking PRAISE-CANDU 1.0 With xLPR 1.0

2013 ◽  
Author(s):  
Min Wang ◽  
Xinjian Duan ◽  
Michael J. Kozluk
Keyword(s):  
Quality Assurance ◽  
Pilot Study ◽  
Fracture Mechanics ◽  
Software Quality ◽  
Verification And Validation ◽  
Quality Assurance Program ◽  
Software Quality Assurance ◽  
Full Compliance ◽  
Low Probability ◽  
State Of Art

A probabilistic fracture mechanics code, PRAISE-CANDU 1.0, has been developed under a software quality assurance program in full compliance with CSA N286.7-99, and was initially released in 2012 June. Extensive verification and validation has been performed on PRAISE-CANDU 1.0 for the purpose of software quality assurance. This paper presents the benchmarking performed between PRAISE-CANDU 1.0 and xLPR (eXtremely Low Probability of Rupture) version 1.0 using the cases from the xLPR pilot study. The xLPR code was developed in a configuration management and quality assured manner. Both codes adopted a state-of-art code architecture for the treatment of the uncertainties. Inputs to the PRAISE-CANDU were established as close as possible to those used in corresponding xLPR cases. Excellent agreement has been observed among the results obtained from the two PFM codes in spite of some differences between the codes. This benchmarking is considered to be an important element of the validation of PRAISE-CANDU.

Sign in / Sign up

Export Citation Format

Share Document