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Security analysts rely on scenarios to assess vulnerabilities, project attacks, and decide on security requirements that mitigate the threat. However, eliciting natural language scenarios from stakeholders can be an ad-hoc process and subject to ambiguity and incompleteness. In this paper, we examine systematic scenario elicitation by introducing a method based on user stories that uses a simplified process model of iterative scenario refinement. The process consists of three steps: 1) eliciting an interaction statement that describes a critical action performed by a user or system process; 2) eliciting one or more descriptive statements about a technology that enables the interaction; and 3) refinement of the technology into technical variants that correspond to design alternatives. We empirically evaluated our method by implementing our prototype in a user study that collects 30 security scenarios from participants. Based on our analysis, our proposed method is shown effective. Participants had a 100% task completion rate with 57% of participants achieving complete task-success, and the remaining 43% of participants achieving partial task-success. We also show the effect of security domain knowledge, and the benefit of using structure when collecting security requirements in natural language text. Finally, we present lessons learned and future research directions.

Estimating the cost and schedule of agile software projects is critical at an early phase to establish baseline budgets and schedules for the selection of competitive bidders. The challenge is that common agile sizing measures such as story points and user stories are not practical for early estimation as these are often reported after contract award in DoD. This study provides a set of effort and schedule estimation models for agile projects using a sizing measure that is available before proposal evaluation based on data from 36 DoD agile projects. The results suggest that initial software requirements, defined as the sum of functions and external interfaces, is an effective sizing measure for early estimation of effort and schedule of agile projects. The models accuracy improves when application domain groups and peak staff are added as inputs.

The term "software quality" is widely used, and although it has many definitions, no one definition is universally accepted. Often, the definition refers to specific phases of the software development process and not to software as a whole. In our article, in order to improve the quality of the software, we decided to improve the quality of the phases. To do that, we will focus attention on the drivers that advance quality value and use a new concept called QVD - quality value drivers. We focused on the requirements phase of software development, which probably ranks as the crucial first step. Hence, as a QVD we present the idea of "User Story" (US), a short and simple description of a functionality valuable to a user of a system. In the study, a comparison is made between requirements written by the US method and requirements that are not. After analyzing the results, we concluded that requirements written by the US method have been better understood and evaluated as less difficult to develop. The overall quality rating of their writing is higher than previously. In addition, learning the US method gives the person the ability to better assess the quality of requirements. Finally, improving the writing of the requirements using the US method as QVD improves the quality of the development process, eventually improving the software quality.

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., Metode pengembangan Extreme Programming (XP) termasuk populer, dikarenakan adanya fleksibilitas proses pengembangan sehingga dapat menampung perubahan dengan cepat. Tetapi metode ini memiliki kelemahan dalam hal dokumentasi. Tim pengembang kesulitan menemukan bagian kode sumber yang perlu diubah jika kebutuhan diubah. Seberapa besar dampak atas perubahan kebutuhan terhadap kode sumber tersebut juga tidak diketahui. Diharapkan kecepatan menemukan bagian mana dari kode sumber yang perlu diubah akan sangat meningkat dengan analisis dampak perubahan pada dokumen kebutuhan. Dalam penelitian ini diusulkan metode analisis dampak perubahan dengan melakukan penelusuran perubahan yang terjadi pada artefak kebutuhan untuk mengetahui kode sumber yang terdampak untuk diterapkan dalam lingkungan pengembangan XP. Metode pemrosesan bahasa alami dan kedekatan semantik digunakan. Berdasarkan nilai kedekatan semantiknya akan dianalis untuk mengetahui elemen pada kode sumber yang terdampak menggunakan Koefisien Korelasi Spearman. Dataset pengujian dalam penelitian ini terdiri dari kode sumber dalam bahasa pemrograman PHP serta kebutuhan fungsional dari perangkat lunak. Dari kode sumber tersebut akan dilakukan pemrosesan populasi kode sumber. Daftar perubahan kebutuhan dibuat oleh pakar dengan menganalisa 2 (dua) versi terbaru dari kode sumber. Perubahan kebutuhan tersebut di deskripsikan dalam sebuah dokumen user story. Berdasar hasil ujicoba pada penelitian ini diperoleh rata-rata nilai precision 0.1725 serta rata-rata nilai recall 0.6041.

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.

Requirements specifications are essential to properly communicate requirements among the software development team members. However, each role in the team has different informational needs in order to perform their activities. Thus, the requirements engineer should provide the necessary information to meet each team member's necessities to reduce errors in software development due to inadequate or insufficient communication. Although some research is concerned with communicating requirements among clients and analysts, no related research has been found to evaluate and improve requirements communication within the software development team. With this in mind, we present the ReComP framework, which assists in the identification of problems in the artifacts used to communicate requirements, identification of informational requirements for each role of the development team, and provide improvement suggestions to address requirements communication problems. ReComP was developed using the Design Science Research (DSR) method and this paper presents the results of two DSR cycles considering the use of ReComP for the developer and tester roles by using, respectively, user stories and use cases as requirements specifications. The results provide evidence that ReComP helps software development teams to identify and improve issues in the requirements specifications used for project communication. In two independent studies, ReComP was able to decrease the frequency of problems by 77% in user stories identified by developers and the frequency of all (100%) problems in use cases identified by testers.

El Instituto Geofísico de la Escuela Politécnica Nacional menciona que el Ecuador está cerca de la zona donde convergen las placas Nazca y Sudamericana, lo que determina una importante actividad sísmica. Este trabajo investigativo describe la creación de una aplicación móvil que como resultado agiliza el registro de haber sentido el movimiento telúrico tomando la ubicación exacta mediante geolocalización, además de datos relevantes como fecha, hora y qué tan fuerte se sintió el sismo. Para llevar a cabo el sistema planteado se utilizó la metodología Scrum, en la cual definieron roles, historias de usuario y producto. Para probar el correcto funcionamiento se realizaron pruebas en dispositivos móviles físicos para la aplicación móvil y la página de administración de sismos.

In Agile model where the software prototypes are developed frequently and also rapidly, testing becomes more critical. Generating an effective Test case for complex system is a challenging task involved in software testing. The major research challenge in this area includes the test case generation with limited resources, identifying the essential functional requirement that plays a crucial role and automation of the test case generation process. To solve this issue, a hybridized bio inspired approach is proposed to generate test cases from the user stories which accepts the business requirements as input, processed using NLP and develop functional test cases from it. The proposed algorithm is compared with other existing algorithms and the experimental results proved that the proposed algorithm is more efficient in many cases.

This study provides the contributions of the implementation and development of DevOps in the integration and deployment of software in the organization due to problems previously detected regarding the speed and quality of reports. The arguments assumed from a DevOps culture, respond to: techniques and practices of continuous integration, continuous deployment, test automation, collaboration, automation, measurement and monitoring; these facts, was thanks to the implementation of the pre-experimental research design of applied type, in a sample of 48 weekly sprints, with a total of 96 user stories of the project taken from the organization. The study allowed to demonstrate the decrease of the Cycletime of days on average, increase the frequency of code release and increase the percentage of attention ratio, based on these results, it was possible to demonstrate the improvement of the speed during the deployment and quality of software processes, these results were thanks to the adoption of DevOps as a culture of interaction and deployment in an organization in the insurance sector.

Context: User stories have been widely accepted as artifacts to capture the user requirements in agile software development. They are short pieces of texts in a semi-structured format that express requirements. Natural language processing (NLP) techniques offer a potential advantage in user story applications. Objective: Conduct a systematic literature review to capture the current state-of-the-art of NLP research on user stories. Method: The search strategy is used to obtain relevant papers from SCOPUS, ScienceDirect, IEEE Xplore, ACM Digital Library, SpringerLink, and Google Scholar. Inclusion and exclusion criteria are applied to filter the search results. We also use the forward and backward snowballing techniques to obtain more comprehensive results. Results: The search results identified 718 papers published between January 2009 to December 2020. After applying the inclusion/exclusion criteria and the snowballing technique, we identified 38 primary studies that discuss NLP techniques in user stories. Most studies used NLP techniques to extract aspects of who, what, and why from user stories. The purpose of NLP studies in user stories is broad, ranging from discovering defects, generating software artifacts, identifying the key abstraction of user stories, and tracing links between model and user stories. Conclusion: NLP can help system analysts manage user stories. Implementing NLP in user stories has many opportunities and challenges. Considering the exploration of NLP techniques and rigorous evaluation methods is required to obtain quality research. As with NLP research in general, the ability to understand a sentence’s context continues to be a challenge.

This paper considers the problem of software requirements capturing for business process model evaluation and recommendations generation to suggest how detected modeling errors may be eliminated in order to improve business process model correctness. Existing software tools for business process model analysis are based on metrics and thresholds that allow assume presence of errors in business process models, but they are not capable to recommend structural changes required to eliminate detected modeling errors. Therefore, business process model analysis and improvement tasks become relevant, since early detection and elimination of possible errors presented in business process models may allow organizations avoid extra costs that may occur on any of the steps of business process lifecycle. Since business process models are shared organizational assets, it is also necessary to consider the capabilities of collaborative and concurrent usage of business process models by multiple stakeholders. Hence, the workflow of business process model analysis and improvement was analyzed and its key steps, which describe expected user and software behavior, were formalized using the IDEF0 functional model. Functional software requirements were captured in the form of user stories according to modern agile practices of software development. These user stories are based on features and drawbacks of existing software tools for business process model analysis. Captured user stories were formalized using the use case modeling. Non-functional software requirements were also captured; they include maintainability, readability, testability, understandability, integrability, and complexity requirements. Captured requirements can be used to design and develop business process model analysis and improvement software capable to provide recommendations to eliminate detected modeling errors. У даній роботі розглядається проблема визначення вимог до програмного забезпечення для аналізу моделей бізнес-процесів та формування рекомендацій щодо усунення виявлених помилок моделювання для підвищення коректності моделей бізнес-процесів. Існуючі програмні засоби аналізу моделей бізнес-процесів базуються на метриках та порогових значеннях, що дозволяють припустити про наявність помилок у моделях бізнес-процесів, проте не надають структурні зміни, необхідні для усунення виявлених помилок моделювання. Тому актуальною стає проблема аналізу та вдосконалення моделей бізнес-процесів, оскільки раннє виявлення та усунення можливих помилок, представлених у моделях бізнес-процесів, може дозволити організаціям уникнути зайвих витрат, які можуть виникнути на будь-якому з етапів життєвого циклу бізнес-процесів. Оскільки моделі бізнес-процесів є спільними організаційними ресурсами, також необхідно враховувати можливості спільного та одночасного використання моделей бізнес-процесів декількома зацікавленими сторонами. Отже, було проаналізовано робочий процес аналізу та вдосконалення моделей бізнес-процесів, а його основні етапи, що описують очікувану поведінку користувачів та програмного забезпечення, були формалізовані за допомогою функціональної моделі IDEF0. Функціональні вимоги до програмного забезпечення були відображені у вигляді користувацьких історій згідно із сучасними практиками гнучкої розробки програмного забезпечення. Дані користувацькі історії засновані на особливостях та недоліках існуючих програмних засобів для аналізу моделей бізнес-процесів. Визначені користувацькі історії були формалізовані за допомогою моделювання варіантів використання. Також були враховані нефункціональні вимоги до програмного забезпечення, які включають придатність до підтримки та тестування, читабельність, зрозумілість, інтегрованість та складність. Визначені вимоги можуть бути використані для проектування та розробки програмного забезпечення для аналізу та вдосконалення моделей бізнес-процесів, здатного пропонувати рекомендації з усунення виявлених помилок моделювання.

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.

User stories play an important role in agile development systems. In this study, a method of summarising user stories is proposed to reuse them in the future. To enhance the results, quality improvement should be made on user stories. It would help developers build better results, and it may also lead to omitting some essential information. To avoid such issues, user stories are duplicated in two exact similar groups, and quality improvement is made on one set while the other set remains unattained. With the help of a modified bag of words and a verb parser, a collection of keywords and key verbs are extracted for both groups. Afterwards, automatic user stories are made, and then an expert improves them. Next, some experts choose between the results and select the better ones. The result is evaluated by applying different experiments on the framework and prototype implementation on 14 data sets of a user story from industry and a fake data set from Duke University. The result showed 97% of micro F-measure and 93% of macro F-measure, which are promising. These new user stories can be used as the base user stories in future similar projects.

Sequential rhetoric can serve as a framework to instruct UX practice (through user story maps) to new learners because it is both approachable and affordable. Sequential rhetoric consists of five m...

Context. The article describes the relevant planning process of software projects, planning problems and different solutions to these problems basis on use of the Scrum methodology. Objective. The purpose of the work is to develop the technology for solving the sprint planning task in the face of uncertainty and possible risks from software development standpoint. Method. The most used software life cycle models are described. The choice of the Scrum as a widely used representative of agile methodology for software development is justified. An analytical review of the methods for estimation of the complexity of user stories is carried out. The major problems of sprint planning are highlighted. The model of the business process to implement an ITproject by Scrum in the form of an BPMN-diagram has been developed. The algorithm to solve the problem of Sprint Backlog planning with uncertainty has been elaborated. The common process of user stories selection from Product Backlog to Sprint Backlog and ways of solving the possible problems are considered. The task of estimation of labor intensity of user stories and the task of risk evaluation in planning are formalized. The technology of user story selection for Sprint Backlog has been developed. Numerical studies of the decision support technology proposed in the article are carried out. It allows suggesting it as the practical tool during sprint planning. The method of adequacy evaluation of proposed technology is offered. The set of key performance indicators for assessing the team performance is selected. Results. The sprint planning technology was developed, which project managers, product owners and development teams for increasing the effectiveness of decision-making process can use. Conclusions. The conducted experiments have confirmed the importance of the proposed decision support technology and allow recommending it for use in practice for planning of software projects. Scientific novelty is to improve the sprint planning process with the assistance of the proposed technology, which alleviates uncertainty while defining labor intensity of user stories and decreases time spent on decision making.

User stories are popular for conveying requirements in agile software projects. Despite existing quality criteria, authors make formal mistakes that result in “bad” user story quality. If developers have insufficient experience in balancing quality problems, the creation of a shared mental model is impossible, thus increasing the risk of impacts on the project’s success. This article provides a work-in-progress research model to set these variables in relation and establish a systematic method to uncover answers regarding their correlation. Details on the effects support research in agile requirements engineering to gain a better understanding of cognitive processes in the comprehension of user stories. In addition, insights can help to develop design recommendations and AI tools to improve user stories. A first evaluation of the model provides promising insights into the behavior and forms a basis for future research.

At present, Mashup development has attracted much attention in the field of software engineering. It is the focus of this article to use existing open APIs to meet the needs of Mashup developers. Therefore, how to select the most appropriate open API for a specific user requirement is a crucial problem to be solved. We propose a Hybrid Open API Selection Approach for Mashup development (HyOASAM), which consists of two basic approaches: one is a user-story-driven open API discovery approach, and the other is multidimensional-information-matrix- (MIM-) based open API recommendation approach. The open API discovery approach introduces user stories in agile development to capture Mashup requirements. First, it extracts three components from user stories, and then, it extracts three corresponding properties from open API descriptions. Next, the similarity calculation is performed on two sets of data. The open API recommendation approach first uses MIM to store open APIs, Mashups, and the invoking relationship between them. Second, it enters the matrix obtained in the previous step into a factorization machine model to calculate the association scores between the Mashups and the open APIs, and TOP-N open API lists for creating the Mashup are obtained. Finally, experimental comparison and analysis are carried out on the PWeb dataset. The experimental results show that our approach has improved significantly.

Understanding of system requirements that satisfy end users’ needs is fundamental of system development, yet challenging when end users are unable to address their needs explicitly. Although a number of scholars have been designing and applying requirement elicitation techniques, there is a research gap in Spatial Decision Support System (SDSS) with Web-based Geographical Information System (Web-GIS) in water resource management for disaster risk reduction. The gap addresses especially design elicitation techniques and their performances 1) to understand data types used for decision making, 2) set timing for sharing the data to accomplish end users’ tasks, and 3) compile the data to be represented so as to facilitate end users’ decision making. This study therefore designed a requirement elicitation technique by advancing User Story Mapping (USM) and validated through a workshop using mock-up system interface with potential end users who are in charge of water resource management in Myanmar’s Bago River Basin. Through the research it could be validated that the user stories-based approach enabled end users to decompose their operation activities into tasks. It also allowed them to link to necessary data with visual image for facilitating their task accomplishments and decision making for water resource management. It was revealed that the benefits of using the designed approach are not only just to summarize necessary data and information for end users’ decision making but also to encourage them to proactively consider data utilization into their operations. For further development of the requirement elicitation to understand end users needs, insights and recommendations for the proposed technique designing and conducting of the workshop were obtained.

There has been observed explosive growth in the development of mobile applications (apps) for Android and iOS operating systems, which has led to the direct impact towards mobile app development. In order to design and propose quality-oriented apps, it is the primary responsibility of developers to devote time and sufficient efforts towards testing to make the apps bug-free and operational in the hands of end-users without any hiccup. Manual testing procedures take a prolonged amount of time in writing test cases, and in some cases, the full testing requirements are not met. Besides, the insufficient knowledge of tester also impacts the overall quality and bug-free apps. To overcome the obstacles of testing, we propose a new testing methodology cum tool called “AgileUATM” which works primarily towards white-box and black-box testing. To evaluate the validity of the proposed tool, we put the tool in a real-time operational environment concerning mobile test apps. By using this tool, all the acceptance criteria are determined via user stories. The testers/developers specify requirements with formal specifications based on programs properties, predicates, invariants, and constraints. The results show that the proposed tool generated effective and accurate test cases, test input. Meanwhile, expected output was also generated in a unified fashion from the user stories to meet acceptance criteria. The proposed solution also reduced the development time to identify test data as compared to manual Behavior-Driven Development (BDD) methodologies. This tool can support the developers to get a better idea about the required tests and able to translate the customer’s natural languages to computer languages as well. This paper fulfills an approach to suitably test mobile application development.

An application with a good user experience design can increase the conversion rate by 400%, while an application with suitable user interfaces only increases the conversion rate by 200%. In general, documenting the user experience design process is done manually through paper or workbooks, resulting in low shareability among team members. This research proposes developing a new website-based application that suits the user's needs by paying attention to the user experience aspect. The application development uses the five planes method, consisting of 5 layers, namely the strategy plane, scope plane, structure plane, skeleton plane, and surface plane. This application provides features that represent all components of the strategy plane, consisting of (1) SWOT, (2) comparison matrix, (3) lean canvas, (4) project statement, (5) user persona, (6) user story. Each feature gives a more detailed explanation of the meaning, why this component is essential, and how to fill it. Users can also export details created into documents in PNG, PDF, and XML formats. Users can also add team members to the project created by using the invite member feature. The trial was conducted on 2018 and 2017 PENS IT students to determine user satisfaction using the Net Promoter Score method. The results of the Net Promoter Score are -0.89 and -2.056, which means that the application still needs improvement in some parts. The application for documenting the user experience process contributes to UX designers, especially beginners, making documentation and understanding and learning the user experience design process.

Sustainability has become an important topic in the field of requirements engineering. In general, five sustainability dimensions can be distinguished: economical, environmental, technical, social and individual. Software requirements can have positive and negative impacts on these different dimensions. A number of methods and frameworks have been already proposed that deal with the question on how impacts of software requirements on sustainability can be identified and managed as part of requirements engineering. Some open questions, however, remain: How can sustainability be supported by using agile development practices from frameworks like Scrum? Is it productive to consider sustainability in sprint planning meetings or product reviews? Is it useful to add sustainability aspects to acceptance criteria of user stories or a definition of done? This paper describes an ongoing doctoral study that attempts to find answers on the prior questions. The goal is to develop a sustainability-aware Scrum framework inspired by existing requirements engineering methods to improve the sustainability impacts of software systems and to make software as sustainable as possible.

User stories are widely used to capture the desires of the users in agile development. A set of user stories is easy to read and write but incapable of representing the hierarchical relations and synergies among the user stories. By contrast, goal models are uncommon in industrial projects however they can express the structure and other relations among requirements captured as goals. This paper presents ArTu, a tool for generating goal models from user stories to effortlessly benefit from both. Given a set of user stories, our tool generates goal models with different structures depending on the heuristic selected by the user. Users can import, edit, and export model data in different formats.

New techniques for managing, specifying, and analyzing requirements in software engineering projects are frequently presented by consultants and agile trainers. However, the effectiveness of these techniques is not evaluated in a rigorous manner, leaving practitioners with the question “Will it work in our company?” In this paper, we investigate the performance of a user story refinement technique named Example Mapping (EM). This is a time-boxed workshop in which people from different disciplines work collaboratively in order to refine, or clarify, a user story with the use of examples. The creation of such examples is intended not only to obtain a more precise specification, but also and mostly to achieve shared understanding on the user story to develop among the team members. We investigate the performance of EM via two longitudinal case studies. To enable a rigorous validation of EM, we first define the Refinement Evaluation Tool (RET), a survey-based measurement instrument that extends the Method Evaluation Model with questions that cover the shared understanding dimension. The results from our case studies show that EM contributes to the shared understanding within a team; certain conditions are necessary: the user stories should not be too small-sized. We also investigated the learning effect for EM; our data indicates that two sessions are generally necessary for the team members to use the technique effectively.

A wide range of new modeling languages with a specific focus on cloud computing, also known as cloud modeling languages (CMLs), have been introduced to help developers describe, evaluate, and deploy cloud applications. In general, CMLs define applications as interconnected cloud components within an architectural topology. However, in agile software development, developers describe system-level functionalities using user stories or epics to define end-user scenarios. So far, a CML bridging the gap between formal architectural descriptions and the informal scenario descriptions from agile development is missing. We present Clams (Cloud application modeling solution), a scenario-based CML. Clams uses cloud computing patterns as architectural placeholders in combination with message sequence charts. We introduce standard tooling to handle Clams models and show how one can refine patterns to concrete service offerings. Additionally, we also provide a development framework to support the creation of custom tools to evaluate, analyze, or translate Clams models efficiently.

In the Software Engineering area, Web Accessibility is gaining more space, establishing itself as an important quality attribute. In the context of agile development, approaching this type of requirement by development teams is still a challenging task, as there is often a lack of knowledge about the domain and a lack of methods or tools to support the specification of accessibility requirements, which end up being neglected or considered only in the final phase of the projects. Therefore, this work proposes the development of a framework to support the specification of web accessibility requirements in an agile context. The framework consists of automating the reuse of accessibility requirements, supporting the generation of artifacts, such as user stories, thus improving communication between stakeholders and supporting the analysis of the possible impact of these accessibility requirements on other system features.

Traditional requirements engineering does not benefit from modern software development techniques. The goal of this tutorial is to revisit requirements elicitation and to bridge the gap between traditional requirements engineering and modern software development. This tutorial will provide the attendees with concrete and immediately applicable guidance by demonstrating how to operationalize a fully-fledged toolchain going from user stories to automated acceptance testing using open-source tools.

Effort estimation is an integral part of activities planning in Agile iterative development. An Agile team estimates the effort of a task based on the available information which is usually conveyed through documentation. However, as documentation has a lower priority in Agile, little is known about how documentation effort can be optimized while achieving accurate estimation. Hence, to help practitioners achieve just-enough documentation for effort estimation, we investigated the different types of documented information that practitioners considered useful for effort estimation. We conducted a survey study with 121 Agile practitioners across 25 countries. Our survey results showed that (1) despite the lower priority of documentation in Agile practices, 98% of the respondents considered documented information moderately to extremely important when estimating effort, (2) 73% of them reported that they would re-estimate a task when the documented information was changed, and (3) functional requirements, user stories, definition of done, UI wireframes, acceptance criteria, and task dependencies were ranked as the most useful types of documented information for effort estimation. Nevertheless, many respondents reported that these useful types of documented information were occasionally changing or missing. Based on our study results, we provide recommendations for agile practitioners on how effort estimation can be improved by focusing on just-enough documentation., To be published at International Conference on Software Maintenance and Evolution (ICSME) 2021

Most agile practitioners employ user stories for capturing requirements, also thanks to the embedding of this notation within development and project management tools. Among user story users, circa 70% follow a simple template: As a role, I want to action, so that benefit. User stories’ popularity among practitioners and their template-based structure make them ideal candidates for the application of natural language processing techniques. In our research, we have found that circa 50% of real-world user stories contain easily preventable linguistic defects. To mitigate this problem, we have created tool-supported methods that facilitate the creation of better user stories. This tutorial combines previous work of the RE-Lab@UU into a pipeline for working with user stories: (1) The basics of creating user stories and their use in requirements engineering; (2) How to improve user story quality with the Quality User Story Framework and the AQUSA tool; (3) How to generate conceptual models from user stories using the Visual Narrator tool and analyze them for possible ambiguity and inconsistency; and (4) How to link requirements to architectures via the RE4SA model. Our approach is demonstrated with results obtained from 20+ software companies employing user stories.

IT services are being built by IT departments and other service providers to address the core technological requirements of organizations. Even if these services solve operational issues, their adoption – because of their internal behavior – has a sustaining or non-sustaining impact on the (long term) strategy of the organization. This impact is called the Business and IT alignment (BITA); as such, it is problematic to estimate before the development of the service without a view on its design. To be properly done, BITA evaluation indeed needs details about the service run-time behavior. Conversely, the agile wave refrains from a detailed upfront software design; functions providing high operational value to users are indeed selected and built for one sprint at a time. The mismatch between a traditional service approach and an agile way of development is therefore quite obvious. The present paper proposes a method (called Agile-MoDrIGo) to reconcile these two approaches. For this purpose, it (i) decomposes services into epic user stories under the scope of which (user-level built) user stories can be mapped (i.e. functional alignment) and (ii) links services as (coarse-grained) conceptual elements along with the strategic objectives they sustain to fine-grained user story functional elements for value-driven prioritization (i.e. strategic alignment). The proposal is presented in the form of a meta-model and supported by a process fragment; it is validated on a case study in healthcare.

The article explores the practicability of employing agile methodology of project management to improve the cooperation way of the faculty in the process of compiling teaching and learning materials for the course of Foreign Language for Professional Purposes. Current research in the field concentrates mainly on techniques and methods of selecting, organizing, and structuring the content, leaving beside the organization of the process itself, which faces many challenges, such as: lack of actual cooperation within the teaching team,  following the traditional ways of designing course materials, treating documentation and planning of the course as a formality.The challenges result in poor quality of university-approved course designs and the necessity for the teachers to construct each class individually, while their efforts should be focused on improving existing content rather than developing their own under increasing study load.The agile methodology of project management, used mainly in the sphere of IT, presents many new possibilities for team work organizing. The Scrum framework is viewed in this article as the one that provides solid ground for enhancing cooperation and improving the content of teaching materials through constant testing, feedback, and adjustment.In this article we analyze and study the main roles, artifacts, and processes stipulated by the aforementioned framework and adjust them to the reality of a university and the needs of teaching staff. The provided examples of developing a backlog of a product, the product being the course materials, set forth the principle of formulating a user story as a skill to be mastered by students.

Geographic information-based planning support tools implemented in a maptable have the potential to mediate collaborative spatial planning processes. However, available tools for a maptable either lack advanced analytical functions or have usability shortcomings. Given these limitations, this research aims to conceptualize an interactive planning support tool intended to fully exploit maptable capabilities while providing spatial analytical functions to better support planning and decision-making processes with a larger group of participants. To do so, we conducted a literature review of reported maptable-based applications and semi-structured interviews with identified intended user groups of such applications, and derived Agile user stories. We identified a) principal spatial analyses, b) must-have functionalities, c) required support for individual contributions, and d) preferred space-time settings for group work collaboration, and based on that conceptualized an interactive tool for a maptable. By involving the intended users in the conception of the tool we revealed a discrepancy between the understanding of scholars and developers with respect to what users need and what they do. Intended user groups require tailored but straightforward instruments, rather than complicated or time-consuming models. Our research has laid down the foundation for future maptable tool development to support collaborative planning processes.

Context - Agile Software Development (ASD) and Reuse-Driven Software Engineering (RDSE) are well-accepted strategies to improve the efficiency of software processes. A challenge to integrate both approaches is that ASD relies mostly on tacit knowledge, hampering the reuse of software development assets. An opportunity to enable RDSE for ASD is by improving the traceability between user stories (USs), the most used notation to register product requirements in ASD. Having enough link semantics between USs could enable defining similarity between them and, consequently, promote RDSE for ASD. However, this is an open challenge. Objective - To propose a taxonomy for adding link semantics between USs, focusing on easing the task of identifying similar ones. Such links, with support of traceability tools, enable the reuse of USs and their related assets. Method : We constructed a taxonomy for types of US focusing on Web Information Systems. The taxonomy is used to classify the US, given two facets: module and operation. Such information is used to infer the similarity between USs using link rules. We developed the taxonomy based on an empirical analysis of five product backlogs, containing a total of 118 USs. Afterward, we validated the taxonomy in terms of its potential to enable the reuse of US-related assets. First, we executed an offline validation by applying it to classify 530 USs from 26 already ended projects. Finally, we applied the taxonomy in a case study with two ongoing projects (59 USs). Results : The proposed taxonomy for USs is composed of two sub-facets, namely, module and operation, which have, respectively, three and 18 terms. In terms of coverage, for the offline study and case study, we classified 90.17% of the USs with the proposed taxonomy. For the case study, we classified all the USs analyzed. Conclusion : We concluded that it is possible to use our approach to compare USs and, consequently, retrieve their related assets. Our results regarding its practical utility have shown that users considered the taxonomy a useful approach to ease the process of assessing the similarity between user stories.

Model-Driven Architecture (MDA) is a framework for software development processes that allows an automatic transformation from a business process model to the code model. In MDA there are two transformation kinds: Transformation from the Computation independent model (CIM) to platform-independent model (PIM), and transformation from PIM to platform-specific model (PSM). In this paper, we based on CIM to PIM transformation. This transformation is done by developing a platform that generates a class diagram, presented in XMI file, from specifications that are presented in user stories, which are written in natural language (English). We used a natural language processing (NLP) tool named "Stanford CoreNLP" for extracting of the object-oriented design elements. Applying our approach to several case studies has given good results.

In UiTM Terengganu, student attendance current manual process is based on Academic Affairs (HEA) criteria. Lecturer has to bring attendance sheet to each class and take student attendance. At the end of semester lecturer has to manually calculate and send the report to HEA. Based on preliminary study, current process causing inefficiency on processing reporting. In order to improve the current process, Student Attendance System (SAS) is a system proposed to be developed for Universiti Teknologi MARA (UiTM) Terengganu. Lecturer is the primary users of the system. These allow user control, update, and view the attendance based on session, course and group. SAS was developed with System Development Life Cycle based on Extreme Programming (XP). XP phases involve phase of select user stories for release, then break down stories to tasks, plan release, develop, release to evaluate it. Then, process is repeated until meet user requirement. System testing based on test plan has been conducted. As for the evaluation, the evaluation process is done by three (3) experts then comment and suggestion is produced. Results based on experts evaluation shows that positive feedback from the experts where the development of SAS caters elements of ease of use, flow is easy to be understood and the system is consistent and follow the standard As conclusion, SAS can be improved based on comments and suggestions form experts and it has a big potential to be implemented in UiTM Terengganu.

This article presents a methodology based on the agile XP process for the development of robot-oriented software in educational platforms using the ROS middleware. The final result was a set of evidences such as user stories, UML-based diagrams and lines of code in the Python language that demonstrate good code quality practices in software development with the use of the object-oriented paradigm. A modified agile methodology is obtained with an evolutionary and incremental design but with a rigorous documentation useful for educational and research projects. Este articulo presenta una metodologia basada en el proceso agil de XP para el desarrollo de software orientado a robots en plataformas educativas usando middleware ROS. El resultado final fue un conjunto de evidencias tales como historias de usuarios, diagramas basados en UML y lineas de codigo en el lenguaje Python que demuestran buenas practicas de calidad de codigo en el desarrollo de software con el uso del paradigma orientado a objetos. Se obtiene una metodologia agil modificada con un diseno evolutivo e incremental, pero con una documentacion rigurosa util para proyectos educativos y de investigacion.

Background: Effort estimations are critical tasks greatly influencing the accomplishment of software projects. Despite their recognized relevance, little is yet known what indicators for inaccurate estimations exist, and which are the reasons of inaccurate estimations. Aims: In this manuscript, we aim at contributing to this existing gap. To this end, we implemented a tool that combines data analytics and developers’ feedback, and we employed that tool in a study. In that study, we explored the most common reasons of inaccurate user story estimations and the possible indicators of inaccurate estimations. Method: We relied on a mixed method approach used to study reasons and indicators for the identification and prediction of inaccurate estimations in practical agile software development contexts. Results: Our results add to the existing body of knowledge in multiple ways. We elaborate causes for inaccurate estimations going beyond the borders of existing literature; for instance, we show that lack of developers’ experience is the most common reason of inaccurate estimations. Further, our results suggest, for example, that the higher the complexity, the higher the uncertainty in the estimation. Conclusions: Overall, our results strengthen our confidence in the usefulness of using data analytics with human-in-the-loop mechanisms to improve effort estimations.

ObjectiveWe sought to demonstrate applicability of user stories, progressively elaborated by testable acceptance criteria, as lightweight requirements for agile development of clinical decision support (CDS).Materials and MethodsUser stories employed the template: As a [type of user], I want [some goal] so that [some reason]. From the “so that” section, CDS benefit measures were derived. Detailed acceptance criteria were elaborated through ensuing conversations. We estimated user story size with “story points,” and depicted multiple user stories with a use case diagram or feature breakdown structure. Large user stories were split to fit into 2-week iterations.ResultsOne example user story was: As a rheumatologist, I want to be advised if my patient with rheumatoid arthritis is not on a disease-modifying anti-rheumatic drug (DMARD), so that they receive optimal therapy and can experience symptom improvement. This yielded a process measure (DMARD use), and an outcome measure (Clinical Disease Activity Index). Following implementation, the DMARD nonuse rate decreased from 3.7% to 1.4%. Patients with a high Clinical Disease Activity Index improved from 13.7% to 7%. For a thromboembolism prevention CDS project, diagrams organized multiple user stories.DiscussionUser stories written in the clinician’s voice aid CDS governance and lead naturally to measures of CDS effectiveness. Estimation of relative story size helps plan CDS delivery dates. User stories prove to be practical even on larger projects.ConclusionsUser stories concisely communicate the who, what, and why of a CDS request, and serve as lightweight requirements for agile development to meet the demand for increasingly diverse CDS.

Requirements elicitation for assistive technology (AT) product development must be collaborative and systemic. This process must ensure that the needs of all different users are identified. For this, UCD methods introduce different tools that seek user involvement and their needs identification. One method commonly used in software development is User Stories. The aim of this paper is to analyse the use of User Stories for requirements elicitation in an AT product development project. This method was applied with three types of users: patients, companions and occupational therapists. For the involvement of these users, the method was customized and two main adaptations were adopted: the stories were written by the development team and all user needs were identified through observations of interactions between patients and prototype. As a result, the development team was able to identify numerous product requirements to be used in later development phases. These requirements were generated by the user needs identified with User Stories. Thus, the method with necessary adaptations, was efficient for requirements elicitation in the AT product development process.

Background: Although agile and Scrum have been important frameworks in software engineering for over a decade, little research has explored how teams use Scrum language within their sprints. Literature review: Most explorations of Scrum communication have been collected through self-reported means. These studies are inherently unable to explore how Scrum teams use Scrum-centric language in their meetings in ways that adhere or run counter to standard Scrum practice. Research questions: 1. In what ways is Scrum reflected in the language used by team members in various sprint meetings? 2. What associations exist between the job title of team members and their use of Scrum language? 3. What does a discourse analysis reveal about the ways in which this team uses language to value and discount Scrum? Research methodology: For three sprints over 10 weeks, I recorded meetings of 27 Scrum team members. I transcribed these meetings, developed a codebook for assigning Scrum language categories, conducted an interrater reliability agreement on the data, completed a correspondence analysis on how Scrum language associates with meeting types and job titles, and conducted a discourse analysis to determine in what ways these teams value and discount Scrum. Results/discussion: Scrum language was found in all recorded meetings across all three sprints, with much language found in the planning meetings. Few associations existed between Scrum language and job title, suggesting that Scrum at this engineering firm is an egalitarian process. In addition, the discourse analysis revealed that this engineering firm valued User Story and Sprint Execution language while discounting Capacity and Story Pointing language. Conclusions: Although this group broadly adheres to Scrum practices about 68% of the time, this study finds that several current standard components of Scrum are routinely discounted. This exploratory study suggests that more research into the in-situ use of Scrum language in engineering workplaces is necessary to better inform engineering professionals about the communicative expectations of Scrum and to better enable engineering communication educators to prepare future engineers for Scrum realities.

Being able to quickly and accurately capture requirements is crucial when using agile methodologies. Requirements, to that end, are often captured in an as-needed and informal manner, with continuous stakeholder interaction. Techniques such as interviews, user stories, rapid feedback, and text mining are commonly used in the industry to gather such informal requirements, which are often congruent with the concept of ‘just-in-time’ (JIT)—informally represented and continuously refined—requirements. Oral communication is an integral part of most of these techniques, and the loss or misinterpretation of verbally communicated requirements is a daunting problem. To address this issue, In this invited paper, we propose a novel framework to assist developers in capturing verbal requirements in complete manner. In particular, our framework automatically captures, transcribes, and mines verbal communication, which in turn produces a set of loosely formulated candidate requirements for further elaboration. We also conducted a survey among practitioners concerning requirements in agile methodologies and our framework. The results of this survey provide positive feedback on the prospects of the framework and also indicate the prevalence of JIT requirements in closed source agile projects. In addition, we proposed a new framework for visual exploration of JIT requirements and presented our JITREvisu prototype tool.

During agile requirements engineering, developers need to assimilate and transform the original requirements information into system functions in the form of user stories. Obviously, this is a challenging cognition-based process, in which developers' cognition plays a key role. However, prior research has not explored developers' cognition during the process. The purpose of this study is to investigate and understand developers' cognitive representation styles and interaction patterns in agile requirements. A classification of developers' cognitive representation styles and interaction patterns was first proposed based on literature review. Then, an empirical research was conducted in a capstone software engineering course. Students were playing the role of developers and engaging in agile software development during this course, so their conversation about splitting and defining user stories was recorded and analyzed to examine developers' cognition via a content analysis method. The results show that, even when facing requirements analysis, developers tend to exhibit a technology-oriented cognitive representation style. Additionally, developers have more cognitive difficulty in determining activity and granularity than the role and business value of a user story. Developers also exhibit a preference for cognitive interaction pattern; assertion, comment, and two question-patterns are the major four patterns in our paper rather than information sharing, which was considered a major pattern in previous research. This paper contributes to our understanding of developers' cognition, further predicting and guiding developers' behaviors toward achieving good quality requirements analysis.

For traditional software development processes, we have detailed empirical knowledge about role-specific information needs that have to be satisfied in requirements documents. Particularly, we gained detailed knowledge about priorities of a set of traditional requirements artifacts in a series of empirical studies from the viewpoint of software architects, usability engineers, and testers. However, little is known about such information needs from the viewpoint of agile team members. Motivated by the widespread use of agile development approaches and existing challenges faced by requirements engineering in agile projects, our current research aims at investigating whether agile teams could also benefit from the empirical results regarding information needs that we gained in our previous research. We envision the development of guidelines based on empirical data in order to support the extensive collaboration and communication necessary in agile projects. In this paper, we present our research agenda as well as first results of our work. This includes a mapping analyis by the authors where the scope and content of the outcome of agile RE practices (e.g., user stories) was compared to previously investigated traditional RE artifacts. This analysis shows that artifacts resulting from agile practices cover key requirements information, but at a lower level of detail than in traditional RE artifacts. Based on these first findings, we conducted interviews and performed surveys with agile team members in order to better understand current challenges and the possible impacts of these challenges. The results reveal that, for instance, less detailed documentation leads to problems such as communication lapses, rework and product inconsistencies in agile settings. We also gained first insights regarding the relevance of agile RE practices from the viewpoint of different agile team members. Finally, we elaborated initial guidelines to be used and evaluated within the scope of industry and research projects in the near future.

Context. Defects such as ambiguity and incompleteness are pervasive in software requirements, often due to the limited time that practitioners devote to writing good requirements. Objective.We study whether a synergy between humans’ analytic capabilities and natural language processing is an effective approach for quickly identifying near-synonyms, a possible source of terminological ambiguity. Method.We propose a tool-supported approach that blends information visualization with two natural language processing techniques: conceptual model extraction and semantic similarity. We evaluate the precision and recall of our approach compared to a pen-and-paper manual inspection session through a controlled quasi-experiment that involves 57 participants organized into 28 groups, each group working on one real-world requirements data set. Results.The experimental results indicate that manual inspection delivers higher recall (statistically significant with p ≤ 0.01) and non-significantly higher precision. Based on qualitative observations, we analyze the quantitative results and suggest interpretations that explain the advantages and disadvantages of each approach. Conclusions.Our experiment confirms conventional wisdom in requirements engineering: identifying terminological ambiguities is time consuming, even when with tool support; and it is hard to determine whether a near-synonym may challenge the correct development of a software system. The results suggest that the most effective approach may be a combination of manual inspection with an improved version of our tool.

An interactive tool with a browser-type interface has been developed for solvent selection using the software R. Two main classes of considerations can be taken into account: technical suitability for the intended duties, and practical considerations including costs and health, safety environment (HSE) impact. The tool builds on quantitative analyses of properties selected by the user for the application at hand. The underlying philosophy is to assist the thought processes of the tool’s users, rather than to prescribe set answers. The tool is a stepping stone toward design-of-experiment in chemical process development, enabling parameter space exploration without specialized software licenses, and grouping properties to assist the users. Six examples of use are given to illustrate various methodologies. In building the tool, scientific software development was found to be more intrinsically iterative than originally expected, with mock-ups and sharing of user stories more agile than lengthy user requireme...

Learning during the pandemic and during the application of new habits in the context of implementing learning that implements the protocol for preventing the spread of Covid-19 has unique and uncertain needs. Unique means that the learning process has special characteristics from pre-pandemic learning. Meanwhile, the meaning of “nonpermanent” is a learning process that changes in learning planning, implementation, and evaluation. This causes the need for new innovations in learning platforms that are able to accommodate this unique and variable learning. This article provides an analysis of the requirements of a blended learning platform. Where changes in dynamic forms of learning give rise to various needs in learning. The method used is the survey, and analysis of responses of respondents using user story quality (USQ). The results found in this study are presented in the form of a table containing the item requirements for developing a blended learning platform.

Agile software development has ended up profoundly prevalent over the final two decades. In conjunction with the increment of these methodology, amount of scientific research on this topic has also increased. This research concentrates on one component from Agile software development which is User Stories (US). In a recent paper, quality framework for User Stories was proposed together with a tool implementing which is still minimal finding to achieve high quality of user story document. It is closely related to the data requirement as part of the success factor in development project. The main goal is to analyze US requirement written and identification of potential errors in datasets that bring the effectiveness in forecasting the quality of User Stories for monitoring purpose. One of the steps require to identify the quality User Stories is by the route passing through data cleaning process. The research analysis considers performing data cleaning and pre-processing towards existing dataset of user story requirement from open-source agile software projects. Results of analyzing the User Stories will reveal the possibility step of data cleaning as initial step to extend the AQUSA tools and forecast the quality of User Stories. Thus, it can be related to the requirements quality based on the number of issues report in the dataset where highest number of issues report can be categorized as poor requirement statement.

Finding a parking space can be very stressful and time consuming. A variety of different vehicle parking applications have been developed but many fail to support diverse end-users. We captured diverse human-centric issues from user reviews and literature, and then created personas that encompass a wide representative range of parking app user groups. Using these personas, user stories were created, categorized and parking app tasks prioritized. We used these to develop a prototype new "smart parking app". A cognitive walk-through was employed using each of the personas and user stories to evaluate the app. With more human-centric factors taken into account in the design and development of the app, we found that majority of the human-centric frustrations identified were resolved, when compared with a commonly used parking app.

Tracing the numerous artifacts produced during a software project is challenging. It is not uncommon to overlook this aspect due to the additional workload to keep organized and effective records of what changes between iterations. In this work, we propose a lightweight approach called U-til for traceability management focusing on the impact of changes in both user stories and test cases. We have conducted a case study to assess the proposal’s impact concerning the efficiency to manage the requirements traceability from the point of view of testers and requirements analysts in the context of an industry software project. We performed quantitative and qualitative analysis before and after applying our approach and observed that it helped the team to manage requirements dependencies and improved the traceability between user stories and test cases.

Quality requirements often receive insufficient attention, both in agile and in traditional software development. This paper describes the quality triage, a quick, agile method in which user stories or features with quality risks are identified. This paper shows how the four qualities scalability, security, safety, and availability are scored at short expert meetings ― triages. In this way, quality risks are made explicit and can be immediately addressed. We illustrate the method with a scenario involving semi-autonomous cars.