research-article

Monitoring code quality and development activity by software maps

Authors:

Johannes Bohnet,

Jürgen DöllnerAuthors Info & Claims

MTD '11: Proceedings of the 2nd Workshop on Managing Technical Debt

Pages 9 - 16

https://doi.org/10.1145/1985362.1985365

Published: 23 May 2011 Publication History

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Abstract

Software development projects are difficult to manage, in general, due to the friction between completing system features and, at the same time, obtaining a high degree of code quality to ensure maintainability of the system in the future. A major challenge of this optimization problem is that code quality is less visible to stakeholders in the development process, particularly, to the management. In this paper, we describe an approach for automated software analysis and monitoring of both quality-related code metrics and development activities by means of software maps. A software map represents an adaptive, hierarchical representation of software implementation artifacts such as source code files being organized in a modular hierarchy. The maps can express and combine information about software development, software quality, and system dynamics; they can systematically be specified, automatically generated, and organized by templates. The maps aim at supporting decision-making processes. For example, they facilitate to decide where in the code an increase of quality would be beneficial both for speeding up current development activities and for reducing risks of future maintenance problems. Due to their high degree of expressiveness and their instantaneous generation, the maps additionally serve as up-to-date information tools, bridging an essential information gap between management and development, improve awareness, and serve as early risk detection instrument. The software map concept and its tool implementation are evaluated by means of two case studies on large industrially developed software systems.

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Cited By

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Fungprasertkul SBahsoon RKazman R(2024)Technical Debt Monitoring Decision Making with Skin in the GameACM Transactions on Software Engineering and Methodology10.1145/366480533:7(1-27)Online publication date: 26-Aug-2024
https://dl.acm.org/doi/10.1145/3664805
Szabados KFarkas IKovács A(2022)Reproducibility in the technical debt domainActa Universitatis Sapientiae, Informatica10.2478/ausi-2021-001613:2(335-360)Online publication date: 2-Feb-2022
https://doi.org/10.2478/ausi-2021-0016
Villa AOcharán-Hernández JPérez-Arriaga JLimón X(2022)A Systematic Mapping Study on Technical Debt in Microservices2022 10th International Conference in Software Engineering Research and Innovation (CONISOFT)10.1109/CONISOFT55708.2022.00032(182-191)Online publication date: Oct-2022
https://doi.org/10.1109/CONISOFT55708.2022.00032
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Index Terms

Monitoring code quality and development activity by software maps
1. Social and professional topics
  1. Professional topics
    1. Management of computing and information systems
      1. Project and people management
2. Software and its engineering
  1. Software creation and management
    1. Software development techniques
      1. Reusability
        Software product lines
    2. Software verification and validation
      1. Empirical software validation
      2. Process validation
  2. Software organization and properties
    1. Software functional properties
      1. Formal methods

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Information & Contributors

Information

Published In

MTD '11: Proceedings of the 2nd Workshop on Managing Technical Debt

May 2011

54 pages

ISBN:9781450305860

DOI:10.1145/1985362

Program Chairs:
Ipek Ozkaya
Software Engineering Institute, USA
,
Philippe Kruchten
University of British Columbia, Canada
,
Rod Nord
Software Engineering Institute, USA
,
Nanette Brown
Software Engineering Institute, USA

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]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 May 2011

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Conference

ICSE11

Sponsor:

SIGSOFT

ICSE11: International Conference on Software Engineering

May 23, 2011

HI, Waikiki, Honolulu, USA

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Overall Acceptance Rate 40 of 92 submissions, 43%

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Cited By

View all

Fungprasertkul SBahsoon RKazman R(2024)Technical Debt Monitoring Decision Making with Skin in the GameACM Transactions on Software Engineering and Methodology10.1145/366480533:7(1-27)Online publication date: 26-Aug-2024
https://dl.acm.org/doi/10.1145/3664805
Szabados KFarkas IKovács A(2022)Reproducibility in the technical debt domainActa Universitatis Sapientiae, Informatica10.2478/ausi-2021-001613:2(335-360)Online publication date: 2-Feb-2022
https://doi.org/10.2478/ausi-2021-0016
Villa AOcharán-Hernández JPérez-Arriaga JLimón X(2022)A Systematic Mapping Study on Technical Debt in Microservices2022 10th International Conference in Software Engineering Research and Innovation (CONISOFT)10.1109/CONISOFT55708.2022.00032(182-191)Online publication date: Oct-2022
https://doi.org/10.1109/CONISOFT55708.2022.00032
Marques Silva JPereira J(2021)NOESIS: Surfing the technological wave from PortugalJournal of Information Technology Teaching Cases10.1177/2043886921102236812:2(170-182)Online publication date: 3-Sep-2021
https://doi.org/10.1177/20438869211022368
Codabux ZVidoni MFard F(2021)Technical Debt in the Peer-Review Documentation of R Packages: a rOpenSci Case Study2021 IEEE/ACM 18th International Conference on Mining Software Repositories (MSR)10.1109/MSR52588.2021.00032(195-206)Online publication date: May-2021
https://doi.org/10.1109/MSR52588.2021.00032
Gomes RPinheiro LMaciel RCavalcante EDantas FBatista T(2020)Anticipating Identification of Technical Debt Items in Model-Driven Software ProjectsProceedings of the XXXIV Brazilian Symposium on Software Engineering10.1145/3422392.3422434(740-749)Online publication date: 21-Oct-2020
https://dl.acm.org/doi/10.1145/3422392.3422434
Weninger MMakor LMossenbock H(2020)Memory Cities: Visualizing Heap Memory Evolution Using the Software City Metaphor2020 Working Conference on Software Visualization (VISSOFT)10.1109/VISSOFT51673.2020.00017(110-121)Online publication date: Sep-2020
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Farias MNeto MKalinowski MSpínola R(2020)Identifying self-admitted technical debt through code comment analysis with a contextualized vocabularyInformation and Software Technology10.1016/j.infsof.2020.106270121:COnline publication date: 1-May-2020
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Scheibel WHartmann JLimberger DDöllner J(2020)Visualization of Tree-Structured Data Using Web Service CompositionComputer Vision, Imaging and Computer Graphics Theory and Applications10.1007/978-3-030-41590-7_10(227-252)Online publication date: 20-Feb-2020
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Mendes TGomes FGonçalves DMendonça MNovais RSpínola R(2019)VisminerTD: a tool for automatic identification and interactive monitoring of the evolution of technical debt itemsJournal of the Brazilian Computer Society10.1186/s13173-018-0083-125:1Online publication date: 16-Jan-2019
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