Enabling real-time feedback in software engineering

Vargas, Enrique Larios; Hejderup, Joseph; Kechagia, Maria; Bruntink, Magiel; Gousios, Georgios

doi:10.1145/3183399.3183416

Cited by 12 publications

(5 citation statements)

References 14 publications

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“…Linking information across repositories may allow us to access additional data for SP changes and information changes. However, linking multiple repositories is not a trivial task (Vargas et al 2018;Tiwari et al 2016). Nonetheless, we carefully check the project documentation of the studied projects 1516 1718 19 and find that JIRA is their main repository to store the information of a work item and the SP estimation.…”

Section: Internal Validitymentioning

confidence: 99%

Story points changes in agile iterative development

2022

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Story Points (SP) are an effort unit that is used to represent the relative effort of a work item. In Agile software development, SP allows a development team to estimate their delivery capacity and facilitate the sprint planning activities. Although Agile embraces changes, SP changes after the sprint planning may negatively impact the sprint plan. To minimize the impact, there is a need to better understand the SP changes and an automated approach to predict the SP changes. Hence, to better understand the SP changes, we examine the prevalence, accuracy, and impact of information changes on SP changes. Through the analyses based on 19,349 work items spread across seven open-source projects, we find that on average, 10% of the work items have SP changes. These work items typically have SP value increased by 58%-100% relative to the initial SP value when they were assigned to a sprint. We also find that the unchanged SP reflect the development time better than the changed SP. Our qualitative analysis shows that the work items with changed SP often have the information changes relating to updating the scope of work. Our empirical results suggest that SP and the scope of work should be reviewed prior or during sprint planning to achieve a reliable sprint plan. Yet, it could be a tedious task to review all work items in the product (or sprint) backlog. Therefore, we develop a classifier to predict whether a work item will have SP changes after being assigned to a sprint. Our classifier achieves an AUC of 0.69-0.8, which is significantly better than the baselines. Our results suggest that to better manage and prepare for the unreliability in SP estimation, the team can leverage our insights and the classifier during the sprint planning. To facilitate future studies, we provide the replication package and the datasets, which are available online.

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Section: Internal Validitymentioning

confidence: 99%

Story points changes in agile iterative development

2022

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“…In addition, companies like Kiuwan, Kovair, and Tasktop have recently started offering software and services for software analytics 2 . Furthermore, very recent research tools are CodeFeedr [21] and Q-Rapids [16]. Despite these efforts, there are still challenges for companies developing commercial systems to understand how to integrate heterogeneous data sources for software analytics.…”

Section: Background and Related Work 21 Software Analytics And Softwmentioning

confidence: 99%

Towards Automated Data Integration in Software Analytics

Martínez‐Fernández

Jovanovic

Franch

et al. 2018

Proceedings of the International Workshop on Real-Time Business Intelligence and Analytics

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Software organizations want to be able to base their decisions on the latest set of available data and the real-time analytics derived from them. In order to support "real-time enterprise" for software organizations and provide information transparency for diverse stakeholders, we integrate heterogeneous data sources about software analytics, such as static code analysis, testing results, issue tracking systems, network monitoring systems, etc. To deal with the heterogeneity of the underlying data sources, we follow an ontology-based data integration approach in this paper and define an ontology that captures the semantics of relevant data for software analytics. Furthermore, we focus on the integration of such data sources by proposing two approaches: a static and a dynamic one. We first discuss the current static approach with a predefined set of analytic views representing software quality factors and further envision how this process could be automated in order to dynamically build custom user analysis using a semi-automatic platform for managing the lifecycle of analytics infrastructures. CCS CONCEPTS• Software and its engineering → Maintaining software;

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“…Of particular relevance is the analysis of git repositories [8], as widely used type of repositories, and GitHub as popular social coding platform [9]. Various platforms have been developed to provide software analytics services to stakeholders [10][11][12]. These analytics services either integrate directly into the Continuous Integration (CI) pipeline or they are to be operated externally [13].…”

Section: Introductionmentioning

confidence: 99%

Integrated Visual Software Analytics on the GitHub Platform

Scheibel,

Blum,

Lauterbach

et al. 2024

Computers

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Readily available software analysis and analytics tools are often operated within external services, where the measured software analysis data are kept internally and no external access to the data is available. We propose an approach to integrate visual software analysis on the GitHub platform by leveraging GitHub Actions and the GitHub API, covering both analysis and visualization. The process is to perform software analysis for each commit, e.g., static source code complexity metrics, and augment the commit using the resulting data, stored as git objects within the same repository. We show that this approach is feasible by integrating it into 64 open source TypeScript projects. Furthermore, we analyze the impact on Continuous Integration (CI) run time and repository storage. The stored software analysis data are externally accessible to allow for visualization tools, such as software maps. The effort to integrate our approach is limited to enabling the analysis component within a project’s CI on GitHub and embed an HTML snippet into the project’s website for visualization. This enables a large amount of projects to have access to software analysis as well as provide means to communicate the current status of a project.

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Enabling real-time feedback in software engineering

Cited by 12 publications

References 14 publications

Story points changes in agile iterative development

Story points changes in agile iterative development

Towards Automated Data Integration in Software Analytics

Integrated Visual Software Analytics on the GitHub Platform

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