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Graphical versus textual software measurement modelling: an empirical study

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Abstract

Model-driven Engineering (MDE) has attained great importance in both the Software Engineering industry and the research community, where it is now widely used to provide a suitable approach with which to improve productivity when developing software artefacts. In this scenario, measurement models (software artefacts) have become a fundamental point in improvement of productivity, where MDE and Software Measurement can reap mutual benefits. MDE principles and techniques can be used in software measurement to build more automatic and generic solutions, and to achieve this, it is fundamental to be able to develop software measurement models. To facilitate this task, a domain-specific language named “Software Measurement Modelling Language” (SMML) has been developed. This paper tackles the question of whether the use of SMML can assist in the definition of software measurement models. An empirical study was conducted, with the aim of verifying whether SMML makes it easier to construct measurement models which are more usable and maintainable as regards textual notation. The results show that models which do not use the language are more difficult—in terms of effort, correctness and efficiency—to understand and modify than those represented with SMML. Additional feedback was also obtained, to verify the suitability of the graphical representation of each symbol (element or relationship) of SMML.

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Notes

  1. In http://alarcos.inf-cr.uclm.es/ontologies/smo/—The Web Ontology Language (OWL) is a family of knowledge representation languages for authoring ontologies endorsed by the World Wide Web Consortium.

  2. In http://alarcos.esi.uclm.es/smf/.

  3. In http://alarcos.esi.uclm.es/smf/smtool/.

  4. LabVIEW (short for Laboratory Virtual Instrumentation Engineering Workbench) is a platform and development environment for a visual programming language from National Instruments.

  5. Simulink is an environment for multidomain simulation and Model-Based Design for dynamic and embedded systems. It provides an interactive graphical environment and a customizable set of block libraries that let you design, simulate, implement, and test a variety of time-varying systems, including communications, controls, signal processing, video processing, and image processing.

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Acknowledgments

This work has been partially supported by the projects: INGENIO (JCCM, PAC08-0154-9262), MEDUSAS (CDTI (MICINN), IDI-20090557), PEGASO/MAGO (MICINN and FEDER, TIN2009-13718-C02-01), and ALTAMIRA (JCCM, Fondo Social Europeo, PII2I09-0106-2463) projects.

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Authors and Affiliations

  1. Indra Software Labs, Information Technology Company, Ciudad Real, Spain

    B. Mora

  2. ALARCOS Research Group, Department of Information Technologies and Systems, University of Castilla-La Mancha, Paseo de la Universidad, 4, 13071, Ciudad Real, Spain

    F. García, F. Ruiz & M. Piattini

Authors
  1. B. Mora
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  2. F. García
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  3. F. Ruiz
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  4. M. Piattini
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Corresponding author

Correspondence to B. Mora.

Appendices

Appendix A: Example of definition of software measurement models

See Figs. 11, 12, 13.

Fig. 11
figure 11

Example of understandability exercise with SMML diagram

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Fig. 12
figure 12

Example of modifiability exercise with a TEXTUAL notation

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Fig. 13
figure 13

Example of modifiability exercise with a TEXTUAL notation (cont.)

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Appendix B: Boxplots

See Figs. 14, 15, 16, 17, 18.

Fig. 14
figure 14

Boxplot diagram of the interaction of UoD × usage of SMML in the experiment for modifiability/understandability valuation

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Fig. 15
figure 15

Boxplot diagram for the usage of SMML in the experiment for the efficiency

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Fig. 16
figure 16

Boxplot diagram for the use of SMML in the experiment for the time

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Fig. 17
figure 17

Boxplot diagram for the use of SMML in the experiment for the correctness

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Fig. 18
figure 18

Boxplot diagram for the usage of SMML in the experiment for the valuation

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Mora, B., García, F., Ruiz, F. et al. Graphical versus textual software measurement modelling: an empirical study. Software Qual J 19, 201–233 (2011). https://doi.org/10.1007/s11219-010-9111-x

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