  This work aims to investigate the reliability of software products as an
important attribute of computer programs; it helps to decide the degree of
trustworthiness a program has in accomplishing its specific functions. This is
done using the Software Reliability Growth Models (SRGMs) through the
estimation of their parameters. The parameters are estimated in this work based
on the available failure data and with the search techniques of Swarm
Intelligence, namely, the Cuckoo Search (CS) due to its efficiency,
effectiveness and robustness. A number of SRGMs is studied, and the results are
compared to Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO)
and extended ACO. Results show that CS outperformed both PSO and ACO in finding
better parameters tested using identical datasets. It was sometimes
outperformed by the extended ACO. Also in this work, the percentages of
training data to testing data are investigated to show their impact on the
results.
