## 1 Introduction  
Due to software systems' increased complexity and size, software failures are inevitable in software development projects. A large part of a software development project is therefore often dedicated to software verification and validation. Detecting the faults, diagnosing the cause of these faults, and resolving these faults is crucial to ensure the functional and quality requirements for software projects. Fault detections are typically described in bug reports, including textual descriptions of the problem and the steps that led to a failure [1]. The validity and performance of the verification tasks depend heavily on the quality of bug reports. Hence the accuracy and completeness of these bug reports are essential. Bug reports are generally handled and tracked with the help of bug tracking software to manage maintenance activities and keep the bugs' details [2]. After detecting the bugs, the classification of software bugs is needed to understand the root causes and provide the proper steps for correcting the bugs. The primary benefit of bug classification is to reduce the bug fixing time by reducing the bug assignment time to the corresponding developer who can fix the bug in the least amount of time [3]. However, one must soon deal with a broad set of bugs from multiple types for large-scale projects. Manually classifying bugs then becomes quickly cumbersome, error-prone, and time-consuming. For example, [PERSON] et al. [4] pointed out that, in their work,researchers spent 90 days manually classifying more than 7000 bug reports. Similarly, [PERSON] et al. [5] reported that, in big software projects, assigning a bug to the first developer who will fix the bug might take up to 180 days, and to the second developer might take an additional 250 days if the first developer cannot fix the bug. Moreover, bug reports are not always well-structured and are very often unstructured. Structured reports adopt a well-defined template for bug classification, whereas unstructured reports use free text, which can dramatically impede bug classification. Several studies have focused on adopting the automation of bug classification activities to overcome the bug classification problem, often using machine learning approaches. However, these studies have focused mainly on academic case studies, open-source software, and unilingual text input. This paper presents the results and lessons learned of our developed bug classification approach and the corresponding tools, applied and validated in an industrial case study research. Furthermore, in contrast to existing studies, our study is applied to a commercial software system. Finally, bug classification is based on unstructured bilingual bug reports written in English and Turkish, derived from black-box testing results. The presented approach adopts and integrates machine learning (ML), text mining, and natural language processing (NLP) techniques to support the classification of software bugs. Our study shows that the presented approach and the corresponding tools effectively reduce the manual classification time and effort. Furthermore, we have used commercial bug reports in this paper. However, [PERSON] et al. [6] stated that almost all studies in the literature use bug repositories of open source systems. Therefore, in this paper, we attempt to extend bug classification issues into commercial bug reports. The contributions of this study are the following. First of all, we provide bug classification for a real industrial project. Since earlier studies mainly focused on open source projects, this study can provide additional insight into the topic. Secondly, the approach focuses on the usage of bilingual unstructured bug reports. Bug classification has been broadly addressed in the literature, but bilingual unstructured bug report classification still requires more in-depth research. Therefore, the current study adds to the existing knowledge. Finally, we provide an empirical case study research-based approach for evaluating automated bug classification.