Methodological Approach to Software Quality Assurance through High-Level Object-Oriented Metrics

  • José Romero
  • Oscar Pastor
  • Jorge Belenguer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2425)


Traditionally, quality software development has been based on the study of lines of implemented code. Software is usually evaluated by means of metrics coming from programming languages.

On the one hand, regarding the great importance of the early stages of development, metrics must be defined from higher level of abstraction. Consequently, high-level metrics to be defined and validated in this work, come from specification languages.

On the other hand, the concept of quality has subjective aspects leading to numerous proposals for its assurance. Typically, they can be classified in process-centric and product-centric methods. This classification establishes a gap among existing methods. This paper is an attempt to bridge this gap by means of unifying part of the most relevant work about the quality issue, under one umbrella framework. This framework is a methodological approach to software quality assurance based on an object-oriented conceptual modeling method including automatic code generation. It also combines a formal specification language with standard notation.

Due to the particular concepts included in our method, the core of this work is to define and validate a specific set of high-level metrics. They assess the quality of an Information System from the Conceptual Model designed with this method.

The originality of the paper is the way that high-level metrics are obtained. Using practical experiences modeling real systems, the Quality Hypotheses are established. Metrics involved in them are chosen as candidates to be incorporated in the set which is being defined. The final step is to describe the strategy for their formal and empirical validation.

Summing up our methodological approach, software quality assurance consists of: modeling a problem, evaluating the set of metrics, and automatically generating the code of the final software application for a target environment.

In future works, the generalization of these ideas to other object-oriented methods will be studied.


Software Quality Software Project Empirical Validation Validation Error Quality Framework 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • José Romero
    • 1
  • Oscar Pastor
    • 1
  • Jorge Belenguer
    • 1
  1. 1.DSICValencia University of TechnologyValenciaSpain

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