Software Quality Evaluation Research Articles

Software Quality Assessment Model: A New Approach for Software Testing Tools

The process of software testing is a crucial phase in determining the quality of software, and this phase requires significant costs and a considerable amount of time for testers. This paper discusses the development of a framework for software quality assessment, involving flexible choices of software testing methods and variables in the form of an application. The method used is experimental, developing a new framework based on previous research, where previous research was limited to specific methods and testing variables. The result of this research is the creation of a new framework for software quality assessment. It is hoped that this framework can serve as a reference for software companies in evaluating software quality. In terms of complexity, this framework has the advantage of allowing a tester to choose methods with more flexible or unlimited testing variables. Regarding the estimated time and costs, with [Formula: see text], the practical application complexity of the developed framework is estimated to have the best costs, time and human resources at IDR 254,240,000, with an estimated time of 3,178 work hours and 6,356 work hours with a team of 3 people.

A Data-Driven Approach for Game Evaluation Using Latent Dirichlet Allocation Method Based on Players’ Reviews

Garena is a global game developer and publisher. Garena provides users with access to popular and engaging online games for mobile and PC, developed, curated, and localized for each market. The Battle Royale genre is relatively new, and this research will evaluate Free Fire, one of the games in this genre made by Garena. Analyzing end-user reviews is considered important for evaluating software quality. Researchers need to understand which aspects need to be evaluated based on player reviews on Google Play and how the model's performance is generated using feedback from players who have played Free Fire. In this study, researchers use the Latent Dirichlet Allocation (LDA) method to model topics and generate clusters in discussions for each topic. LDA is a generative probabilistic model of a corpus. This research on topic modeling using Google Play reviews and LDA has identified the topics users are most concerned with. The research shows three main aspects: bugs, graphics and performance, and game rules/punishment policy, as aspects that need to be evaluated based on player reviews on Google Play.

SEA4DQ 2024 Workshop Summary

Welcome to the sixth edition of the workshop on Machine Learning Techniques for Software Quality Evaluation (SEA4DQ 2024), held in Brazil, July 16th, 2024, co-located with ESEC / FSE 2024 [1]. Three papers from all over the world were submitted, and all of them were accepted based on the overall positive reviews. The program also featured two keynotes by Denys Poshyvanyk on Towards an Interpretable Science of Deep Learning for Software Engineering: A Causal Inference View and Qinghua Lu on Responsible AI Engineering from A Data Perspective.

Evaluating Software Quality Metrics for Enhanced Software Management and Engineering

Evaluating Software Quality Metrics for Enhanced Software Management and Engineering

A New Score Function of IFSs and its Application in the Evaluation of Software Quality

A New Score Function of IFSs and its Application in the Evaluation of Software Quality

A fuzzy logic-based quality model for identifying microservices with low maintainability

Microservice Architecture (MSA) is a popular architectural style that offers many advantages regarding quality attributes, including maintainability and scalability. Developing a system as a set of microservices with expected benefits requires a quality assessment strategy that is established on the measurements of the system's properties. This paper proposes a hierarchical quality model based on fuzzy logic to measure and evaluate the maintainability of MSAs considering ISO/IEC 250xy SQuaRE (System and Software Quality Requirements and Evaluation) standards. Since the qualitative bounds of low-level quality attributes are inherently ambiguous, we use a fuzzification technique to transform crisp values of code metrics into fuzzy levels and apply them as inputs to our quality model. The model generates fuzzy values for the quality sub-characteristics of the maintainability, i.e., modifiability and testability, converted to numerical values through defuzzification. In the last step, using the values of the sub-characteristics, we calculate numerical scores indicating the maintainability level of each microservice in the examined software system. This score was used to assess the quality of the microservices and decide whether they need refactoring. We evaluated our approach by creating a test set with the assistance of three developers, who reviewed and categorized the maintainability levels of the microservices in an open-source project based on their knowledge and experience. They labeled microservices as low, medium, or high, with low indicating the need for refactoring. Our method for identifying low-labeled microservices in the given test set achieved 94% accuracy, 78% precision, and 100% recall. These results indicate that our approach can assist designers in evaluating the maintainability quality of microservices.

Data-oriented QMOOD model for quality assessment of multi-client software applications

There has been a great effort to evaluate software quality using proper tools and methods against different development environments changing over time. Quality Model for Object Oriented Design (QMOOD) is a verified model used for quality assessment of object-oriented software. The model associates quality metrics gathered from the source code and quality attributes in use to present a quality measurement. However, the model should be revised for recent multi-client software including native client applications, because there is a deficiency of metric gathering tools in such environments. More specifically, it is sometimes not possible to gather all quality properties required by QMOOD in all native development platforms of client applications. Hence, even though different client applications have the same design, the implementation quality cannot be monitored for the quality assurance. Analyzing and simplifying the metric set may alleviate this challenge, and a convenient quality assessment might be achieved. Thus, we propose to change the operational aspect of QMOOD by inserting an additional layer, Data Analytic, to the hierarchical structure of the conventional model. Accordingly, we provide a discussion on a case study including five native client applications. For this purpose, a design quality of one of the client applications is achieved to validate the appropriateness of the design, the data analytic on the metric set are implemented and the proposed data-oriented simplified QMOOD is applied to the other client applications. Finally, it is stated that the proposed approach successfully alleviated the problems in metric gathering for multi-client applications while applying QMOOD.

Towards a set of metrics for hybrid (quantum/classical) systems maintainability

Given the rapid evolution that has taken place in recent years in the software industry, and along with it the emergence of quantum software, there is a need to design an environment for measuring quality metrics for hybrid, classic-quantum software.  In order to measure and evaluate the quality of classic software, there are models and standards, among which ISO/IEC 25000 stands out, which proposes a set of quality characteristics such as maintainability. However, there is currently no consensus for the measurement and evaluation of quantum software quality.  In this paper we propose a series of adaptations to “classic” metrics, as well as a set of new measurements for hybrid maintainability. Finally, a first prototype of a measurement tool developed as a SonarQube plugin, capable of measuring these metrics in quantum developments, is also presented. 

Sine function similarity-based multi-attribute decision making technique of type-2 neutrosophic number sets and application to computer software quality evaluation

With the rapid development of information technology, software products are playing an increasingly important role in people’s production and life, and have penetrated into many industries. Software quality is the degree to which the software meets the specified requirements, and is an important indicator to evaluate the quality of the products used. At present, the scale of software is increasing, and the complexity is increasing. It is an urgent problem to reasonably grasp and ensure the product quality. The measurement and evaluation of Software quality characteristics is an effective means to improve Software quality. Faced with the complex system of software, there are many factors that affect product quality. Current research mainly measures software product quality from a qualitative perspective. The computer software quality evaluation is a classical multi-attribute group decision making (MAGDM). Type-2 Neutrosophic Numbers (T2NNs) is a popular set in the field of MAGDM and many scholars have expanded the traditional MAGDM to this T2NNs in recent years. In this paper, two new similarity measures based on sine function for T2NN is proposed under T2NNs. These two new methods are built for MAGDM based on the sine similarity measures for T2NN (SST) and sine similarity weighted measures for T2NN (SSWT). At the end of this paper, Finally, a practical case study for computer software quality evaluation is constructed to validate the proposed method and some comparative studies are constructed to verify the applicability. Thus, the main research contribution of this work is constructed: (1) two new similarity measures based on sine function for T2NN is proposed under T2NNs; (2) These two new methods are built for MAGDM based on the sine similarity measures for T2NN (SST) and sine similarity weighted measures for T2NN (SSWT); (3) an example for computer software quality evaluation is employed to verify the constructed techniques and several decision comparative analysis are employed to verify the constructed techniques.

My Instructional Tools Software for College Faculty

This study was conducted using the research and development methodology over the course of three stages. The first phase involved conducting a survey to determine the faculty needs in terms of information and communication technology. According to survey findings, faculty members were particularly interested in using offline educational software. The second phase involved creating offline instructional software in accordance with the system development life cycle. The three information technology professionals examined and evaluated the software to verify its quality. Pilot testing and rolling out the program to the faculty were part of phase three. The program was evaluated using the Department of Trade and Industry/Bureau of the Philippines Standards software quality models and the International Standard 25010:2011 Systems and Software Quality Requirements and Evaluation System. Eight characteristics make up this product quality model, which is further broken down into subcharacteristics that relate to software's static and dynamic qualities. The stated quality criteria were used as a checklist to assure a full treatment of quality needs, and offered a framework for anticipating the ensuing effort and activities necessary during system development. When defining or assessing the quality of computer systems or software products, the qualities in the quality in use model and product quality model were meant to be used together as a set.

A median-based fuzzy approach to software quality evaluation

A median-based fuzzy approach to software quality evaluation

Application of Meta-Programming Techniques for Accelerating Software Development and Improving Quality

A contemporary software tool has been devised to evaluate software quality through metric analysis techniques. This tool calculates pertinent metrics utilizing quality indicators and establishes a composite quality indicator value for software products. The intricacies of software quality assessment processes have been elucidated, including the examination of software quality's standardization as well as the presentation level of its model. This enables the potential for enhancement through the formulation of suitable criteria for quality assessment, refining models for metric analysis, and quantitatively measuring quality across all phases of project implementation. Notably, the use of metric analysis to gauge software quality reveals a lack of standardized metrics, resulting in varying assessment methods and metrics from different measurement system providers. Interpreting metric values also proves challenging for most software users due to a lack of clarity and informativeness. Furthermore, it has been discovered that while decisions based on cost, development duration, and designer company reputation influence software implementation choices, they do not always guarantee optimal software quality.

An entropy-based group decision-making approach for software quality evaluation

Software quality evaluation (SQE) is a multi-dimensional decision-making problem. The increasingly complex socioeconomic environment has made group decision making (GDM) more important. Determination of the relative contribution (weight) of individual decision makers is an important part of the GDM process. Calculation of the similarity between decision matrices, potentially using a comprehensive projection measure, is also critical. This paper presents: (1) a new entropy-based approach to determine the weight of decision makers; (2) a novel normalized projection approach to measuring the similarity between two decision matrices; and (3) new group regret and satisfaction reference matrices that are modeled in a GDM setting. A comprehensive GDM method is proposed and adopted for SQE. An experimental analysis is conducted to investigate the practicability, feasibility, and validity of the proposed GDM method. The experimental results confirm the proposed GDM method as practicable, producing stable rankings of alternatives, with the same ranking of alternatives being produced in almost all of the dynamic experimental cases.

Construction of similarity measure for intuitionistic fuzzy sets and its application in face recognition and software quality evaluation

As a generalization of fuzzy sets, intuitionistic fuzzy sets (IFSs) are more capable of representing and addressing uncertainty in real-world problems. As a result, IFSs have been utilized in various areas of application. However, the distance and similarity measures between the two IFSs are still an open issue that has drawn much attention over the past few decades. Even though several intuitionistic fuzzy similarity measures (IFSMs) have been developed, a number of issues still exist, including counter-intuitive results, ‘the zero divisor problem,’ violation of similarity measure axioms, and being incompetent to detect minor changes in membership or non-membership. To overcome these shortcomings, a novel intuitionistic fuzzy similarity measure (IFSM) has been introduced in this study. Unlike existing measures, this method considered the global maximum and minimum of differences in memberships and differences in non-memberships, along with their individual differences, to construct an IFSM. Moreover, it has been shown that a convex combination of two similarity measures is also a similarity measure. Some numerical examples are employed to emphasize the advantages and strengths of the proposed method over existing ones. The suggested IFSM has been implemented on a few pattern classification issues to demonstrate its efficacy and a new face recognition method is also presented. Moreover, an entropy measure is introduced using the proposed IFSM, which is further used to construct the weights of attributes in the MADM method. Furthermore, the MADM technique, IF-E-TOPSIS, is constructed using the suggested IFSM and entropy measure. The effectiveness of this method is shown by utilizing it for software quality assessment, and the results are compared with existing ones to highlight the superiority of the proposed method.

Pemenuhan Persyaratan Permohonan Paten dengan Metode Multi-Attribute Global Inference of Quality (MAGIQ)

As a decision support system, we implemented the Multi-Attribute Global Inference of Quality (MAGIQ) method in patent applications. By employing the Rank Order Centroid (ROC) weighting approach, we determined that MAGIQ provides an effective and efficient solution for addressing challenges in the patent application process. Although previous studies have applied MAGIQ to software quality evaluation, our application in selecting patent applicants introduces a new perspective. Our analysis identified Applicant 2 as the most suitable, achieving the highest score of 0.454861. Furthermore, when comparing our results with those derived from the Analytical Hierarchy Process (AHP) method, we observed a high consistency in rankings, affirming MAGIQ's reliability. Consequently, we suggest applying MAGIQ to more intricate problems to delve deeper into its potential and constraints in diverse contexts

Quality Measurement of Accurate-5 Accounting Software Using the Iso 9126 Model

This study aims to evaluate the degree of excellence of the Accurate-5 accounting software by employing the ISO-9126 model, which assesses six dimensions (primary characteristics) and associated attributes (secondary characteristics) of software quality. The researchers measured a sample of 41 participants who attended a workshop at STMIK Mardira Indonesia Bandung using the Accurate-5 software. The researchers gathered primary data using a questionnaire that utilized the Likert scale. The validity test results supported the validity of the items, as a value greater than 0.316 was found. The reliability test results demonstrated that all attributes have a high level of reliability, as each item had a Cronbach's alpha value greater than 0.7. The software quality evaluation findings utilizing the ISO 9126 standard indicate that all dimensions and attributes satisfy the "Good" criteria. The researchers found that the attributes of Compliance, Installability, and Coexistence satisfy the criteria of "Very Good." Based on the data, we can infer that the Accurate-5 software complies with the ISO 9126 standard as it achieved an average percentage score of 77.53%, indicating that it meets the "Good" criteria.

УЗЛУКСИЗ ҲАРАКАТДАГИ АХБОРОТТИЗИМЛАРИ УЧУН АНАЛИТИК МОДЕЛ

Requirements for information security and reliable operation of systems do not become obsolete. On the contrary, the demand for them has increased and has become a problem that does not lose its relevance. It's no secret that the fault tolerance of large software systems is of great importance, especially when they are online. The presented article is devoted to these issues and a model is proposed for evaluating software quality indicators under failure conditions.

Unlocking the Potential of Blockchain Through Multi-Criteria Decision Making in Platform Selection

Purpose: The purpose of this paper is to introduce a methodology that can help organizations choose the best Blockchain platform for their specific business case. With numerous options available, it's important to carefully consider the capabilities of a Blockchain before selecting it. This methodology is intended to provide a structured approach to aid in the decision-making process, taking into account the various characteristics of Blockchain that are needed. Theoretical Framework: The theoretical framework for this paper is based on Multi Criteria Decision Making (MCDM) and ISO/IEC 25010. MCDM is a decision-making technique that considers multiple criteria when making a choice, which is useful for selecting the best Blockchain platform. ISO/IEC 25010 is a standard that provides a framework for evaluating software quality characteristics, which is relevant for evaluating the quality of the Blockchain platform. Design/Methodology/Approach: The methodology presented in this paper involves a structured approach to selecting the best Blockchain platform for a specific business case. The approach is based on a combination of MCDM and ISO/IEC 25010, and involves several steps. First, the relevant criteria for selecting the Blockchain platform are identified. Next, a weighting system is developed to determine the importance of each criterion. Then, each Blockchain platform is evaluated based on the criteria and weights, and a score is assigned. Finally, the scores are aggregated to determine the best Blockchain platform for the specific business case. Findings: The main finding of this paper is the methodology for selecting the best Blockchain platform for a specific business case. This methodology can aid organizations in making an informed decision when choosing a Blockchain platform, taking into account the various characteristics of Blockchain that are needed. The paper also highlights the importance of careful consideration when selecting a Blockchain platform, as the wrong choice could have negative consequences. Research, Practical & Social Implications: The research implications of this paper are significant, as it provides a structured approach for selecting the best Blockchain platform for a specific business case. This methodology can be used across industries and could have a significant impact on the adoption of Blockchain technology. From a practical perspective, this methodology can aid organizations in making informed decisions when selecting a Blockchain platform, which can save time and resources. From a social perspective, the adoption of Blockchain technology has the potential to revolutionize business operations and improve transparency and accountability. Originality/Value: The originality of this paper lies in the development of a methodology for selecting the best Blockchain platform for a specific business case. This methodology is based on a combination of MCDM and ISO/IEC 25010 and is not specific to any one industry. The value of this paper is in providing a structured approach to aid organizations in making an informed decision when selecting a Blockchain platform, taking into account the various characteristics of Blockchain that are needed.

A Quantitative Evaluation for Usability under Software Quality Models

Usability evaluation in Human-Computer Interaction (HCI) is done by observing the user's behaviors and reactions while performing a given task. The observers examine users' behaviors while doing assigned tasks and describe their observations in terms of usability. The usability evaluation would depend on the observers' ability or experience. It proceeds qualitatively. We propose a quantitative evaluation, which adopts attributes and metrics from System and Software Quality Requirement and Evaluation(SQuaRE) published by International Standard Organization (ISO). Furthermore, we examine qualitative observations conducted in usability testing and apply our method to make it a quantitative evaluation.

Review of Software Quality Verification and Evaluation Methods

The basic concepts in the field of software quality testing and evaluation are defined. In particular, the concepts of verification, validation and software lifecycle and their role in the testing process are considered. The concept of an artifact in the software lifecycle is considered. The Russian and international standards in the field of software quality assessment are taken into account. The existing methods of software verification are regarded: expertise, static analysis, formal methods, dynamic and synthetic methods.An overview of software quality assessment methods used in software development and testing cycles is presented. Functional and administrative factors affecting software quality are also considered. The article lists modern testing automation tools that can be used today. The review material of the article will be useful for software developers, novice testers and related specialists.