Fault prediction of multimedia software is necessary to develop good quality multimedia software because integrating various multimedia heterogeneous components in a software system usually generates many faults. So, this research article proposes a new fault prediction model based on the decided threshold values of structural features. These features are captured using metrics specifically identified for multimedia software and weighted suitably based on the behavior of the components dealing with multimedia handling. The threshold values are optimized using the genetic algorithm (GA). This paper also proposes a GA-based technique to combine multiple features using conjunction (AND) and disjunction (OR) operators while finding threshold values. Finally, the proposed model is tested for cross-project software fault prediction on selected six multimedia software and validated on three other general software datasets. Results show that our identified thresholds-based model performs excellently for multimedia software and satisfactorily over other general software. 

Code metrics, fault prediction, genetic algorithm, threshold values