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The presence of experts, such as a data protection officer (DPO) and a privacy engineer is essential in Privacy Requirements Engineering. This task is carried out in various forms including threat modeling and privacy impact assessment. The knowledge required for performing privacy threat modeling can be a serious challenge for a novice privacy engineer. We aim to bridge this gap by developing an automated approach via machine learning that is able to detect privacy-related entities in the user stories. The relevant entities include (1) the Data Subject, (2) the Processing, and (3) the Personal Data entities. We use a state-of-the-art Named Entity Recognition (NER) model along with contextual embedding techniques. We argue that an automated approach can assist agile teams in performing privacy requirements engineering techniques such as threat modeling, which requires a holistic understanding of how personally identifiable information is used in a system. In comparison to other domain-specific NER models, our approach achieves a reasonably good performance in terms of precision and recall.

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.

Context: User stories are often used for elicitation and prioritisation of requirements. However, the lack of a widely adopted user story template, covering benefit and the usage (or not) of a persona, can affect user stories’ quality, leading to ambiguity, lack of completeness, or accidental complexity. Objectives: Our goal was to analyse the differences between 4 alternative user story templates when creating and understanding user stories. Methods: We conducted a quasi-experiment. We asked 41 participants to perform creation and understanding tasks with the user story templates. We measured their accuracy, using metrics of task success; their speed, with task duration; visual effort, collected with an eye-tracker; and participants’ perceived effort, evaluated with NASA-TLX. Results: Regarding the impact of the different templates in creating user stories, we observed statistically significant differences in some of the metrics for accuracy, speed and visual effort. For understanding user stories, we observed small differences in terms of visual effort. Conclusions: Although some templates outperformed others in a few metrics, no template obtained the best overall result. As such, we found no compelling evidence that one template is "better" than the others.

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.

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.

Spikes can be an essential component of the agile development cycle, because they assist the teams, for both technical and functional issues, to identify any uncertainty in a user story, leading to a more efficient solution to the problem. The use of spikes in agile software development (ASD) can enable organizations to produce quality software by employing the required technical expertise, planning the entire development cycle and ensuring that the client’s requirements are adhered to. This study aims to examine the use of spikes in ASD. It explores the role, efficiency and efficacy of spikes in various software development domains through the different agile methods. An exploratory research design is adopted to achieve this purpose, whereby mixed methods are used to collect concurrently both qualitative and quantitative data from the experts recruited to the study. Through the survey, it establishes that the primary role of spikes is risk management through investigations to understand user stories and reveal any uncertainty. Conclusively, the study findings imply that spikes have become an essential tool for most agile teams in ASD. The efficiency and effectiveness that are reported show that the majority of experts in software development have realized the value of using spikes in their processes.

Nowadays most of software development companies have adopted agile development methodologies, which suggest capturing requirements through user stories. The use of these good practices improves the organization of work teams and the quality of the resulting software product. However, user stories are too often poorly written in practice and exhibit inherent quality defects. In addition, it is common to find the user stories of a software project immersed in large volumes of issues request logs from software quality tracking systems, which makes difficult to process them later. In order to solve these defects and to formulate high quality requirements, a current trend is the application of computational linguistic techniques to identify and then process user stories. In this work, we present two recurrent neural network models that were developed for the identification of user stories in issue records from software quality tracking systems for further processing.

In this article, a multi-criteria approach is proposed to prioritize user-stories in an Agile Software Development environment. User-stories are characterized by their interdependencies and the effort of development. The PROMETHEE II multi-criteria method is proposed as a technique to find a ranking of user-stories, but it needs information about preference thresholds and criteria weights. These parameters are considered stochastic variables and a simulation process is performed to explore robustness of the user-stories prioritization. We show that the information provided by the approach reveals zones of ambiguity in which some user-stories cannot be ranked. An example illustrates this approach and its utility is analyzed. Limitations of the approach are discussed and future research is proposed.

The focus of agile methodology is on customer satisfaction through the early and continuous delivery of valuable software. In agile, requirements are represented in the form of user stories. And the user stories are represented from the user’s point of view. The user stories are effective only when the software practitioners are aware of the user story quality and customer value delivery. In this research work, we studied how well are the user stories used in practice. And are agile software practitioners using user stories and using them correctly? Furthermore, are they aware of the quality issues in the user stories? It was observed from our study that all agile practitioners do not use user stories. The results show that only 45% of agile practitioners used user stories. And only 14.81% of these practitioners had a sound understanding of user stories. This suggests that most of the agile software practitioners may not be using user stories correctly. Additionally, the results also show that backend developers do not seem to focus much on user stories when compared to frontend and most importantly the full-stack developers. Nonetheless, there is still a significant knowledge gap. Therefore, we see it as a general need to train and educate agile professionals about user stories so that they can be used in an effective way to generate customer value.

Scrum is a type of agile process that incrementally, iteratively and continuously deliver software based on sprint time box. It is composed by User Stories, product backlog, sprint backlog, scrum team and sprints. Scrum team take user stories from product backlog into sprint backlog to start each sprint and deliver products at the end of each sprint. Sprint retrospective and review occurs at the end of each sprint to evaluate the delivered products and team performance. Based on the Scrum guide, scrum is easy to be understood but hard to be measured. Especially, it is depended largely on the performance of team dynamics referring to team compositions and task allocations, as its optimization make big impact on each sprint result. A simulation tool is also designed and developed to carry on scrum team modelling and simulation which has realized all the designed strategies to carry on experiments and evaluation. The tool (Z. Wang, 2018; Zhe Wang, 2018, 2019a, 2019b)can simulate all types of scrum context and team composition to test designed strategies under various what-if assumptions in agent-based modelling.

Unit testing is part of software testing in which an application split up small parts is known as units. The software development technique also contains test-driven development (TDD) that unit tests are applied to support the development process. The aim of this paper is to evaluate quality, productivity and defect rate on tests by applying test-driven development approach. This expected system establishes the defect-based, user story-based and test-based of regression analysis method to examine the performance effect on quality, productivity, and defect - rate. This expected system’s outcomes studied the productivity’s effect is good, the effect of quality slightly diminished and the defect rate’s effect is quite reduced. Test-Driven Development supports issues to be observed at the earliest, which has the impact of reducing the resolution cost but also the no: of bugs. This approach gives the developer confidence to execute the refactoring and on-going improvement tasks essential to the success of the method.

Participatory design is an approach in human-computer interaction that involves all relevant stakeholders coequally in the design process. A recent participatory method for visualization design is the creative visualization-opportunities (CVO) workshop, which is used to efficiently develop visualization design requirements in the early stages of applied visualization work. In this paper we report on our experiences of running four CVO workshops in different domains with diverse participants to explore new methods and variations of workshop variables. Through reflection on our experiences, we propose two contributions that extend existing guidance for planning, executing, and analyzing CVO workshops: a set of 12 pragmatic recommendations that extend and complement existing ones; and a recommended method for analyzing workshop results, called user stories. Additionally, we report on the outcomes of our successful workshops to provide evidence for the efficacy of CVO workshops.

This paper proposes a just-in-time approach to introduce adaptive planning in personal daily context. Adaptive planning is known to be effective in agile development, which is expected to be useful for our daily life as well. The chatbot-based approach has been proposed for modeling personal daily context as user story graph. This paper extends this approach by adopting the design of sprint planning. To evaluate the effectiveness of the proposed method, a short-term real-world simulation using a storytelling interface is conducted. The result shows that the proposed adaptive planning framework could lead to better decision-making during individual’s daily life.

In the size estimation software, there are many methods that have proven their reliability. One of them is Use Case Points (UCP). UCP has a well-known advantage based on the use case scenario which is a reformation of the user story in the software requirements specification (SRS) document. However, UCP also has several weaknesses, including the use case is a summary of the user story. User stories often do not reveal detailed data. Therefore, the potential ambiguity of the use case must be watched by a business/system analyst. On the other hand, there is an international association called COSMIC, which has developed a global standard for calculating the size of the software namely ISO/IEC 19761. The COSMIC model begins with a user story which is then carried out cascade to sequence diagrams to make an engagement between process/method flow and data. The purpose of this study is to substitute the use case weight of the pure UCP method, to become a COSMIC functional size unit (Cfsu). Then, the estimation results of the two are compared with the actual effort. The case study used as a comparison of the COSMIC and UCP methods is the Hair Salon Online Booking Application. From this study the results obtained are the deviation between the results of the original UCP estimate (keep use case weight) of the actual effort is 76.85 percent. As for software effort estimation using early COSMIC is 92.67 percent against the actual effort.

Chili is one of the horticultural commodities that is the biggest contributor to inflation for the Indonesian economy. This is caused by the high level of consumption of chili by the public, while the price of chili tends to fluctuate throughout the year. This can come from a variety of factors, one of which is the long chili product distribution chain. With the help of information technology that has developed rapidly, the problem of price fluctuations can be reduced by creating a digital market for buying and selling chili. The digital market can accelerate the process of chili transactions throughout Indonesia so that it can narrow the distribution chain. The application to be developed is a web-based marketplace called Tokocabai. Back-end development will use gRPC and GraphQL as an API service. Front-end development will use the Vue Js framework. Tokocabai application development uses extreme programming methods. The stages of extreme programming methods are planning, design, coding, testing, and release. The iteration that has been successfully carried out is twice with the number of user stories as many as 19. The number of user stories in iteration one is eight and the second iteration is 11. The feature categories that have been successfully implemented are auth, product catalog, profile, transaction, and product review.

The user story widely studied insufficiently describes the software requirements. Many studies discuss the challenges of requirements specifications and proposed solutions. However, there are many agile methods and each method embraces different practices. Therefore, the solution has to follow each method’s ceremonies. Only a few studies discuss conducted practices in requirements specification development with the agile method and there are no studies that discuss practices comparisons among these methods. In this paper, we performed a systematic literature review to gather the available studies in procuring a current insight into the requirements engineering practices incorporate into the agile method. This study aims to map the variability and commonality practices among agile methods. The various and standard agile RE practices show crucial practices in the requirements specification development process. Moreover, it gives information on practices from other methods that increase the success of requirements specification development. From the systematic literature review, we found a total of 12 studies relevant to the study. There are eight variability and commonality practices between Scrum, XP, and Lean methods.

The development of methodology and support tools of the design process and practical implementation of the manufacturing enterprise common information space (CIS) is considered. The proposed methodology allows top management, analysts, developers and IT specialists to respond quickly to changing organizational and technical conditions of production and impact of the external environment, to clarify and agree on requirements to elements of the enterprise control system, to continuously improve and modernize the CIS during the operation of the enterprise. It is shown that the application of existing methodologies and notations is not enough to ensure consistency at each level of CIS design with the corresponding program documents: business development strategy, functional strategies (including information technology development strategy, digital transformation strategy, etc.), project description and technical tasks for software and hardware development, etc. The proposed methodology involves using IDEF0 notation at the top level with decomposition and business process modeling in BPMN or eEPC notations at the middle level. For modeling and software development at the lower level it is proposed to use flexible development methodologies - the agile methods based on the use of corresponding models: user stories, abstract UML models, block diagrams. The advantages and peculiarities of practical application of the proposed methodology in the design of the CIS and elements of the production executive system of the manufacturing enterprise are considered.

In the software development process, effort estimation is essential and a critical phase for the development team in order to ensure that development tasks will be delivered within the planned time. This paper presents a confirmatory case study in an IT company, which examined its current estimation techniques and its process in the context of mobile app development in the Agile process. Moreover, the study provides, and has validated, a proposed estimation technique, namely Pair-estimation, in order to enhance the accuracy of the existing technique. This study, in addition, presents the effectiveness of estimation factors/predictors in supporting the development team to manage, estimate and create subtasks for their user stories.

​© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., In the context of digital transformation, speeding up the time-to-market of high-quality software products is a big challenge. Software quality correlates with the success of requirements engineering (RE) sessions and the ability to collect feedback from end-users in an efficient, dynamic way. Thus, software analysts are tasked to collect all relevant material of RE sessions and user feedback, usually specified on written notes, flip charts, pictures, and user reviews. Afterward comprehensible requirements need to be specified for software implementation and testing. These activities are mostly performed manually, which causes process delays, with a negative effect on software quality attributes such as reliability, usability, comprehensibility. This paper presents Requirements-Collector, a tool for automating the tasks of requirements specification and user feedback analysis. Our tool involves machine learning (ML) and deep learning (DL) computational mechanisms enabling the automated classification of requirements discussed in RE meetings (stored in the form of audio recordings) and textual feedback in the form of user reviews. We use such techniques as they demonstrated to be quite effective in text classification problems. We argue that Requirements-Collector has the potential to renovate the role of software analysts, which can experience a substantial reduction of manual tasks, more efficient communication, dedication to more analytical tasks, and assurance of software quality from conception phases. The results of this work have shown that our tool is able to classify RE specifications and user review feedback with reliable accuracy.

The overall quality and success of software highly depends on the involvement of stakeholders. Requirements elicitation supports RE analyst to gather requirements from the stakeholders based on their needs. There are multiple elicitation techniques present in literature and used by the practitioners. Some of them are questionnaires, interviews, prototyping, and user stories etc. However, these techniques are based on textual representation of requirements. These techniques are quite common among the requirement engineers yet problems of ambiguity, inconsistency, incompleteness still exist mostly due to their textual nature and lack of stakeholder involvement. Lack of clarity about the system increases the ambiguity of what exactly are the system requirements. Since elicitation is carried at an early stage of development the users are not sure of what they want, as requirements tend to evolve with the help of discussions and interactions among various stakeholders and technical team. Furthermore, the conventional elicitation methods are limited when it comes to stakeholders’ participation and involvement, thus leaving a space for more ambiguous and incomplete requirements. In this work, Gamification, a game-based context will be used in non-gaming context for user involvement in fun ways. During elicitation, gamification would help to involve and interact with the stakeholders, with an intention to develop their interest in eliciting and finalizing system requirements. The goal of this paper is to reduce ambiguity during requirements elicitation. This would help in reducing the cost and time of development. Furthermore, we will elicit software requirements using gamification by developing a gamification tool with a focus to elicit unambiguous requirements by ensuring users’ participation and maintaining interest. The validation of tool would be done using multiple confirmatory case studies from software industry.

In Malaysia, Heart Failure (HF) is one of the commonest reasons for hospitalization, with a quarter of HF patients readmitted within 30 days from the onset of acute HF. Reducing frequent hospitalization from HF would significantly reduce the burden on the health care system and resources. The opportunity exists to create digital health system to provide continuous patient care after the diagnosis of HF and subsequent discharge from inpatient care to reduce hospital readmission. This paper reports our ongoing project in Malaysia with the Ministry of Health Malaysia cardiac centers to address some of the barriers to continuous care for patients with chronic HF using digital health systems’ interventions. We have applied a combination of existing requirements approaches – work system design, User Stories, personas, and emotional goal modeling – for the elicitation, modeling, and analysis of requirements. In this paper we report the results of our research including key contributions, lessons learned and the strengths and limitations of our approaches.

User stories are commonly used to capture user needs in agile methods due to their ease of learning and understanding. Yet, the simple structure of user stories prevents us from capturing relations among them. Such relations help the developers to better understand and structure the backlog items derived from the user stories. One solution to this problem is to build goal models that provide explicit relations among goals but require time and effort to build. This paper presents a pipeline to automatically generate a goal model from a set of user stories by applying natural language processing (NLP) techniques and our initial heuristics to build realistic goal models. We first parse and identify the dependencies in the user stories, and store the results in a graph database to maintain the relations among the roles, actions, and objects mentioned in the set of user stories. By applying NLP techniques and several heuristics, we generate goal models that resemble human-built models. Automatically generating models significantly decreases the time spent on this tedious task. Our research agenda includes calculating the similarity between the automatically generated models and the expert-built models. Our overarching research goals are to provide i. an NLP-powered framework that generates goal models from a set of user stories, ii. several heuristics to generate goal models that resemble human-built models, and iii. a repository that includes sets of user stories, with corresponding human-built and automatically generated goal models.

Effort estimation is essential for all development teams in order to ensure the user's story for the software project is delivered on time, boxed released. The characteristics of mobile apps make app development different from other traditional software. There are many challenges in developing a mobile app that could lead to inaccurate estimation of user stories. Therefore, the aim of this paper is to provide a comprehensive investigation into the factors that affect the accuracy of effort estimation. The effort estimation factors have been collected from previous studies and validated with 20 practitioners across 18 organisations in the development field of mobile applications.

Software engineering is the application of principles used in engineering design, development, testing, deployment, and management of software systems. One of the software engineering’s approaches, highly used in new industries, is agile development. User stories are a commonly used notation to capture user requirements in agile development. Nevertheless, for the elaboration of user stories, a high level of collaboration with the client is necessary. This professional skill is rarely measured or evaluated in educational contexts. The present work approaches collaboration in software engineering students through multimodal learning analytics, modeling, and evaluating students’ collaboration while they are writing user stories. For that, we used multidirectional microphones in order to derive social network analysis metrics related to collaboration (permanence and prompting) together with human-annotated information (quality of the stories and productivity). Results show that groups with a lower productivity in writing user stories and less professional experience in managing software requirements present a non-collaborative behavior more frequently, and that teams with a fewer number of interventions are more likely to produce a greater number of user stories. Moreover, although low experience subjects produced more user stories, a greater productivity of the most experienced subjects was not statistically verified. We believe that these types of initiatives will allow the measurement and early development of such skills in university students.

Object-oriented analysis is a significant step that plays a vital role in the success of software development. The planning and management stages, in particular, profoundly rely on the deliverance of an accurate estimate that takes the software's complexity and size into consideration. Today, several software industries are transforming their development methodologies to Agile due to its ability to deliver value in a short time and its cost efficiency. However, Agile methods prevent heavyweight modeling analysis and depend on user stories to drive the estimation process. Because user stories are descriptive language, they may not provide a clear picture for the implementation. Also, they may not help Agile developers give an accurate estimation due to their difficulty in measuring the complexity and size of a feature. Thus, this paper presents a new Agile artifact called developer story that allows the Agile developer to not only analyze and design software products but also predict the size of each feature, including its complexity. In this paper, a case study is presented that shows how the utilization of developer story is a practical approach in predicting the source code size of a feature and its complexity.

This paper proposes a computer-understandable presentation as user story graph and a method for obtaining users’ daily context using a conversational interface. Lean Manufacturing, originally designed for minimizing storage costs and increasing productivity, has been successfully adopted in software development and brought up the popularity of Agile Development in the last couple of decades. In addition to software development, it has extended to development in personal and professional life management, such as Personal Kanban and bunch of TODO-like applications. However, most practices and experiences shared are currently still within original methodology and tools from manufacturing or project development, where adaptation to the personal application has not yet been enough.This paper employs the user story model from requirements engineering to represent personal daily context. The proposed system is designed based on a conversational interface, which maps occurrences from personal daily context into a user story graph extended for describing personal daily context. This paper describes a mechanism of constructing user story graph through a chatbot and illustrates how to use the obtained graph to assist individual task management through a couple of scenarios.

In the past few years, there has been observed explosive growth in the development of Mobile Applications across Android and iOS operating system 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 the 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. In order to test the mobile apps, manual testing procedures takes prolonged amount of time in writing test cases and even the full testing requirements are not met. In addition to this, lack of sufficient knowledge by the tester also impacts overall quality and assurance that app is bug free. To overcome all the issues of testing, and to assure that apps designed by developers are almost bug free, we propose a new testing methodology cum tool “AgileUATM” which works primarily towards white-box and black-box testing. With this tool, all the test cases are generated automatically based on user stories and acceptance criteria by using formal specification and Z3 SMT solvers. To test the validity of the proposed tool, we applied the tool in real-time operational environment with regard to test Mobile apps. Using this tool, all the acceptance criteria is determined via user stories. The testers/developers specify requirements with formal specifications based on programs properties, predicates, invariants, and constraints. From the results, it is observed that the proposed tool i.e. AgileUATM generated effective and accurate test cases, test input, and expected output was generated in a unified fashion from the user stories to meet acceptance criteria. In addition to this, the tool also reduced the development time to identify test data as compared to manual Behavior Driven Development (BDD) methodologies. With this tool, the developers got better idea with regard to required tests and able to translate the customers natural languages to the computer language as well.

In this modern world, software products have significant impacts on every aspect of peoples' life. Requirements engineering is one of the most critical activities in software development in which the foundation of the product is laid. In order to provide structure in requirements, the user stories concept is often used. The user story concept emphasizes information in three central parts, the stakeholder's role, the requirement, and the business value which will be satisfied by the requirement. Stakeholders' participation is crucial in gathering, eliciting, and analyzing requirements; however, frequently due to circumstances, stakeholders provide minimum information related to the software requirements. In order to increase user's participation in providing stories related to the software requirements, our research aims to develop a gamified web-based support tool for the stakeholders and engineers to use in gathering requirements while implementing the user story concept. The gamified support tool is then evaluated to assess the system adoption regarding its use to support users in providing requirements regarding a specific software product. Results show that the support tool receives scores as follow, 81.1% for Joy, 73.4% for Control, 67.2% for Focused Immersion, 60.6% for Temporal Dissociation, 80% for Curiosity, 76.8% for Perceived Ease of Use, 72.9% for Perceived Usefulness, and 76.2% for Behavioral Intention to Use. Based on the interview with the users, the support tool shows excellent potential to be further developed to support the requirements engineering activity in software development.

The quality assessment is an essential step in the software development process; it takes place previous and after the development. Internal quality is a set of characteristics from an internal approach in the software such as requirements, UML diagrams, and the code. These characteristics are constant during the software life cycle. The external quality metrics are the ones that require the end product and, in many cases, the users involvement. Several authors stated that the external quality of the product is related to the assurance of the internal quality of the project. For that reason, this study proposes a framework for assessing the internal quality of user stories to improve the external quality of the project deliveries. The internal quality assessment is based on the grammatical structure of the user stories, and the external quality considers the functionality and usability of the product deliveries. The experiment for validating the framework was conducted with 19 developers considering three different projects which gathered 46 user stories. The findings suggest that the presence of adjectives in user stories improves the usability and the correctness of the product is related to the developer’s experience.

Learning requirements engineering (RE) notations is a tedious task for most people, because this learning activity is all but engaging. As an alternative to traditional educational methods, we propose BakeRE, a serious educational game for RE. The game focuses on specific learning objectives: the specification and analysis of requirements with user stories. BakeRE is the first game proposed to address these learning objectives. It is a multilevel puzzle game that can complement courses (traditional or on-line), such as a general software engineering or a specialized RE course. The player assembles user stories for a specific system by combining building blocks (roles, actions, benefits) from a predefined collection. As the player progresses through the levels, the difficulty increases. At the end of each level, learning feedback is provided to the player. Besides describing the game and its learning objectives, we present the game design process and outline in-progress research that aims to extend BakeRE through its embedding within an RE course.

Although users feel more engaged when they are involved in the elicitation, negotiation and prioritization of requirements for a product or service they are using, the quality of crowdsourced requirements remains an issue. Simple notations like user stories have been highly adopted by practitioners in agile development to capture requirements for a software product, but their utilization in crowdsourced requirements engineering is still scarce. Through a case study of a web application for sports tournament planning, we investigate how a dedicated platform for user story writing in crowd requirements engineering is valued by its users and we show that the delivered requirements are not inferior to those written by professionals.

Product Owners (PO) in the Scrum framework have an important role in the development process. While the POs primal description is straightforward - the actual implementation of this role in industries is not. Many companies face the difficulty of assigning the right level of tasks and responsibilities to this role. To provide solutions to this problem, the Product Owner role became a subject of research. However, most of the studies focus on the actual state of the role to propose solutions on how to tailor it. What is missing is the Scrum Teams perspective. Therefore, we were interested in the Teams expectations on the Product Owner role. Which tasks do they expect to be performed by this role and how would they characterize a perfect Product Owner? In an attempt to answer this question, we conducted an online survey in the oil and gas industry and gathered feedback from all members of the Scrum Team. Our findings indicate that the Scrum Team expects the Product Owner to write user stories and prioritize the backlog solely. Other tasks are expected to be done either in direct collaboration with the management or the scrum master or are not expected to be done by the Product Owner role at all. Also, the respondents would characterize a perfect Product Owner primarily as trustworthy.

The behavior, attributes and properties of a software system is represented in a set of requirements that are written in structured natural language and are usually ambiguous. In large development projects, different modeling techniques are used to create and manage these requirements which aid in the analysis of the problem domain. Requirements are later used in the development process to create test cases, which is still mainly a manual process. To automate this process, we plan to use several of the techniques used in model-driven software development and Natural Language Processing(NLP). The approach under consideration is to use a model-to-model transformation to convert requirements into test cases with the support of Stanford CoreNLP techniques. Key to this transformation process is the use of meta-modeling for requirements and test cases. In this paper we focus on creating a comprehensive meta-model for requirements that can represent both use cases and user stories and performing preliminary analysis of the requirements using NLP. In later work we will develop a set of transformation rules to convert requirements into partial test cases. To show the feasibility of our approach we develop a prototype that can accept a cross-section of requirements written as both use cases and user stories.

To specify good requirements, system analysts need to understand the domain knowledge of the system. There are several techniques in requirements elicitation to improve domain knowledge understanding, such as user interviews, questioners, document analysis, and brainstorming. Most of these techniques require profound stakeholder involvement. However, not all software projects can do this task due to limited time or availability of stakeholders. In agile software development, the user story is the de facto standard used for capturing and writing functional requirements. The user story is an appropriate format and easy to understand for writing the results of requirements elicitation. This study purposes a conceptual model to extract user story from online news for improving domain knowledge understanding. The information in the online news contained lesson learned related to certain events. This information may improve the functionality of the software products. The user story consists of three aspects, namely: who, what, and why. Aspect of who represents the role or user, aspect of what shows the purpose or feature, while the aspect of why explains the reason. This format can summarize the lessons learned in the news. Our experimental results indicate that this conceptual model can extract user story from online news. The model manages to extract 105 user stories from 92 aspects of what/why candidate and 109 aspects of who candidate.

This paper presents a method to support the design and the implementation of democratic information system in organizations. Ethical principle of democracy is today a challenge to propose a solution to the major issue of Shadow IT especially. Our method called DEMOS focuses on end-users’ viewpoint concept to propose a participative and collaborative approach for information system co-construction. It combines different participative tools such as photolanguage, mind map or User Story writing. This article presents strategies and intentions of DEMOS process with the MAP formalism and proposes a detailed description of DEMOS meta-model and key concepts. We conducted an experiment in 2018 with lifelong training service at the University Toulouse 1. A qualitative study evaluates the effectiveness of DEMOS.

This paper proposes a generic agri-food supply chain traceability system based on blockchain technology implementing the "from-farm-to-fork" (F2F) model currently used in the European Union, which can integrate current traceability rules and processes. The proposed system allows the consumer to reconstruct the product history up to the origin in order to verify product health and quality by simple QR code scan. The blockchain chosen for this purpose is Hyperledger Sawtooth, issued with writing permissions and rules to guarantee access only to members recognized as legitimate participants in the process. The whole system has been realized according to an agile methodology (ABCDE), recently devised for designing a general blockchain system with software engineering practices by mean of User Stories and UML diagrams, in order to obtain a higher software quality. All of the involved operators are able to identify any participants along the entire supply chain, increasing the degree of trust between organizations and individuals, with autonomous management of temporal sequence of activities.