Replication Package – Machine Learning for Software Aging Detection: A Systematic Mapping Study

Systematic Mapping Study – Data Extraction Form This form outlines the variables for extracting data from studies included in a systematic mapping study SMS. Each variable is designed to capture specific information relevant to understanding the methodology, findings, and context of the reviewed papers. ● V1 BibTexId: Unique bibliographic identifier for the study. ● V2 Paper Title: The full title of the publication. ● V3 Database: The digital library or indexing database where the study was retrieved. ● V4 Publication Year: The year in which the study was published. ● V5 Publication Type: The type of publication, such as journal article, conference paper, among others. ● V6 Conference or Journal: The name of the journal or conference proceedings in which the study appeared. ● V7 Main Objective: The primary goal or research question addressed by the study. ● V8 Domain/Application Area: The specific domain or application field in which the study was conducted (e.g., Cloud-based applications, Virtual machine applications). ● V9 Execution Environment: The target environment analyzed in the study. ● V10 Software Systems: Systems or applications analyzed in the study. ● V11 Approach/Technique: The methodological or algorithmic approach employed (e.g., supervised learning, unsupervised methods). ● V12 Preprocessing Technique: Data preprocessing strategies applied (e.g., normalization, feature selection, outlier removal). ● V13 ML Algorithm: The machine learning algorithm(s) implemented (e.g., Random Forest RF, Neural Networks). ● V14 Evaluation Metrics: Metrics used to assess model performance (e.g., accuracy, precision, recall, F1-score, ROCAUC. ● V15 ML Problem: Type of machine learning problem tackled (e.g., classification, regression, anomaly detection). ● V16 Aging Indicators Adopted: System degradation or aging indicators monitored (e.g., CPU usage, memory consumption). ● V17 Dataset Name: The name or designation of the dataset used in the study. ● V18 Dataset Type: Nature and characteristics of the dataset used in the study. ● V19 Dataset Source: Origin or repository where the dataset was obtained. ● V20 Challenges/Limitations: Key limitations, constraints, or open challenges identified in the study. ● V21 Future Work/Recommendations: Suggestions made by the authors for future research directions or improvements. ● V22 Notes: Additional relevant notes or observations not covered by other variables.