Achieve Software Quality Research Articles

How Scrum adds value to achieving software quality?

Scrum remains the most popular agile software development method implementation for a variety of reasons; one important motive is to improve software quality. Yet many organizations fail to achieve quality improvements through the use of Scrum, and existing research sheds little light on the value-add of Scrum for software quality. More specifically, (1) how notions of software quality among Scrum practitioners relate to established quality perspectives, (2) how Scrum helps teams to achieve higher software quality and (3) why some teams fail to meet the objective of higher quality. We addressed these gaps through a two-phased qualitative study based on 39 interviews and two in-depth case studies. We find that Scrum practitioners emphasize established notions of external quality comprising of conformity to business needs and absence of defects, while they also value internal quality, especially sustainable software design. Our results show that Scrum helps teams achieve both dimensions of quality by promoting some social antecedents (collaboration, psychological safety, accountability, transparency) and process-induced advantages (iterative development, formal inspection, and adaptation). Our findings unveil how these factors contribute to achieving software quality and under what conditions their effects can fail to materialize. These conditions include inconsistent Scrum implementations, cultural constraints, team tensions, and inaccessibility of end-users. In addition, the complexity of the project aggravates the impact of these conditions. Taken together, these findings show that Scrum can complement established quality assurance and software engineering practices by promoting a social environment that is conducive to creating high-quality software. Based on our findings, we provide specific recommendations for how practitioners can create such an environment.

Prediction of software defects using deep learning with improved cuckoo search algorithm

SummaryThe software project model needs a defect prediction model to find defect‐prone file software systems. The fault‐prone model prediction, predicting bugs, and bug removal can undertake the software industry to achieve software quality. Therefore, automatically forecasting the number of errors in software modules is important, and it may assist developers in allocating limited resources more efficiently. Several methods for detecting and repairing such flaws at a low cost have been offered. These approaches, on the other hand, need to be significantly improved in terms of performance. Hence in this article, we implement an ensemble technique for the software defect prediction and prediction of the software bug. Also, we proposed a hybrid technique to predict several defects in the software system. The proposed approach uses principle component analysis for feature extraction which is to improve further performance and control the optimization problem. Classifiers were applied to five PROMISE datasets to determine the greatest implemented classifier with respect to the prediction achievement measuring factor. Our proposed model yields greater results on solving defect prediction problems and showing enhancement toward the existing model.

Software Defect Prediction: State of the Art Survey

Software has evolved into a critical component in today's world. The quantity of faults in a software product is connected to its quality, which is also restricted by time and cost. In terms of both quality and cost, software faults are costly. The practice of tracing problematic components in software prior to the product's launch is known as software defect prediction. Defects are unavoidable, but we should strive to keep the number of defects to a bare minimum. Defect prediction results in shorter development times, lower costs, less rework, higher customer satisfaction, and more dependable software. As a result, defect prediction procedures are critical for achieving software quality and learning from prior errors.In this study, we conduct a review of the literature from the last two decades and look into recent advancements in the field of defect prediction.

Optoelectronic control systems: Technological principles to achieve software quality

Optoelectronic control systems: Technological principles to achieve software quality

Improving test automation maturity: A multivocal literature review

AbstractMature test automation is key for achieving software quality at speed. In this paper, we present a multivocal literature review with the objective to survey and synthesize the guidelines given in the literature for improving test automation maturity. We selected and reviewed 81 primary studies, consisting of 26 academic literature and 55 grey literature sources. From primary studies, we extracted 26 test automation best practices (e.g., Define an effective test automation strategy, Set up good test environments, and Develop high‐quality test scripts) and collected many pieces of advice (e.g., in forms of implementation/improvement approaches, technical techniques, concepts, and experience‐based heuristics) on how to conduct these best practices. We made main observations: (1) There are only six best practices whose positive effect on maturity improvement have been evaluated by academic studies using formal empirical methods; (2) several technical related best practices in this MLR were not presented in test maturity models; (3) some best practices can be linked to success factors and maturity impediments proposed by other scholars; (4) most pieces of advice on how to conduct proposed best practices were identified from experience studies and their effectiveness need to be further evaluated with cross‐site empirical evidence using formal empirical methods; (5) in the literature, some advice on how to conduct certain best practices are conflicting, and some advice on how to conduct certain best practices still need further qualitative analysis.

Can We Really Achieve Software Quality?

As software engineers, we need to reject a "good enough" quality mindset. Achieving software quality will be possible when better tools to enforce it will be widespread and software engineers will learn to make it a priority, no matter what.

Comparison of threshold identification techniques for object-oriented software metrics

Quality assurance is a continuous process throughout the project lifecycle from inception till post-delivery. Software metrics are tools to help developers in achieving software quality objectives. Software metrics are used to predict the fault-proneness of classes in software using machine-learning and statistical techniques. However, these methodologies are difficult for daily tasks. Simpler and on the fly methodologies such as threshold values are needed. Metric thresholds can be used to control software quality and to recommend improvements on software code. Thresholds detect the parts of software that need more verification and validation. Many threshold identification techniques were proposed in previous research. However, the techniques do not provide consistent thresholds. The authors compare eight threshold identification techniques to diagnose software fault-proneness. The eight techniques are derived from diagnosis measures such as specificity, sensitivity, recall and precision. Five threshold identification techniques have derived thresholds that are skewed and have large standard deviations. Only three techniques are selected for threshold identification based on consistency and variation in selecting thresholds of software metrics in the systems under study. These techniques find thresholds that have the least variation among the studied techniques. The median of the 11 systems is selected as a representative of all thresholds.

Descriptions of issues and comments for predicting issue success in software projects

Software development tasks must be performed successfully to achieve software quality and customer satisfaction. Knowing whether software tasks are likely to fail is essential to ensure the success of software projects. Issue Tracking Systems store information of software tasks (issues) and comments, which can be useful to predict issue success; however; almost no research on this topic exists. This work studies the usefulness of textual descriptions of issues and comments for predicting whether issues will be resolved successfully or not. Issues and comments of 588 software projects were extracted from four popular Issue Tracking Systems. Seven machine learning classifiers were trained on 30k issues and more than 120k comments, and more than 6000 experiments were performed to predict the success of three types of issues: bugs, improvements and new features. The results provided evidence that descriptions of issues and comments are useful for predicting issue success with more than 85% of accuracy and precision, and that the predictions of issue success vary over time. Words related to software development were particularly relevant for predicting issue success. Other communication aspects and their relationship to the success of software projects must be researched in detail using data from software tools.

Multi-response optimization based on desirability function and Taguchi method in agile software development

Software industries are continuously striving to achieve software quality through delivery of defect free software within time and within estimated budget. Most of the quality improvement strategies in software development focusses on optimizing a single response variable such as the defect count. But in reality, many responses contribute to the quality of software developed which requires to be studied simultaneously. This paper attempts to study the number of defects in software and the effort required in correcting these defects, simultaneously using desirability function and Taguchi method. Effort is defined as the time span from when the defect was logged into the system to the time when the defect was corrected and removed from the system and is measured in hours. The work has been executed on the issue tracking system of a large telecommunication organization. The organization manufactured consumer electronic devices having embedded software developed using agile development method. The input factors studied are Change Request Priority, software development phase and severity, which were selected from a total of 24 parameters using analytic hierarchy process. Significant factors and their optimal levels which optimized the defects captured and the effort taken to eliminate them, were obtained. Confirmation tests were performed using the optimal settings of the input factors on the data from the subsequent sprint which showed a 20% improvement in the overall desirability value.

Aspects of software quality applied to the process of agile software development: a systematic literature review

The importance of quality in software engineering is widely recognized today. As a result, agile methods have incorporated quality practices in the software development process to achieve quality software quickly and in harmony with rapidly changing customer requirements. Experts have published a substantial amount of information related to the diverse aspects of software quality and agile development. This work aims to perform a systematic literature review of the following characteristics: critical success factors, metrics to measure quality, quality attributes, agile practices, quality models, and agile principles considered by these models. 773 papers related to quality in the agile development process were identified, of which, for the preparation of this article, 71 papers were selected. This study catalogs 118 critical success factors, 137 agile practices, 102 metrics, and 70 quality attributes that affect the agile software development. In addition, 14 quality models, which do not cover all the aspects of quality related to agile development, were studied to prepare this paper. 28.17% of the studies analyzed consider the agile practices as they affect the quality of software, which is the most studied aspect.

Pattern detection and design rationale traceability: an integrated approach to software design quality

Design rationale is the synthesis of the structure that is consistent with the model of an artefact, decisions, alternative approaches, and the reasoning behind it. Hence, bypassing it will result in poor quality systems engineering. Ambiguous representation of design rationale goals is just one of the many limitations that contributes to the intricacy of design patterns, thereby this research aims to introduce an approach to support the structuring, evaluation, and analysis of design patterns. The authors have proposed a method and implemented an associated tool with a mechanism that validates the class relationships and properties of design patterns comprehensively, resulting in a reliable pattern detection result. The preliminary results of the proposed research show that although detection and evaluation of a design pattern require some overhead using the approach, it does contribute to the confidence of the developers and gives affirmation that the design pattern implemented in the source code achieves its defined rationale goals based on the gang of four definition of design patterns through the reliable pattern detection output and straightforward evaluation result. The conclusion could be drawn that through the proposed approach, the preliminary result resolves the intricacy of design rationale traceability while achieving software quality is permissible.

Challenges in NoSQL-Based Distributed Data Storage: A Systematic Literature Review

Key-Value stores (KVSs) are the most flexible and simplest model of NoSQL databases, which have become highly popular over the last few years due to their salient features such as availability, portability, reliability, and low operational cost. From the perspective of software engineering, the chief obstacle for KVSs is to achieve software quality attributes (consistency, throughput, latency, security, performance, load balancing, and query processing) to ensure quality. The presented research is a Systematic Literature Review (SLR) to find the state-of-the-art research in the KVS domain, and through doing so determine the major challenges and solutions. This work reviews the 45 papers between 2010–2018 that were found to be closely relevant to our study area. The results show that performance is addressed in 31% of the studies, consistency is addressed in 20% of the studies, latency and throughput are addressed in 16% of the studies, query processing is addressed in 13% of studies, security is addressed in 11% of the studies, and load balancing is addressed in 9% of the studies. Different models are used for execution. The indexing technique was used in 20% of the studies, the hashing technique was used in 13% of the studies, the caching and security techniques were used together in 9% of the studies, the batching technique was used in 5% of the studies, the encoding techniques and Paxos technique were used together in 4% of the studies, and 36% of the studies used other techniques. This systematic review will enable researchers to design key-value stores as efficient storage. Regarding future collaborations, trust and privacy are the quality attributes that can be addressed; KVS is an emerging facet due to its widespread popularity, opening the way to deploy it with proper protection.

Developer Testing in the IDE: Patterns, Beliefs, and Behavior

Software testing is one of the key activities to achieve software quality in practice. Despite its importance, however, we have a remarkable lack of knowledge on how developers test in real-world projects. In this paper, we report on a large-scale field study with 2,443 software engineers whose development activities we closely monitored over 2.5 years in four integrated development environments (IDEs). Our findings, which largely generalized across the studied IDEs and programming languages Java and C#, question several commonly shared assumptions and beliefs about developer testing: half of the developers in our study do not test; developers rarely run their tests in the IDE; most programming sessions end without any test execution; only once they start testing, do they do it extensively; a quarter of test cases is responsible for three quarters of all test failures; 12 percent of tests show flaky behavior; Test-Driven Development (TDD) is not widely practiced; and software developers only spend a quarter of their time engineering tests, whereas they think they test half of their time. We summarize these practices of loosely guiding one's development efforts with the help of testing in an initial summary on Test-Guided Development (TGD), a behavior we argue to be closer to the development reality of most developers than TDD.

Un Enfoque Inteligente para Soporte a la Toma de Decisiones de Diseño Arquitectónicas en el Contexto de la Evaluación de Arquitecturas de Software

La Ingeniería de Software necesita herramientas novedosas para alcanzar alta calidad en el software, enfrentando el rol cambiante del mismo. La Arquitectura de Software es clave, ya que afecta directamente a la calidad final. La Evaluación de Arquitecturas de Software valida si la arquitectura cumple con los requerimientos de calidad, implicando decisiones de diseño. La toma de decisiones es un proceso complejo conducido por factores humanos, donde la Inteligencia Artificial puede asistir. Entonces, se propone un enfoque basado en Inteligencia Artificial para ayudar a arquitectos en el proceso de toma de decisiones de diseño conducido por atributos de calidad. Esta versión combina modelos de atributos de calidad y un Agente inteligente, utilizando Aprendizaje por Refuerzo para obtener una política de aplicación de patrones arquitectónicos secuencial mediante simulación. Un estudio de caso y una serie de experimentos ilustran la propuesta con patrones comúnmente utilizados en la industria del software.

Empirical study of software process improvement in Malaysian small and medium enterprises: The human aspects

AbstractSoftware Process Improvement (SPI) aims to achieve quality software products in software companies. Ignoring human factors can cause several types of damage in the software development process. Because, Software development is not a purely technical task, but rather it is a relationship between technical and human factors that interact with each other constantly. Currently, Small Medium Enterprises' (SMEs) software development companies in Malaysia still struggle to implement SPI successfully. Therefore, the main objective of this study is to investigate the empirical evidence based on the human factor perspective for helping Malaysian SMEs' software development companies to implement SPI strategies. A questionnaire‐based survey method was used for gathering information from 79 practitioners. The results indicate that 9 factors (employee awareness, leadership involvement, employee involvement, customer involvement, senior management support, staff experience, staff learning, staff skills, and client support) are considered important for implementing SPI in Malaysian SME software development companies. The involvement of both leadership and employees, and getting support from management are the most important human factors that should be considered during the design process of SPI strategies.

To Achieve Software Quality Assurance in Brain Tumor Detection Using Artificial Neural Networks

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.

New Model to Achieve Software Quality Assurance in E-Learning Application

New Model to Achieve Software Quality Assurance in E-Learning Application

Special Section on Software Quality Assurance: Research and Practice

The papers in this special section are devoted to the topic of software quality assurance. As software is integrated more frequently into every aspect of our lives, as it grows more quickly in size and function, as its failure in operations causes increasingly devastating consequences, and as schedules and budgets are continually reduced despite the need for high-quality, reliable, and secure software, advanced and innovative technologies must be developed to achieve software quality assurance more effectively and efficiently. It is also critical for the industry and academia to work together to conduct cooperative research to reduce the gap between state-of-the-art analyses and practice applications.

Study on Various Methodologies/frameworks used to Achieve Software Quality in different Organizations

Purpose of this study is to explain that how the various methodologies, frameworks and processes leads to software quality. Numerous methodologies have been introduced on which lot of exploration or research has been made. This paper includes the study of some processes and techniques which have been used by the firms to achieve software quality. This study strongly recommends the necessity of consciousness regarding the use of software quality oriented processes and the arenas on which extra work leads to quality of software or quality assurance.

How To Improve Software Quality Assurance In Developing Countries

Quality is an important factor in software industry. Software quality depends upon the customer satisfaction which can be achieved through applying standards. In this era achieving quality software is very important because of the high customer demands. Developed countries are excelling in software industry and improving day by day. Meanwhile developing countries like Pakistan are struggling with software quality and cannot maintain reputation in International Market. Software Quality lacks due to many reasons. This paper will address the problems for lacking interest in improving the software quality by higher authorities and software assurance team. We have provided solution to the addressed problems also.