skip to main content
10.1145/3555228.3555239acmotherconferencesArticle/Chapter ViewAbstractPublication PagessbesConference Proceedingsconference-collections
research-article

Use Cases for Software Development Analytics: A Case Study

Published: 05 October 2022 Publication History

Abstract

Context Software engineering activities provide practitioners with large volumes of data that software analytics tools can use for many purposes, including defect prediction and effort estimation. However, the adoption of such tools depends on the information they provide and the real needs of practitioners. While existing research has focused on what developers need, the needs of managers are not well understood. Aims This study provides an in-depth analysis of the information needs of software practitioners from one organization that performs research, development, and innovation projects with industry partners. Understanding these practitioners’ needs enables the development of better analytics solutions to support managerial decision-making. Method We interviewed practitioners in leadership positions and analyzed the collected data using Grounded Theory coding techniques, i.e., open and selective coding. Results We identified 19 software analytics use cases and classified them into four dimensions: quality, people, project management, and knowledge management. We also elicited several indicators to meet the identified use cases and captured key aspects concerning the organization’s analytics scenario. Conclusions Although our results are particularly relevant to organizations similar to the one in which we conducted the study, they aim to serve as input for implementing new analytics solutions by practitioners and researchers in general.

Supplementary Material

Interview script and use cases with their respective quotations (supplements.zip)

References

[1]
Abdullah Al-Nayeem, Krzysztof Ostrowski, Sebastian Pueblas, Christophe Restif, and Sai Zhang. 2017. Information needs for validating evolving software systems: An exploratory study at google. In 2017 IEEE International Conference on Software Testing, Verification and Validation (ICST). IEEE, 544–545.
[2]
Andrew Begel and Thomas Zimmermann. 2014. Analyze this! 145 questions for data scientists in software engineering. In Proceedings of the 36th International Conference on Software Engineering. 12–23.
[3]
Jacob T Biehl, Mary Czerwinski, Greg Smith, and George G Robertson. 2007. FASTDash: a visual dashboard for fostering awareness in software teams. In Proceedings of the SIGCHI conference on Human factors in computing systems. 1313–1322.
[4]
Katarzyna Biesialska, Xavier Franch, and Victor Muntés-Mulero. 2021. Big Data analytics in Agile software development: A systematic mapping study. Information and Software Technology 132 (2021), 106448.
[5]
Lionel Briand, Domenico Bianculli, Shiva Nejati, Fabrizio Pastore, and Mehrdad Sabetzadeh. 2017. The case for context-driven software engineering research: generalizability is overrated. IEEE Software 34, 5 (2017), 72–75.
[6]
Raymond PL Buse and Thomas Zimmermann. 2010. Analytics for software development. In Proceedings of the FSE/SDP workshop on Future of software engineering research. 77–80.
[7]
Raymond PL Buse and Thomas Zimmermann. 2012. Information needs for software development analytics. In 2012 34th International Conference on Software Engineering (ICSE). IEEE, 987–996.
[8]
Joelma Choma, Eduardo Martins Guerra, and Tiago Silva Da Silva. 2017. Patterns for implementing software analytics in development teams. In Proceedings of the 24th Conference on Pattern Languages of Programs. 1–12.
[9]
Iris Figalist, Christoph Elsner, Jan Bosch, and Helena Holmström Olsson. 2020. Breaking the Vicious Circle: Why AI for software analytics and business intelligence does not take off in practice. In 2020 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA). IEEE, 5–12.
[10]
Latifa Guerrouj, Olga Baysal, David Lo, and Foutse Khomh. 2016. Software analytics: challenges and opportunities. In 2016 IEEE/ACM 38th International Conference on Software Engineering Companion (ICSE-C). IEEE, 902–903.
[11]
Mohammad Ibraigheeth and Syed Abdullah Fadzli. 2019. Core factors for software projects success. JOIV: International Journal on Informatics Visualization 3, 1(2019), 69–74.
[12]
Silverio Martínez-Fernández, Anna Maria Vollmer, Andreas Jedlitschka, Xavier Franch, Lidia López, Prabhat Ram, Pilar Rodríguez, Sanja Aaramaa, Alessandra Bagnato, Michał Choraś, 2019. Continuously assessing and improving software quality with software analytics tools: a case study. IEEE access 7(2019), 68219–68239.
[13]
Mohd Hairul Nizam Nasir and Shamsul Sahibuddin. 2011. Critical success factors for software projects: A comparative study. Scientific research and essays 6, 10 (2011), 2174–2186.
[14]
Ali Nizam. 2022. Software Project Failure Process Definition. IEEE Access (2022).
[15]
Luca Pascarella, Davide Spadini, Fabio Palomba, Magiel Bruntink, and Alberto Bacchelli. 2018. Information needs in contemporary code review. Proceedings of the ACM on Human-Computer Interaction 2, CSCW(2018), 1–27.
[16]
Mirko Perkusich, Lenardo Chaves e Silva, Alexandre Costa, Felipe Ramos, Renata Saraiva, Arthur Freire, Ednaldo Dilorenzo, Emanuel Dantas, Danilo Santos, Kyller Gorgônio, 2020. Intelligent software engineering in the context of agile software development: A systematic literature review. Information and Software Technology 119 (2020), 106241.
[17]
Kai Petersen and Claes Wohlin. 2009. Context in industrial software engineering research. In 2009 3rd International Symposium on Empirical Software Engineering and Measurement. IEEE, 401–404.
[18]
Shaun Phillips, Guenther Ruhe, and Jonathan Sillito. 2012. Information needs for integration decisions in the release process of large-scale parallel development. In Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work. 1371–1380.
[19]
Pilar Rodríguez, Emilia Mendes, and Burak Turhan. 2018. Key stakeholders’ value propositions for feature selection in software-intensive products: An industrial case study. IEEE Transactions on Software Engineering 46, 12 (2018), 1340–1363.
[20]
Per Runeson and Martin Höst. 2009. Guidelines for conducting and reporting case study research in software engineering. Empirical software engineering 14, 2 (2009), 131–164.
[21]
Mali Senapathi, Jim Buchan, and Hady Osman. 2018. DevOps capabilities, practices, and challenges: Insights from a case study. In Proceedings of the 22nd International Conference on Evaluation and Assessment in Software Engineering 2018. 57–67.
[22]
Mojtaba Shahin and M Ali Babar. 2020. On the role of software architecture in DevOps Transformation: An industrial case study. In Proceedings of the International Conference on Software and System Processes. 175–184.
[23]
Miroslaw Staron and Wilhelm Meding. 2018. Software Development Measurement Programs. Springer. https://doi. org/10.1007/978-3-319-91836-5 10 (2018), 3281333.
[24]
Christoph Treude, Fernando Figueira Filho, and Uirá Kulesza. 2015. Summarizing and measuring development activity. In Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering. 625–636.
[25]
Cathy Urquhart. 2012. Grounded theory for qualitative research: A practical guide. Sage.
[26]
Cathy Urquhart and Walter Fernández. 2016. Using grounded theory method in information systems: The researcher as blank slate and other myths. In Enacting research methods in information systems: Volume 1. Springer, 129–156.
[27]
Claes Wohlin and Aybüke Aurum. 2015. Towards a decision-making structure for selecting a research design in empirical software engineering. Empirical Software Engineering 20, 6 (2015), 1427–1455.
[28]
Dongmei Zhang, Shi Han, Yingnong Dang, Jian-Guang Lou, Haidong Zhang, and Tao Xie. 2013. Software analytics in practice. IEEE software 30, 5 (2013), 30–37.

Cited By

View all
  • (2023)On Adopting Software Analytics for Managerial Decision-Making: A Practitioner’s PerspectiveIEEE Access10.1109/ACCESS.2023.329482311(73145-73163)Online publication date: 2023

Index Terms

  1. Use Cases for Software Development Analytics: A Case Study

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    SBES '22: Proceedings of the XXXVI Brazilian Symposium on Software Engineering
    October 2022
    457 pages
    ISBN:9781450397353
    DOI:10.1145/3555228
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 05 October 2022

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. indicators
    2. information needs
    3. software analytics
    4. use cases

    Qualifiers

    • Research-article
    • Research
    • Refereed limited

    Conference

    SBES 2022
    SBES 2022: XXXVI Brazilian Symposium on Software Engineering
    October 5 - 7, 2022
    Virtual Event, Brazil

    Acceptance Rates

    Overall Acceptance Rate 147 of 427 submissions, 34%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)28
    • Downloads (Last 6 weeks)1
    Reflects downloads up to 15 Feb 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2023)On Adopting Software Analytics for Managerial Decision-Making: A Practitioner’s PerspectiveIEEE Access10.1109/ACCESS.2023.329482311(73145-73163)Online publication date: 2023

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    HTML Format

    View this article in HTML Format.

    HTML Format

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media