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Effort estimation based on user stories plays a pivotal role in agile software development, where accurate predictions of project efforts are vital for success. While various supervised ML tools attempt to estimate effort, the prevalence of estimation errors presents significant challenges, as evidenced by the CHAOS report by the Standish Group, which highlights incorrect estimations contributing to a substantial percentage of failed agile projects. This research delves into the domain of user story-based effort estimation in agile software development, aiming to explore the issues arising from inaccurate estimations. The primary goal is to uncover these issues comprehensively and propose potential solutions, thus enhancing the efficacy of the user story-based estimation method. To achieve the research objectives, a systematic literature review (SLR) is conducted, surveying a wide range of sources to gather insights into issues surrounding user story-based effort estimation. The review encompasses diverse estimation methods, user story attributes, and the array of challenges that can result from inaccurate estimations. The SLR reveals a spectrum of issues undermining the accuracy of user story-based effort estimation. It identifies internal factors like communication, team expertise, and composition as crucial determinants of estimation reliability. Consistency in user stories, technical complexities, and task engineering practices also emerge as significant contributors to estimation inaccuracies. The study underscores the interconnectedness of these issues, emphasizing the need for a standardized protocol to minimize inaccuracies and enhance estimation precision. In light of the findings, it becomes evident that addressing the multi-dimensional factors influencing user story-based effort estimation is imperative for successful agile software development. The study underscores the interplay of various aspects, such as team dynamics, task complexity, and requirement engineering, in achieving accurate estimations. By recognizing these challenges and implementing recommended solutions, software development processes can avoid failures and enhance their prospects of success in the agile paradigm. [ABSTRACT FROM AUTHOR]

Requirements Engineering (RE) is a critical process in the development of any software. It requires intensive communication among many stakeholders in order to identify software requirements accurately. As RE activities require intensive communication, cultural influences might need to be considered to improve these activities and to avoid issues that might affect the software project outcomes. In our work, we explored the influence of national culture on RE activities. We conducted an empirical study in two countries that have different cultural profiles: Saudi Arabia and Australia. To explore this issue, we conducted 41 face-to-face interviews. To consolidate the collected data, we conducted also 30 follow-up interviews with the same practitioners. The aim of our study was to empirically identify the set of cultural influences affecting RE activities, and analyse their implication on RE activities. This paper reports the results of the analysis of participants' responses with respect to their industrial profiles, in terms of three factors: the type of software methodology applied by the participants (Traditional vs. Agile), the size of their company/organisation (small, medium, and large), and its type (private vs. government). The results showed a number of significant differences in the cultural influences that determine the type of software development methodology, i.e., Traditional or Agile, being applied within the corresponding company. In this paper, we discuss the identified differences and the factors that determine them. This in-depth analysis provides a broader examination of the influence of culture on RE activities, which might assist RE practitioners to select the most suitable RE practices/methodology to overcome any negative effects of these influences. [ABSTRACT FROM AUTHOR]

Flexible iterative development life cycle, adaptive nature and fast delivery has given Agile an upper edge as compared to all other software development frameworks. In the current industry scenario agile methods are gaining popularity, owing to its people centric approach, hence organizations are adopting agile development methodologies at a large scale. Agile projects work in self-organizing small collaborative teams. Team size varies according to the project requirement however, agile development focus on smaller team size. Supervised machine learning is applied in this study to provide optimum prediction model. All the available regression models in Matlab R2019b are used to predict number of team members required for an agile project. Iterations from five different open source projects are considered for this study. The results after training all the variants of each regression model, namely Linear Regression models, Support Vector Machine models, Tree models, Ensemble models and Gaussian Process Regression models are compared using Root Mean Square Error (RMSE) score and R-squared values. On the basis of evaluative and comprehensive analysis, the most significant model to predict manpower requirement for an agile project has been chosen. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. • We propose developers' cognitive representation styles and interaction patterns in agile requirements. • We examine developers' cognition by their utterances of splitting user stories. • Developers prefer to technology-oriented cognitive representation style even in requirements stage. • Developers have more cognitive difficulty in user stories activity and granularity. • Developers have a preference for four major cognitive interaction patterns. [ABSTRACT FROM AUTHOR]

This paper presents a systematic literature review of agile software development at decision making method for requirement engineering. Presently, agile software development method is operated to cope with requirements that changes dynamically. This study seeks to find out and discuss what types of method that have been exploited for decision making on managing feasible requirements and challenges of decision making in agile software development. Papers reviewed in this study are published from 2017 to present. Resulting 8 papers that have been identified of presenting decision making methods. Using these papers, 11 methods and 7 challenges of decision making identified. This study contributes a review of requirement management and engineering by providing decision making methods on agile software development and the challenges of decision making for requirement engineering. [ABSTRACT FROM AUTHOR]

The paper proposes an ontology-based approach to support for requirements traceability in Agile development. The task of supporting the requirements traceability in a software development project is considered as a part of requirements engineering process. A brief overview of the benefits of requirements traceability usage is given. The expediency of using the ontology-based approach to support for requirements engineering, requirements traceability in particular, is shown through the analysis of scientific publications. OWL ontology is chosen to support the requirements engineering process. The ontology is implemented in the Protégé environment. The developed ontology takes into account particular qualities of working with the requirements in Agile projects, accumulates knowledge about the requirements types and requirements artefacts, enables tracing the relations between them. [ABSTRACT FROM AUTHOR]

Researchers have proposed that generating conceptual models automatically from user stories might be useful for agile software development. It is, however, unclear from the state-of-the-art what a consistent and complementary set of models to generate is, how these models can be generated such that relationships and dependencies in a set of related user stories are unveiled, and why these models are useful in agile software development projects. In this paper, we address these questions through a Design Science research study. First, we define four stylized versions of Unified Modeling Language (UML) diagrams (i.e., use case diagram, class diagram, activity diagram, state machine diagram) that will be the target of the model generation. Although these stylized UML diagrams have a reduced abstract syntax, they offer different perspectives on the software system in focus with potential usefulness for requirements and software engineering. Second, we develop an automated model generation approach based on different design artifacts including a Natural Language Processing (NLP) tool that implements our approach. Key to our solution is the use of the Behavior-Driven Development (BDD) scenario template to document user stories. Using an example set of BDD scenarios as source of the model generation, we demonstrate the feasibility of our approach via the NLP tool that implements our approach. Third, we conduct an empirical study with experts in agile software development involving the researcher-guided interactive use of our tool to explore the use of the generated models. This study shows the perceived usefulness of the models that our tool can generate and identifies different uses and benefits of the models for requirements analysis, system design, software implementation, and testing in projects that employ agile methods. [ABSTRACT FROM AUTHOR]

Nowadays, Agile Software Development (ASD) is used to cope with increasing complexity in system development. Hybrid development models, with the integration of User-Centered Design (UCD), are applied with the aim to deliver competitive products with a suitable User Experience (UX). Therefore, stakeholder and user involvement during Requirements Engineering (RE) are essential in order to establish a collaborative environment with constant feedback loops. The aim of this study is to capture the current state of the art of the literature related to Agile RE with focus on stakeholder and user involvement. In particular, we investigate what approaches exist to involve stakeholder in the process, which methodologies are commonly used to present the user perspective and how requirements management is been carried out. We conduct a Systematic Literature Review (SLR) with an extensive quality assessment of the included studies. We identified 27 relevant papers. After analyzing them in detail, we derive deep insights to the following aspects of Agile RE: stakeholder and user involvement, data gathering, user perspective, integrated methodologies, shared understanding, artifacts, documentation and Non-Functional Requirements (NFR). Agile RE is a complex research field with cross-functional influences. This study will contribute to the software development body of knowledge by assessing the involvement of stakeholder and user in Agile RE, providing methodologies that make ASD more human-centric and giving an overview of requirements management in ASD. [ABSTRACT FROM AUTHOR]

Abstract: Innovative companies need an agile approach towards product and service requirements, to rapidly respond to and exploit changing conditions. The agile approach to requirements must nonetheless be systematic, especially with respect to accommodating legal and non-functional requirements. This paper examines how to support lightweight, agile requirements processes which can still be systematically modeled, analyzed and changed. We propose a framework, RE-KOMBINE, which is based on a propositional language for requirements modeling called Techne. We define operations on Techne models which tolerate the presence of inconsistencies. This paraconsistent reasoning is vital for supporting delayed commitment to particular design solutions. We evaluate these operations with an industry case study using two well-known formal analysis tools. Our evaluations show that the proposed framework scales to industry-sized requirements model, while still retaining (via propositional logic) the informality that is so useful during early requirements analysis. [Copyright &y& Elsevier]

• LEL+ scenarios are used to create more accurate conceptual models in an agile way. • A rule-based methodology allows systematic derivation of mathematical programming models from conceptual models. • A domain ontology provides a semantic model that defines concepts and relationships. • A semantic mediawiki supports conceptual model building and derivation to mathematical programming models. • A fresh tomato packing application is provided. Mathematical programming models are invaluable tools at decision making, assisting managers to uncover otherwise unattainable means to optimize their processes. However, the value they provide is only as good as their capacity to capture the process domain. This information can only be obtained from stakeholders, i.e., clients or users, who can hardly communicate the requirements clearly and completely. Besides, existing conceptual models of mathematical programming models are not standardized, nor is the process of deriving the mathematical programming model from the concept model, which remains ad hoc. In this paper, we propose an agile methodology to construct mathematical programming models based on two techniques from requirements engineering that have been proven effective at requirements elicitation: the language extended lexicon (LEL) and scenarios. Using the pair of LEL + scenarios allows to create a conceptual model that is clear and complete enough to derive a mathematical programming model that effectively captures the business domain. We also define an ontology to describe the pair LEL + scenarios, which has been implemented with a semantic mediawiki and allows the collaborative construction of the conceptual model and the semi-automatic derivation of mathematical programming model elements. The process is applied and validated in a known fresh tomato packing optimization problem. This proposal can be of high relevance for the development and implementation of mathematical programming models for optimizing agriculture and supply chain management related processes in order to fill the current gap between mathematical programming models in the theory and the practice. [ABSTRACT FROM AUTHOR]