Estimating, planning and managing Agile Web development projects under a value-based perspective

Context: The processes of estimating, planning and managing are crucial for software development projects, since the results must be related to several business strategies. The broad expansion of the Internet and the global and interconnected economy make Web development projects be often characterized by expressions like delivering as soon as possible, reducing time to market and adapting to undefined requirements. In this kind of environment, traditional methodologies based on predictive techniques sometimes do not offer very satisfactory results. The rise of Agile methodologies and practices has provided some useful tools that, combined with Web Engineering techniques, can help to establish a framework to estimate, manage and plan Web development projects. Objective: This paper presents a proposal for estimating, planning and managing Web projects, by combining some existing Agile techniques with Web Engineering principles, presenting them as an unified framework which uses the business value to guide the delivery of features. Method: The proposal is analyzed by means of a case study, including a real-life project, in order to obtain relevant conclusions. Results: The results achieved after using the framework in a development project are presented, including interesting results on project planning and estimation, as well as on team productivity throughout the project. Conclusion: It is concluded that the framework can be useful in order to better manage Web-based projects, through a continuous value-based estimation and management process.Ministerio de Economía y Competitividad TIN2013-46928-C3-3-

Empirical research on relative and absolute effort estimation in software development projects

Should we be using relative estimation methods in software effort estimation? This thesis looks into an aspect of agile estimating by comparing the effects of using relative estimation methods with absolute estimation methods for software development effort estimates. The thesis describes a study conducted on a software development project where estimates in story points (relative) and ideal time (absolute) are provided using planning poker

Effort Estimation in Agile Software Development: A Systematic Map Study

Introduction − Making effort estimation as accurate and suitable for software development projects becomes a fundamental stage to favor its success, which is a difficult task, since the application of these techniques in constant changing agile development projects raises the need to evaluate different methods frequently.  Objectives− The objective of this study is to provide a state of the art on techniques of effort estimation in agile software development (ASD), performance evaluation and the drawbacks that arise in its application.  Method− A systematic mapping was developed involving the creation of research questions to provide a layout of this study, analysis of related words for the implementation of a search query to obtain related studies, application of exclusion, inclusion, and quality criteria to filter nonrelated studies and finally the organization and extraction of the necessary information from each study.   Results− 25 studies were selected; the main findings are: the most applied estimation techniques in agile contexts are: Estimation of Story Points (SP) followed by Planning Poker (PP) and Expert Judgment (EJ). The most frequent solutions supported in computational techniques such as: Naive Bayes, Regression Algorithms and Hybrid System; also, the performance evaluation measures Mean Magnitude of Relative Error (MMRE), Prediction Assessment (PRED) and Mean Absolute Error (MAE) have been found to be the most commonly used. Additionally, parameters such as feasibility, experience, and the delivery of expert knowledge, as well as the constant particularity and lack of data in the process of creating models to be applied to a limited number of environments are the challenges that arise the most when estimating software in agile software development (ASD)    Conclusions− It has been found there is an increase in the number of articles that address effort estimation in agile development, however, it becomes evident the need to improve the accuracy of the estimation by using estimation  techniques supported in machine learning  that have been shown to facilitate and improve the performance of this.  Key Words − Effort Estimation; Agile Software Development; Issues and Challenges; Automatic Learning; Performance Metrics  Introducción − Realizar una estimación de esfuerzo lo más precisa y adecuada para proyectos de desarrollo de software, se ha convertido en pieza fundamental para favorecer el éxito y desarrollo de los mismos, sin embargo, aplicar este tipo de estimación en proyectos de desarrollo ágil, en donde los cambios son constantes, la convierte en una tarea muy compleja de implementar.    Objetivo− El objetivo de este estudio es proveer un estado del arte sobre técnicas de estimación de esfuerzo en desarrollo de software ágil, la evaluación de su desempeño y los inconvenientes que se presentan en su aplicación.    Metodología− Se desarrolló un mapeo sistemático que involucró la creación de preguntas de investigación con el fin de proveer una estructura a seguir, análisis de palabras relacionadas con el tema de investigación para la creación e implementación de una cadena de búsqueda para la identificación de estudios relacionados con el tema, aplicación de criterios de exclusión, inclusión y calidad a los artículos encontrados para poder descartar estudios no relevantes y finalmente la organización y extracción de la información necesaria de cada artículo.     Resultados− De los 25 estudios seleccionados; los principales hallazgos son: las técnicas de estimación más aplicadas en contextos ágiles son: Estimación por medio de Puntos de Historia (SP) seguidos de Planning Poker (PP) y Juicio de Expertos (EJ). Soluciones soportadas en técnicas computacionales como: Naive Bayes, Algoritmos de Regresión y Sistema Híbridos; también se ha encontrado que la Magnitud Media del Error Relativo (MMRE), la Evaluación de la Predicción (PRED) y Error Absoluto Medio (MAE) son las medidas de evaluación de desempeño más usadas. Adicionalmente, se ha encontrado que parámetros como la viabilidad, la experiencia y la entrega de conocimiento de expertos, así como la constante particularidad y falta de datos en el proceso de creación de modelos para aplicarse a un limitado número de entornos son los desafíos que más se presentan al momento de realizar estimación de software en el desarrollo de software ágil (ASD)    Conclusiones− Se ha encontrado que existe un aumento en la cantidad de artículos que abordan la estimación de esfuerzo en el desarrollo ágil, sin embargo, se hace evidente la necesidad de mejorar la precisión de la estimación mediante el uso de técnicas de estimación soportadas en el aprendizaje de máquina que han demostrado que facilita y mejora el desempeño de este.    

An Update on Effort Estimation in Agile Software Development: A Systematic Literature Review

[EN] Software developers require effective effort estimation models to facilitate project planning. Although Usman et al. systematically reviewed and synthesized the effort estimation models and practices for Agile Software Development (ASD) in 2014, new evidence may provide new perspectives for researchers and practitioners. This article presents a systematic literature review that updates the Usman et al. study from 2014 to 2020 by analyzing the data extracted from 73 new papers. This analysis allowed us to identify six agile methods: Scrum, Xtreme Programming and four others, in all of which expert-based estimation methods continue to play an important role. This is particularly the case of Planning Poker, which is very closely related to the most frequently used size metric (story points) and the way in which software requirements are specified in ASD. There is also a remarkable trend toward studying techniques based on the intensive use of data. In this respect, although most of the data originate from single-company datasets, there is a significant increase in the use of cross-company data. With regard to cost factors, we applied the thematic analysis method. The use of team and project factors appears to be more frequent than the consideration of more technical factors, in accordance with agile principles. Finally, although accuracy is still a challenge, we identified that improvements have been made. On the one hand, an increasing number of papers showed acceptable accuracy values, although many continued to report inadequate results. On the other, almost 29% of the papers that reported the accuracy metric used reflected aspects concerning the validation of the models and 18% reported the effect size when comparing models.This work was supported by the Spanish Ministry of Science, Innovation and Universities through the Adapt@Cloud Project under Grant TIN2017-84550-R.Fernández-Diego, M.; Méndez, ER.; González-Ladrón-De-Guevara, F.; Abrahao Gonzales, SM.; Insfran, E. (2020). An Update on Effort Estimation in Agile Software Development: A Systematic Literature Review. IEEE Access. 8:166768-166800. https://doi.org/10.1109/ACCESS.2020.3021664S166768166800

UX Poker: Estimating the Influence of User Stories on User Experience in Early Stage of Agile Development

Agile methods are used more and more frequently to develop products by reducing development time. Requirements are typically written in user stories or epics. In this paper, a new method called UX Poker is presented. This is a method to estimate the impact of a user story on user experience before development. Thus, there is the opportunity that the product backlog can also be sorted according to the expected UX. To evaluate UX Poker, a case study was conducted with four agile teams. Besides, a workshop followed by a questionnaire was conducted with all four agile teams. The goal of being able to estimate the UX even before development was achieved. Using UX Poker to create another way to sort the product backlog can be considered achieved in this first evaluation. The results show that UX Poker can be implemented in a real- life application. Additionally, during the use of UX Poker, it was found that a shared understanding of UX began. The participants clarified in the team discussion about UX Poker what related to influence the user stories had on UX and what UX meant for their product

Agile software development practices in Egypt SMEs : a grounded theory investigation

Agile information system development methods have been adopted by most software development organizations due to their proven benefits in terms of flexibility, reliability, and responsiveness. However, companies face significant challenges in adopting these approaches. Specifically, this research investigates challenges faced by software development companies in Egypt while transitioning to Agile. As little previous research is available targeting their concerns, we have conducted a grounded theory investigation. Key problem areas were found including lack of cadence in sprints planning, inadequate use of effort estimation and product quality issues. The developed grounded theory reflects on the key problem areas found with SMEs adopting agile practices and can be used by software development practitioners adopting agile methods in Egypt or similar developing countries as an outline for the common problem areas they are expected to find

Achieving Quality through Software Maintenance and Evolution: on the role of Agile Methodologies and Open Source Software

Agile methodologies, open source software development, and emerging new technologies are at the base of disruptive changes in software engineering. Being effort estimation pivotal for effective project management in the agile context, in the first part of the thesis we contribute to improve effort estimation by devising a real-time story point classifier, designed with the collaboration of an industrial partner and by exploiting publicly available data on open source projects. We demonstrate that, after an initial training on at least 300 issue reports, the classifier estimates a new issue in less than 15 seconds with a mean magnitude of relative error between 0.16 and 0.61. In addition, issue type, summary, description, and related components prove to be project-dependent features pivotal for story point estimation. Since story points are the most popular effort estimation metric in the agile context, in the second study presented in the thesis we investigate the role of agile methodologies in software maintenance and evolution, and prove its undoubted influence on the refactoring research field over the last 15 years. In the later part of the thesis, we focus on recent technologies to understand their impact on software engineering. We start by proposing a specialized blockchain-oriented software engineering, on the basis of the peculiar challenges the blockchain sector must confront with and statistical data retrieved from a corpus of open source blockchain-oriented software repositories, identified relying upon the 2016 Moody’s Blockchain Report. We advocate the need for new professional roles, enhanced security and reliability, novel modeling languages, and specialized metrics, along with new research directions focusing on collaboration among large teams, testing, and specialized tools for the creation of smart contracts. Along with the blockchain, in the later part of this work we also study the growing mobile sector. More specifically, we focus on the relationships between software defects and the use of the underlying system API, proving that our findings are aligned with those in the literature, namely, that the applications which are more connected to API classes are also more defect-prone. Finally, in the last work presented in the dissertation, we conducted a statistical analysis of 20 open source object-oriented systems, 10 written in the highly popular language Java and 10 in the rising language Python. We leveraged two statistical distribution functions–the log-normal and the double Pareto distributions–to provide good fits, both in Java and Python, for three metrics, namely, the NOLM, NOM, and NOS metrics. The study, among other findings, revealed that the variability of the number of methods used in Python classes is lower than in Java classes, and that Java classes, on average, feature fewer lines of code than Python classes

Challenges of using software size in agile software development: A systematic literature review

Academic Papers at IWSM Mensura, IWSM-Mensura 2018; Beijing; China; 19 September 2018 through 20 September 2018Software size is a fundamental measure for software management. Size is used for a variety of purposes, such as benchmarking, normalization, and portfolio measurement, and it is frequently considered as the sole input of estimation. Estimations can be produced for various reasons; e.g., to predict effort, cost and duration of software development projects. There are different types of software size measures. Particularly in projects where agile methodologies are adopted, measurement becomes a significant challenge as it is perceived as a non-value-added task and records of tasks such as requirements identification are not always consistent. The difficulties of applying traditional size measurement techniques in agile contexts, however, do not diminish the need, and new methods and techniques are introduced to improve the manageability of the agile projects. In this paper, we discuss estimation and measurement approaches in relation with ―software size in agile contexts. Based on this review, we present the perceptions of software size and related challenges, such as misinterpretation of size, difficulties in implementation, and acceptability of the measurement processes. We anticipate that providing a baseline for the state of software size measures in agile contexts and presenting related challenges, particularly in terms of its acceptability by practitioners can shed light on the development of new techniques