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

Get Access

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.

References

[1]

Beck, K.: Extreme Programming Explained: Embrace Change, Addison-Wesley Professional, 1999.

Digital Library

Google Scholar

[2]

Correia, J., Kanellopoulos, Y., and Visser, J.: A survey-based study of the mapping of system properties to ISO/IEC 9126 maintainability characteristics, IEEE Int'l Conf. on Software Maintenance, 2009, 61--70.

Google Scholar

[3]

Eick, S., Steffen, J., and Sumner, Jr.: Seesoft - A Tool for Visualizing Line Oriented Software Statistics, IEEE Trans. on Software Engineering, 1992, 18, 957--968.

Digital Library

Google Scholar

[4]

Froehlich, J. and Dourish, P.: Unifying Artifacts and Activities in a Visual Tool for Distributed Software Development Teams, Proc. of the Int'l Conf. on Software Engineering, 2004, 387--396.

Digital Library

Google Scholar

[5]

Gaudin, O.: Evaluate your technical debt with Sonar, http://www.sonarsource.org/evaluate-your-technical-debtwith-sonar.

Google Scholar

[6]

Healey, C., Booth, K., and Enns, J.: High-speed visual estimation using preattentive processing, ACM Trans. Comput.-Hum. Interact., 1996, 3, 107--135.

Digital Library

Google Scholar

[7]

Lehman, M. and Belady, L.: Program evolution: processes of software change, 1985, Academic Press Professional, Inc.

Digital Library

Google Scholar

[8]

Parnas, David: Software aging. In: International Conference on Software Engineering, 1994, pp. 279--287.

Digital Library

Google Scholar

[9]

Shneiderman, Ben: Tree visualization with tree-maps: 2-d space-filling approach. In: ACM Transactions on Graphics 11 (1992), No. 1, pp. 92--99.

Digital Library

Google Scholar

[10]

Ware, Colin: Information Visualization: Perception for Design. Morgan Kaufmann Publishers, 2004.

Digital Library

Google Scholar

[11]

Wettel, R. and Lanza, M.: Visualizing software systems as cities, Proc. of the IEEE Int'l Workshop on Visualizing Software For Understanding and Analysis, 2007, 92--99.

Crossref

Google Scholar

[12]

Wettel, R. and Lanza, M.: Visual Exploration of Large-Scale System Evolution, Proc. of the IEEE Working Conf. on Reverse Engineering, 2008, 219--228.

Digital Library

Google Scholar

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
Show More Cited By

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

Recommendations

Software quality and assurance in waterfall model and XP: a comparative study

Dealing with an increasingly volatile organizational environment is a serious challenge for managers of any software development. Traditional formal software development methodologies can be characterized as reflecting linear, sequential processes, and ...
Software Development Worldwide: The State of the Practice

The worldwide boom in IT use has spurred software development efforts around the globe. The authors' research program focuses on collecting quantitative data about several countries' current practices and performance, their adoption of competing models ...
DevOps and software quality: A systematic mapping
Abstract
Quality pressure is one of the factors affecting processes for software development in its various stages. DevOps is one of the proposed solutions to such pressure. The primary focus of DevOps is to increase the deployment speed, ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

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]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 May 2011

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

ICSE11

Sponsor:

SIGSOFT

ICSE11: International Conference on Software Engineering

May 23, 2011

HI, Waikiki, Honolulu, USA

Acceptance Rates

Overall Acceptance Rate 40 of 92 submissions, 43%

Upcoming Conference

ICSE 2025

2025 IEEE/ACM 46th International Conference on Software Engineering

April 26 - May 3, 2025

Ottawa , ON , Canada

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

42
Total Citations
View Citations
952
Total Downloads

Downloads (Last 12 months)26
Downloads (Last 6 weeks)7

Reflects downloads up to 10 Nov 2024

Other Metrics

View Author Metrics

Citations

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
https://doi.org/10.1109/VISSOFT51673.2020.00017
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
https://dl.acm.org/doi/10.1016/j.infsof.2020.106270
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
https://doi.org/10.1007/978-3-030-41590-7_10
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
https://doi.org/10.1186/s13173-018-0083-1
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Software quality and assurance in waterfall model and XP: a comparative study

Software Development Worldwide: The State of the Practice

DevOps and software quality: A systematic mapping