Software Quality Requirements

As software systems continue to grow more complex, evaluating software quality becomes increasingly critical. This study analyzes existing software quality models, including McCall, Boehm, FURPS, and ISO Systems and Software Engineering – Systems and Software Quality Requirements and Evaluation (SQuaRE), with a specific focus on the ISO/IEC 25010:2023 standard. The research aims to assess the completeness of these models and explore interdependencies among key quality attributes relevant to software requirements engineering. The paper identifies key characteristics and associated metrics based on ISO/IEC standards using comparative analysis and a literature review. Findings show that ISO/IEC 25010:2023 provides the most comprehensive structure, with Functional Suitability and Compatibility identified as essential due to their universally recommended metrics. Survey data from 328 practicing analysts in Ukraine and internationally demonstrate a gap between theoretical models and real-world requirements documentation practices, particularly for non-functional requirements. The identified dependencies between quality attributes enable a more integrated and structured approach to identifying and analyzing non-functional requirements in IT projects. The study emphasizes that software quality models must be tailored to project-specific goals and constraints, with attention to trade-offs and stakeholder needs during the requirements specification, prioritization, and validation processes. The findings support the adaptation of quality models to specific project constraints and emphasize the business analyst’s role in tailoring quality criteria for practical use in software development.

The advancements in the technology landscape and software development in recent years mandate paying attention to Software Quality Assurance (SQA) because it is becoming significantly important and complex. SQA is a set of activities within the software development lifecycle that aims at reducing development and testing costs, improving the quality of the software systems, and increasing customer satisfaction. Thus, the objective of this paper is to build a SQA maturity model, particularly in the telecommunication industry. To achieve this, this research identified perspectives and factors based on a comprehensive literature review and experts’ inputs using Hierarchical Decision Modeling (HDM) as the methodology. The proposed model consists of five perspectives, which are requirements validation, testing, software change management control, technology, and organization and culture with every perspective containing relevant factors. The factors and perspectives are validated and quantified using SQA inputs from subject matter experts. The findings of this study suggest that requirements validation is the most important perspective. Two case studies were conducted to identify the maturity score for each case, demonstrate the practicality of the research model, identify areas of deficiencies, and propose corrective actions. This paper provides an in-depth look at software quality factors and their relative importance, targeting to help SQA practitioners understand and assess their SQA practices.

The U.S. Geological Survey's automated information system's software for processing, storing, and retrieving water data is developed and maintained by the National Water Information System Program of the Water Resources Division. As part of that responsibility, a new system is currently being designed to replace the systems that run on a mainframe computer located at headquarters in Reston, Vz., and on minicomputers located in Division offices across the Nation. The new system is to run on workstations and file servers to be installed in all of the Division offices. A software life cycle provides the framework for defining, developing, and maintaining the new software system and for helping to meet software development challenges. Soft*'are quality assurance is needed in building the new system to provide confidence that the software is engineered to meet users' needs and conforms to established technical requirements. Successful software quality assurance depends on the application of uniform terminology and effective communication among users, developers, and managers. Software quality control is a planned and systematic process that focuses on establishing software standards and procedures, reviews and inspections, testing, and software configuration management throughout the software life cycle. This report explains the background for software quality assurance and the implementation of software quality assurance and quality control in the National Water Information System Program using a generic workbench approach, and presents an example workbench for the requirements-analysis phase of the software life-cycle.

The support of software quality in a software development process may be regarded under two aspects: first, by providing techniques, which support the development of high quality software and second, by providing techniques, which assure the required quality attributes in existing artifacts. Both approaches have to be combined to achieve effective and successful software engineering.In this study, we compare three of the most industrially relevant software development process models (Rational Unified Process (RUP), Microsoft Solution Framework (MSF) and Extreme Programming (XP)) regarding their software quality support in terms of software quality development and software quality assurance. Based on the results we propose a de-facto standard for quality support in software development process models.

Putting Requirements and Quality at the Core of Global Service Delivery: Current Efforts and Future Plans at Pace University

Aims: Software quality assurance is a formal process for evaluating and documenting the quality of the work products during each stage of the software development lifecycle.The practice of applying software metrics to operational factors and to maintain factors is a complex task.Successful software quality assurance is highly dependent on software metrics.It needs linkage the software quality model and software metrics through quality factors in order to offer measure method for software quality assurance.The contributions of this paper build an appropriate method of Software quality metrics application in quality life cycle with software quality assurance.Design: The purpose approach defines some software metrics in the factors and discussed several software quality assurance model and some quality factors measure method.Methodology: This paper solves customer value evaluation problem are: Build a framework of combination of software quality criteria.Describes software metrics.Build Software quality metrics application in quality life cycle with software quality assurance.Results: From the appropriate method of Software quality metrics application in quality life cycle with software quality assurance, each activity in the software life cycle, there is one or more QA quality measure metrics focus on ensuring the quality of the process and the resulting product.Future research is need to extend and improve the methodology to extend metrics that have been validated on one project, using our criteria, valid measures of quality on future software project.

Developing a good software system is a very complex task. In order to produce a good software product, several measures for software quality attributes need to be taken into account. System complexity measurement plays a vital role in controlling and managing software quality because it generally affects the software quality attributes like software reliability, software testability and software maintainability. Thus, software quality assurance (SQA) needs to be addressed keeping in view the new strategies, tool, methodologies and techniques applicable to software development life cycle.This paper is primarily aimed at revisiting and examining peculiar aspects of software development process that affect software quality management process. These aspects of software development process include software reliability measurement, ISO approach applicable to software quality and some aspects related to software testing improvement. Software testing and evaluation methods/tools/techniques do not guarantee effective testing and ensure high software quality. The way to improve the effectiveness of testing is to improve the attitude of software developers towards testing.In this paper, all these factors affecting software quality management have been discussed as well as all the possible improvements have been suggested. The results of this paper may be quite helpful to the researchers in quantifying the specific measuring tools for these software quality attributes.

Empirical Analysis of Quality Models in Practice in Small IT Companies in SEE Region

Software testing is an important process in software quality assurance(SQA). Software testing consumes the majority of the software developers' time and cost of all the phases of system development. An important problem in software testing is to determine whether a program has been tested enough with a testing criterion and when one could stop testing. On the other hand, software measurement is used to estimate the quality of a software. Complexity measures can be used to compare software quality and development cost. This paper proposes a new testing approach which choosing testing path based on path complexity. The process is to use a set of testing paths that satisfying all-uses testing criterion, and then choose the testing path with the most complexity to test. This process is continued until the program can be accepted. The proposed formula is used to determine if it is possible to stop testing before satisfying all-du-paths testing criterion. The main contribution of the paper is that software developers can choose a proper testing action with lower testing effort.

Software testing is an extremely important work link in software engineering. It runs through the entire life cycle of software engineering to ensure that software development meets requirements and can meet certain software quality requirements. With the continuous expansion of the scale of information systems, simple software testing can no longer meet the requirements of system and software quality assurance. This requires practitioners to gradually begin to think about and improve the testing methods of large-scale information software. For large-scale information software, testing will be embedded in each unit, and the software testing process will be organized in a more macroscopic way of thinking and organization. This article will summarize a series of methods suitable for large-scale information software testing through the research of software testing and the practice of the author. It is hoped that the research in this article can provide some help for the testing of large-scale information software, and also provide help for the precipitation and improvement of the author's own work.

This work (1) reviews the current concept ad~ internationally on the disposal of highlevel nuclear wastes; (2) discusses some of the major challenges facing this disposal technology; (3) presents an evaluation of the Canadian performance assessment work as a case study; and (4) introduces a new paradigm within which to site an underground. disposal facility that offers many significant advantages over the existing concept.Chapter 1 explains the setup of the work and forms the "General Introduction" to the subject material.Chapter 2 describes the current internationally-accepted concept of underground disposal in stable, terrestrial, geologic media using a multi-barrier system of engineered (man-made) and natural barriers to prevent or retard the movement of radionuclides from depth to man's environment at the surface. Various aspects of the research and development work being conducted internationally to demonstrate the efficacy of this technology are described with emphasis paid to the Canadian Nuclear Fuel Waste Management Program (CNFWMP).Chapter 3 examines some of the technical challenges of the current disposal concept including (a) the present focus on the lithologic aspects of the geologic/geotechnic research; (b) the unsatisfactory situation in attempts at "validating" models used in computer simulations to forecast very long-term future conditions; and (c) the unsatisfactory state of software quality assurance in such computer simulations. The collection of papers in this chapter points out these problems and presents some of the software engineering tools and techniques used for software verification and quality assurance. Paper 3.4 introduces a comprehensive and systematic approach with which a rigorous process of validating models can be applied.Chapter 4 presents a review of some aspects of the Canadian performance assessment code, its models, as a case study to illustrate the application of principles, and tools and techniques described in Chapter 3. As such, various widely-recognized ANSI/IEEE software engineering standards were used to carry out the evaluation. This review is the first m-depth evaluation done externally and will likely serve, m part, as a basis for the ultimate judgement as to the quality and credibility of the Canadian performance assessment work.Chapter 5 introduces a completely new approach, called the Regional Recharge Concept (RRC), to the siting of underground waste repositories. The emphasis of this new concept is on achieving understanding of regional groundwater flow patterns so as to exploit such knowledge to locate a repository in an area where escaping contaminants will be carried by the groundwater into "stagnant zones" or on a flow trajectory long enough to render decaying radionuclides harmless if and when they do ever surface. The theoretic basis of the RRC is developed in this chapter and the many advantages of the concept are shown through a modelling exercise. Because of the "passive safety" philosophy inherent in this new concept, as well as the move away from the current international focus on lithologic studies (where experience has shown the great difficulties in characterizing fractures and predicting their future behaviour), the RRC being advocated in this work represents a true paradigm shift from the current concept of nuclear waste disposal.Chapter 6 summarizes the results from previous chapters in the form of conclusions relevant to future work in this area.

The moderator has offered seven propositions relative to the meaning and conduct of effective software quality assurance. Although I find it difficult to give unqualified acceptance or rejection to any of these propositions, in response to the rules of the session I accept propositions 1, 2, 3 and 5 and reject 4, 6 and 7.After a number of years experience in the software quality arena, both in government and industry, I have come to the conclusion that the most important aspect of software quality assurance is to make a positive contribution to the objective of the software project. I define this objective as the development of a quality software product delivered on time and within budget. I further define a quality software product as one which meets customer requirements and provides usable service. In short my perspective of software quality assurance is one of contribution in contrast to the “righteousness of the cause.”To this end I suggest an “engineering analysis approach” to software quality. Such an approach can take the form of a typical engineering problem solving model with steps of problem formulation, problem analysis, search, decision, specification and implementation. Using such an approach the advocates for quality software can use empirical evidence to establish the contributions software quality assurance efforts make toward the software project objective.

This paper discussed the development of an Online Support Management System to have a centralized system to support the information technology needs of every department of the University of Antique, in effect, to support the needs of the students. The system was developed using the modified Software Development Life Cycle Waterfall Model using six phases – Conceptualization, Technical Feasibility, Development, Pilot Testing, Creation of User’s manual, and Evaluation of Online Support Management System. Each phase must be completed before the next phase can begin and there is no overlapping in the phases. The researcher anchors the study on Research and Development (R&D) which aims to create a new body of knowledge about existing products or processes, or the creation of an entirely new product. Unstructured interviews, document analysis, and modified survey-questionnaire adapted from ISO/IEC 25010: 2011 Systems and Software Quality Requirements and Evaluation (SQuaRE) - System and software quality models had been conducted for data collection. The findings showed that three groups of the respondents were satisfied with the features and capabilities of the Online Support Management System and complied with the requirements or specifications based on ISO/IEC 25010: 2011 standards. Though the respondents are satisfied with their evaluation of the developed Online Support Management System, the result revealed that there was a significant difference noted in the evaluations of the respondents. This result implies that the evaluation made by the three groups of respondents significantly differs from one another in terms of functional suitability, performance efficiency, compatibility, usability, reliability, security, and maintainability.

The tragic nature of safety-critical software failure’s consequences makes high quality and extreme reliability requirements in such types of software of paramount importance. Far too many accidents have been caused by software failure error or where such failure/error was part of the problem. Safety-critical software is widely applied in diverse areas, ranging from medical equipment to airborne systems. Currently, the trend in the use of safety-critical software in the aerospace industry is mostly concentrated on avionic systems. While standards for certification and development of safety-critical software have been developed by authorities and the industry, very little research has been done to address safety-critical software quality. In this paper, we study safety-critical software embedded in airborne systems. We propose a lifecycle specially modeled for the development of safety-critical software in compliance with the DO-178B standard and a software quality assurance (SQA) model based on a set of four acceptance criteria that builds quality into safety-critical software throughout its development.

Background & Problem Statement - Software testing is a critical phase in the software development lifecycle (SDLC), ensuring that applications function correctly, meet user requirements, and maintain high- quality standards. Traditional software testing approaches, including manual testing and rule-based automation, often face challenges in scalability, efficiency, and adaptability to dynamic software environments. Traditional testing methods are overwhelmed by complex software systems which slows down defect detection and extends both testing costs and release schedules. Machine Learning (ML) has emerged as a transformative solution, introducing predictive and adaptive capabilities that optimize test case selection, automate defect detection, and enhance overall software quality assurance (QA). This study explores the integration of ML in software testing, addressing the challenges of traditional QA methodologies and demonstrating how AI-driven frameworks improve testing efficiency. Methodology - To investigate the impact of ML in software testing, this research adopts a systematic approach by analyzing ML-driven test automation techniques, including predictive testing, adaptive test execution, and automated test case generation. Research reviews how Google Microsoft Facebook IBM and Deep Code put ML-based quality assurance frameworks into operation. The study leverages supervised learning, reinforcement learning, deep learning, and NLP-based techniques to demonstrate how ML models predict software defects, dynamically adapt test cases, and optimize testing resources. The research tests how ML-based testing models operate within CI/CD pipelines to improve ongoing testing and deployment flow. Analysis & Results - The analysis of ML-driven software testing reveals that predictive analytics improves early defect detection rates. It helps developers spend 37% less time debugging their work. Adaptive testing models, including self-healing test scripts, minimize maintenance costs by 50% and enhance test reliability in agile environments. The integration of NLP-based test case generation increases test coverage. NLP technology enables automatic connection between requirements and test cases at 89% success rate. Additionally, reinforcement learning techniques improve test case selection, reducing redundant test executions by 43%. Our research shows different ML methods work well to lessen incorrect error alerts. ML integration for QA surely increasing defect prediction accuracy and optimizing test execution time. Findings & Contributions - This research contributes to the field of AI-driven software testing by providing a comprehensive framework for ML-based QA methodologies. Our study shows that machine learning helps find more software problems better adapts test cases and lowers testing expenses to solve present software development needs. The study also identifies critical challenges, including data availability, model interpretability, and computational overhead, suggesting future research directions in Explainable AI (XAI), hybrid AI-ML testing models, and AI-driven security testing. As the industry moves toward AI-first software testing, this research paves the way for fully autonomous QA frameworks, enabling intelligent, scalable, and cost- effective software validation techniques. Keywords - Machine Learning, Software Testing, Quality Assurance, Predictive Testing, Adaptive Testing, Test Automation, Defect Prediction, Self- Healing Test Scripts, AI-Driven QA, Reinforcement