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Business Intelligence (BI) becomes in the front of demanding technologies. The large or midsize companies need a technology to adapt changing requirements, to deal with rich amount of data; to get correct information, analysis data, and finally to quick support decision makers. Developing agile BI application can be defined as a short delivering so...
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... Every iteration has to be fully integrated and carefully tested as a final production release (Penmetsa, 2017). Delivery time is a critical factor for agile product success (Sanaa et al., 2016). Since the iterations make the software development effective and efficient to meet the customer's requirements and contribute to the project's success, it also makes the development process a little more complicated and time-consuming (Javed et al., 2019). ...
A test case is a cornerstone of the testing process; hence, it is quintessential to ensure the quality of the test cases. However, test case design in the Agile testing process has limitations that affect its quality standards, leading to the failure of many software projects. Previous studies are limited in providing a clear guideline for assessing the test case quality. However, evaluating the quality of test cases will help software testing practitioners to understand some critical issues in designing test cases from various perspectives. Therefore, this paper aims to present the verified factors and criteria of test case quality by software testing experts in an Agile environment. The proposed factors and criteria were verified through expert review techniques, which included an online survey of professionals and those in domain and knowledge experts. Twenty-three industry practitioners, including developers, testers, and systems analysts, were used to identify the domain experts. In contrast, the knowledge experts were drawn from 13 academic areas of software engineering and testing. The results showed that the quality of test cases is paramount in Agile projects; therefore, the experts accept seven factors and 32 criteria with a few modifications and suggestions. The finding may assist the researchers in improving the proposed factors and criteria for validation purposes. Hence, may contribute to software testing practitioners as a guideline in constructing, designing, and assessing compelling test cases. Most significantly, the fixed factors and criteria may contribute to the body of knowledge in the software testing domain and industries.
... However, such an approach has a drawback that certain perspectives may remain neglected. To sum up, in the GQM related literature, we have observed a common practice of extending the GQM to adjust it to particular research needs, like in [64] for agile software development and [65] for data warehouses quality assessment. ...
Digitalization increasingly enforces organizations to accommodate changes and gain resilience. Emerging technologies, changing organizational structures and dynamic work environments bring opportunities and pose new challenges to organizations. Such developments, together with the growing volume and variety of the exchanged data, mainly yield complexity. This complexity often represents a solid barrier to efficiency and impedes understanding, controlling, and improving processes in organizations. Hence, organizations are prevailingly seeking to identify and avoid unnecessary complexity, which is an odd mixture of different factors. Similarly, in research, much effort has been put into measuring, reviewing, and studying complexity. However, these efforts are highly fragmented and lack a joint perspective. Further, this negatively affects the complexity research acceptance by practitioners. In this study, we extend the body of knowledge on complexity research and practice addressing its high fragmentation. In particular, a comprehensive literature analysis of complexity research is conducted to capture different types of complexity in organizations. The results are comparatively analyzed, and a morphological box containing three aspects and ten features is developed. In addition, an established multi-dimensional complexity framework is employed to synthesize the results. Using the findings from these analyses and adopting the Goal Question Metric, we propose a method for complexity management. This method serves to provide key insights and decision support in the form of extensive guidelines for addressing complexity. Thus, our findings can assist organizations in their complexity management initiatives.
... One RE technique could not resolve all the requirement challenges at once, thus combination of RE techniques which based on situational background are one of the recommended by most of the literatures [2]- [4]. However, most of the combination techniques involved extensive communications with end users which lead to rigorous and iterative cycles of RE process that contributes to project failures [5]- [7]. LSS method also applied a combination of RE techniques with specific tools at specific phases where Survey, Focus Group discussion, interview and questionnaires were practiced in the industrial environment. ...
Requirement Elicitation (RE) is the most important phase in software development life cycle. It is a complex process because it involves the communications between two group of people to get into understanding of what to be built and what need to be delivered from software perspective. The purpose of this paper is to introduce a hybrid framework which combine the RE techniques from analytical and synthetic category with Lean Six Sigma (LSS) method, aimed at improving RE process to produce a quality software requirement. A framework consists of three phases; design, implementation and analysis are proposed where an industry case study is demonstrated for validation. The new framework observed a significance acceptance by analysts where the new hybrid approach is easy to adopt though at absence of users at the early stage of requirement study. The result also shown that the entire RE process cycle time improved tremendously. The limitation of this paper because it only tested in one company and at a specific project. The main contribution of the paper is to provide new knowledge in combining the RE techniques with LSS at absence of end user.
Tests on software are performed to ensure it has no defects. Software testing companies and organizations claimed that the testing problem increased their time and budget for testing by over 50%. As a result, the product’s release is delayed, which attracts customer complaints. Testing involves test cases, which are a vital part of the process. Therefore, quality test cases likely to identify defects and meet users’ requirements must be chosen. This paper aims to identify and verify the characteristics, sub-characteristics, and metrics that construct the proposed model for producing high-quality black-box test cases in an Agile Software Development environment. An expert review approach was used to verify the proposed model. Ten academic and six industry experts contributed to this verification. The results showed that six characteristics, 22 sub-characteristics, and 56 metrics are accepted to be included in the proposed model. Furthermore, findings revealed that the proposed model is comprehensive, consistent, relevant, and well-organized for Agile projects.
Развитие сложных программно-технических систем привело к существенному увеличению их структурной и функциональной сложности и приданию им свойств многофункциональности. Поддержка принятия решений на управление в процессе развития таких систем требует учета динамики изменения требований назначения, происходящих из-за вариации внешних условий. Это обосновывает актуальность разработки механизмов анализа изменения требований назначения многофункциональных систем. На основе анализа целеориентированных методов построения систем требований построена их модель в виде изменяемой иерархии функциональных требований. Предложенная модель позволяет учитывать как динамику изменения требований, так и взаимосвязи между ними. В результате анализа процесса изменения требований назначения многофункциональных систем выявлены основные факторы и показана необходимость учета динамики изменения требований. Для решения задач системного анализа введен показатель динамики изменения требований назначения, рассчитываемый как отношение суммы относительной величины изменения требований к наблюдаемой продолжительности изменения. Предложен подход к расчету показателя динамики требований на основе квалиметрического подхода, позволяющий учитывать изменения с учетом их важности на основе заранее построенного дерева показателей качества. Областью применения нового показателя является косвенная оценка изменения условий применения многофункциональных реконфигурируемых систем. Использование показателя позволяет решать прямую и обратную задачи оценки пригодности системы в условиях изменения требований. Расчет нового показателя для сложных систем отдельных классов показывает высокое значение (более 0,2 в год) динамики, что обосновывает актуальность мероприятий модернизации для поддержания пригодности многофункциональных систем.
Currently, data quality is in the spotlight of research and organizations. It derives from new technological developments, such as the Internet of Things (IoT), which provides unprecedented amounts of data and enables new ways of creating knowledge. The interim value is hidden in the flood of data and has already received many industries such as construction, manufacturing, and healthcare. These organizations adopt data applications to extract critical information to understandits purpose better, leading to a competitive advantage. In parallel to gain these positive effects based on struggling around with the data, the quality of data and the decisions are neglected very often. Decisions must be made quickly in response to changing requirements. Thereby, agile methods and approaches can be successfully and profitably applied. The decisive factor for success is the holistic view of architecture, organization, technology, and adapted process models. Due to the given ideas, research on data quality combined with agile companies is still in its infancy. This paper presents categories for data quality in combination agility based on literature and expert interviews to close this gap and establish a foundation for future research.
