Effort Estimation across Mobile App Platforms using Agile Processes: A Systematic Literature Review

Altaleb, Abdullah; Gravell, Andrew M.

doi:10.17706/jsw.13.4.242-259

Cited by 10 publications

(12 citation statements)

References 50 publications

(49 reference statements)

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“…Software developers require effective effort estimation models to facilitate project planning and for the eventual successful implementation of the project [15]. If the effort estimations are accurate, they can contribute to the success of software development projects, while incorrect estimations can negatively affect companies' marketing and sales, leading to monetary losses [16]. Software project estimation involves the estimation of the effort, size, staffing, schedule (time) and cost involved in creating a unit of the software product [17], [18].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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 paper 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.

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Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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“…There exists a systematic literature review [14] which has provided an overview of the current state-ofthe-art for effort estimation techniques in mobile app development which use the Agile process. 21 papers were found among this literature; 13 of the 21 studies concerned the estimation size metrics and techniques in mobile app development, whereas 8 studies concerned the applicability of the Agile process in the development of mobile apps.…”

Section: Related Workmentioning

confidence: 99%

“…[13]. Another systematic literature review was conducted for the effort estimation techniques in mobile apps [14]; as a result, no previous studies were found regarding the state-of-practice to investigate and validate the suitability of existing estimation techniques which are used in the Agile process, such as Planning Poker, for mobile app development.…”

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confidence: 99%

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An Empirical Investigation of Effort Estimation in Mobile Apps Using Agile Development Process

Altaleb¹,

Gravell²

2019

JSW

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Effort estimation is essential in order for a project manager and development team members to be able to successfully plan for a software project. The planning and development of mobile applications present many challenges. The aim of this study is to provide and report an overview on the state of the practice of effort estimation techniques that companies use for their mobile app projects. This study focuses on organisations which apply the Agile development process during their projects. We conducted structured and semi-structured interviews with 20 Agile practitioners at 18 different organisations. The results revealed that Planning Poker (PP) and Expert Judgment (EJ) were the most frequently used estimation techniques in mobile app projects.

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“…The initial development costs of mHealth apps can range from the thousands to the hundreds of thousands of dollars, with factors such as the number of screens, complexity of content (static or dynamic), and inclusion of media files (e.g. video), all contributing to higher costs [18,19]. Further, there are many non-trivial issues in the development and effective design of the components of mobile health systems currently being addressed by the mobile computing research community, such as energy efficiency, data management, human-computer interaction factors, and developing flexible and generic APIs to support health apps [20,21].…”

Section: Introductionmentioning

confidence: 99%

schema: an open-source, distributed mobile platform for deploying mHealth research tools and interventions

Shatte

Teague

2020

BMC Med Res Methodol

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Background: Mobile applications for health, also known as 'mHealth apps', have experienced increasing popularity over the past ten years. However, most publicly available mHealth apps are not clinically validated, and many do not utilise evidence-based strategies. Health researchers wishing to develop and evaluate mHealth apps may be impeded by cost and technical skillset barriers. As traditionally lab-based methods are translated onto mobile platforms, robust and accessible tools are needed to enable the development of quality, evidence-based programs by clinical experts. Results: This paper introduces schema, an open-source, distributed, app-based platform for researchers to deploy behavior monitoring and health interventions onto mobile devices. The architecture and design features of the platform are discussed, including flexible scheduling, randomisation, a wide variety of survey and media elements, and distributed storage of data. The platform supports a range of research designs, including cross-sectional surveys, ecological momentary assessment, randomised controlled trials, and micro-randomised just-in-time adaptive interventions. Use cases for both researchers and participants are considered to demonstrate the flexibility and usefulness of the platform for mHealth research. Conclusions: The paper concludes by considering the strengths and limitations of the platform, and a call for support from the research community in areas of technical development and evaluation. To get started with schema, please visit the GitHub repository: https://github.com/schema-app/schema.

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Effort Estimation across Mobile App Platforms using Agile Processes: A Systematic Literature Review

Cited by 10 publications

References 50 publications

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

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

An Empirical Investigation of Effort Estimation in Mobile Apps Using Agile Development Process

schema: an open-source, distributed mobile platform for deploying mHealth research tools and interventions

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