On the question of a method for researching user requirements for software

Методы User Story все чаще используются в качестве основы артефактов проектирования требований при разработке программного обеспечения. На практике доказано, что метод User Story является более эффективным для описания основных целей системы. Но непрерывное управление работой программного обеспечения может быть особенно трудоемким и подверженным ошибкам, особенно при оценке качества или объема пользовательских историй и наблюдении за общей картиной системы. С другой стороны, эти модели были признаны эффективными инструментами коммуникации и анализа цели. В рамках данной работы рассмотрены и проанализированы методы выявления и представления требований к разработке программного обеспечения. В статье предлагается генеративный подход для создания диаграмм надежности на основе автоматизированного анализа пользовательских историй. Истории преобразуются в диаграммы, что позволяет разработчикам требований и пользователям проверять основные концепции и функциональные этапы, лежащие в основе историй, и обнаруживать искаженные или избыточные истории. Такие модели также открывают двери для автоматизированного систематического анализа. The User Story methods (user stories) increasingly are used as the basis of requirements design artifacts in software development. In practice, it is proved that the User Story method is more effective for describing the main goals of the system. But continuous management of software operation can be particularly time-consuming and error-prone, especially when evaluating the quality or volume of user stories and observing the overall picture of the system. On the other hand, these models were recognized as effective tools for communication and goal analysis. Within the framework of this work, methods for identifying and presenting requirements for software development are considered and analyzed. In the article, we propose a generative approach for creating reliability diagrams based on automated analysis of user stories. Stories are converted into diagrams, which allow requirements developers and users to check the basic concepts and functional stages underlying the stories, and detect distorted or redundant stories. Such models also open the door for automated systematic analysis.

Estimation Approaches of Machine Learning in Scrum Projects: A Review

It is inevitable for any successful IT industry not to estimate the effort, cost, and duration of their projects. As evident by Standish group chaos manifesto that approx 43% of the projects are often delivered late and entered crises because of over budget and less required functions. Improper and inaccurate estimation of software projects leads to a failure, and therefore it must be considered in true letter and spirit. When Agile principle-based process models (e.g. Scrum) came into the market, a significant change can be seen. This change in culture proves to be a boon forstrengthening the collaboration betweendeveloper and customer.Estimation has always been challenging in Agile as requirements are volatile. This encourages researchersto work on effort estimation. There are many reasons for the gap between estimated and actual effort, viz., project, people, and resistance factors, wrong use of cost drivers, ignorance of regression testing effort, understandability of user story size and its associated complexity, etc. This paperreviewed the work of numerous authors and potential researchers working on bridging the gap of actual and estimated effort. Through intensive and literature review, it can be inferred that machine learning models clearly outperformed non-machine learning and traditional techniques of estimation. Keywords: Machine Learning, Scrum, Scrum Projects, Effort Estimation, Agile Software Development

Analisis Dampak Perubahan Artefak Kebutuhan Berdasarkan Kedekatan Semantik Pada Pengembangan XP

The Extreme Programming (XP) development method is popular because of the flexibility of the development process, it can accommodate changes quickly. But this method has a weakness in terms of documentation. It is expected that the speed of discovering which parts of the source code need to be changed will be greatly improved by analyzing the impact of changes on the requirements document. In this study, a method of analyzing the impact of changes is proposed by tracing changes in the artifact of the need to find out the source code that occurs. Early language methods and semantic approaches are used. Based on the proximity of the semantics, it will be analyzed to find out the elements in the source code that use the Spearman Correlation Coefficient. The test dataset in this study consisted of the source code in the PHP programming language as well as the functional requirements of the software. Requirements change list is generated by analysis of the latest 2 (two) expert versions of the source code. The changing needs are described in a user story document. Based on the test results in this study, the average precision was 0.1725 and the average recall value was 0.6041.

Sistem Informasi Rekam Medis Berbasis Web Pada Klinik Risa Rafana Menggunakan Metodologi Extreme Programming

Risa Rafana is a clinic that located at Wage Batujai West Praya, Central Lombok, West Nusa Tenggara Province. Risa Rafana clinic has problems in medical records processing because the existing system could not systematically assess patient, so the clinicians had trouble for finding the data of patients when had been in manual system. The is development method that was used is Extreme Programming methodology. The method prioritizing of clients as a resource person who understand the system that will be created, from the client itself acquired user story. The Stages that will be created such as planning, design, coding and testing. The information system is designed by concept of UML (Unified Modeling Language) and developed using Framework PHP (Hypertext Preprocessor), which is a web-based CodeIgniter. The processing of database by MySQL. The information system could process data of patients, doctors, specialists, labs, rontgen, medications, so it could make medical records information and made report of patient’s surgery, reporting of laboratory check, reporting of medicine prescription, reporting of drug selling that has been given to patients, so it made easier to diagnose the disease

Extending the Participant’s Voice to Guide Artificial Intelligence Transformation Using Futures Methodology and Layered User Story Analysis

Artificial intelligence (AI) is a vital driver of the next wave of automatisation of Industry 4.0. It impacts product-based and service-based organisations and is becoming an investment stream in organisational transformation strategies. The transformation teams that deploy AI use agile incremental methodologies that ideally match the learning and adaptation requirements for the machine, as well as the human user who is the source of data and requires a service response. This research outlines a layered analysis process of 65 user stories (a common agile method of obtaining user requirements) generated via a participatory process, involving 110 participants in three workshop settings, in what they determined AI would not do. The results outline the workshop approach undertaken to generate user stories and the analysis of user stories via persona and futures methodology causal layered analysis (Inayatullah S. 1998. Causal layered analysis. Futures 30(8): 815-829). The final component of the analysis generated a futures focussed set of guiding principles that can be used as a lens to broaden the transformation teams perspective in AI deployment. Concepts also consider the importance of futures literacy as a key competency of AI creation teams.

Modified Usability Test Scenario: User Story Approach to Evaluate Data Visualization Dashboard

The data processing results are commonly displayed in a dashboard with various graphic visualization forms to deliver new knowledge easier to understand by users. However, many data analysis dashboards cannot communicate the knowledge effectively and efficiently given the unsuitable design implementation. Therefore, research to measure the interface display's effectiveness in the data analysis system is deemed necessary. This research proposed a scenario modification in the usability test with a user story approach to measuring the system interface display in delivering the information to users. The approach of a usability test with the user story is expected to be capable of helping the researcher in understanding the user habits indirectly. There were 20 participants to validate the proposed method. Participants were asked to use the system and answer several questions to develop their user experience. After developing user experience for each user, the System Usability Scale (SUS) was conducted. SUS score results obtained from this research was 75.25. Besides, the researcher also measured the understanding level among the users using questionnaires. The questionnaire results were converted into numbers and resulted in a mean value of 91.8. Those two values indicate the users' ability to use the system well and obtain the new knowledge displayed in the data analysis dashboard.

User Story Estimation based on the Complexity Decomposition using Bayesian Networks

Currently, in Scrum, there are different methods to estimate user stories in terms of effort or complexity. Most of the existing techniques consider factors in a fine grain level; these techniques are not always accurate. Although Planning Poker is the most used method in Scrum to estimate user stories, it is primarily effective in experienced teams since the estimation mostly depends on the observation of experts, but it is difficult when is used by inexperienced teams. In this paper, we present a proposal for complexity decomposition in a coarse grain level, in order to consider important factors for complexity estimation. We use a Bayesian network to represent those factors and their relations. The edges of the network are weighted with the judge of professional practitioners about the importance of the factors. The nodes of the network represent the factors. During the user estimation phase, the Scrum team members introduce the values for each factor; in this way, the network generates a value for the complexity of a User story, which is transformed in a Planning Poker card number, which represents the story points. The purpose of this research is to provide to development teams without experience or without historical data, a method to estimate the complexity of user stories through a model focused on the human aspects of developers.