Determining the Tested Classes with Software Metrics

Year 2017, Volume: 13 Issue: 4, 863 - 871, 29.12.2017

Fatih Yücalar , Emin Borandağ

https://doi.org/10.18466/cbayarfbe.330995

Abstract

Early detection and
correction of errors appearing in software projects reduces the risk of
exceeding the estimated time and cost. An efficient and effective test plan
should be implemented to detect potential errors as early as possible. In the
earlier phases, codes can be analyzed by efficiently employing software metric
and insight can be gained about error susceptibility and measures can be taken
if necessary. It is possible to classify software metric according to the time
of collecting data, information used in the measurement, type and interval of
the data generated. Considering software metric depending on the type and
interval of the data generated, object-oriented software metric is widely used
in the literature. There are three main metric sets used for software projects
that are developed as object-oriented. These are Chidamber & Kemerer, MOOD
and QMOOD metric sets. In this study, an approach for identifying the classes
that should primarily be tested has been developed by using the object-oriented
software metric. Then, this approach is applied for selected versions of the
project developed. According to the results obtained, the correct determination
rate of sum of the metrics method, which was developed to identify the classes
that should primarily be tested, is ranged between 55% and 68%. In the random
selection method, which was used to make comparisons, the correct determination
rate for identifying the classes that should primarily be tested is ranged
between 9.23% and 11.05%. In the results obtained using sum of the metrics
method, a significant rate of improvement is observed compared to the random
selection method.

Keywords

Software Fault Prediction, Software Quality and Assuarance, Software Metrics, Software Testing

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