M2SmallLint : software health monitoring tool

  • Hayatou Oumarou University of Maroua
  • Nurul Rismayanti Universitas Muslim Indonesia, Makassar

Keywords: Software data visualization,, Software quality, Software metrics, Software tools


Developing error-free applications is a major challenge for computer scientists. Tools to remedy this problem have been developed, notably Rule Checkers and proof assistants. As a particular case of error, a bug is by nature intangible, invisible and difficult to trace. We propose to investigate the correlations between the alerts generated by rule checkers and the internal quality of the software system. In this first version of the work, we present M2SmallLint, a tool for visualizing and navigating through source code properties in order to locate potential errors. This tool enables the visualization of software health.


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J. Sliwerski, T. Zimmermann Et A. Zeller, HATARI: raising risk awareness., ESEC/SIGSOFT FSE, pp. 107-110., 2005.

A. Hora, N. Anquetil Et S. Ducasse, Bug maps: A tool for the visual exploration and analysis of bugs., In : 2012 16th European Conference on Software Maintenance and Reengineering. IEEE., pp. 523-526, 2012.

C. Couto, P. Pires, M. T. Valente Et H. N. A. Andre, Bugmaps-granger: A tool for causality analysis between source code metrics and bugs., Brazilian Conference on Software: Theory and Practice (CBSoft'13)., 2013.

F. Bolte Et S. Bruckner, Vis-a-vis: visual exploration of visualization source code evolution., IEEE Transactions on Visualization and Computer Graphics, pp. 3153-3167., 2020.

Reddivari, Sandeep Et Khan, Mohammed Salman. VisioTM: A Tool for Visualizing Source Code Based on Topic Modeling., 43rd Annual Computer Software and Applications Conference (COMPSAC) IEEE. , pp. 932-933., 2019.

J. Maletic, D. Mosora Et C. Newman, MosaiCode: visualizing large scale software: A tool demonstration., 6th International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT). IEEE, pp. 1-4, 2011.

H. Kienle Et H. Müller, The Rigi reverse engineering environment., 1nd International Workshop on Advanced Software Development Tools and Techniques (WASDeTT 1)., 2008.

PharoConsortium, Welcome to Pharo, 2022. [En ligne]. Available: https://pharo.org/. [Accès le 13 juin 2022].

Synectique, Moose, 2022. [En ligne]. Available: https://moosetechnology.org/. [Accès le 04 juillet 2022].

S. Ducasse, N. Anquetil Et M. U. Bhatti, Mse And Famix 3.0: an interexchange format and source code model family,» 2011.

S. R. C. a. C. F. Kemerer, A Metrics Suite for Object, IEEE Transaction on Software Engineering, 2020.

C. a. N. Harrison, Evaluation of the MOOD Set of Object-Oriented Software Metrics, IEEE Transaction on Software, 2020.

P. Mengal, Métriques Et Critères D’évaluation De La Qualité Du Code Source D’un Logiciel, Revue d’un professionnel de l’industrie du logicie, Paris, 2019.

T. Durieux, F. Madeiral, M. Martinez et R. Abreu, Empirical review of Java program repair tools: A large-scale experiment on 2,141 bugs and 23,551 repair attempts., 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, pp. 302-313, 2019.

P. Hegedűs et R. Ferenc, Static code analysis alarms filtering reloaded: A new real-world dataset and its ML-based utilization., IEEE Access, 10, , pp. 55090-55101. , 2022.

S. Heckman Et L. Williams, On establishing a benchmark for evaluating static analysis alert prioritization and classification techniques., Second ACM-IEEE international symposium on Empirical software engineering and measurement ., pp. 41-50, 2008.

T. Kremenek Et D. Engler, Z-ranking: Using statistical analysis to counter the impact of static analysis approximations.,» chez International Symposium, SAS. , San Diego, CA, USA, 2003.

How to Cite
Hayatou Oumarou, & Nurul Rismayanti. (2023). M2SmallLint : software health monitoring tool. Indonesian Journal of Data and Science, 4(2), 130-135. https://doi.org/10.56705/ijodas.v4i2.90