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Open research questions in Software System Performance and Reliability

203 gap statements mined from Software System Performance and Reliability papers in our 7.9M-paper local library, which holds 980 papers on the topic — drawn mostly from each paper's own stated research gap, future-work, challenge and limitation notes, and its abstract. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one.

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What the literature leaves open

  • Anyway, as finally stated in the response in Q4, some aspects should be further explored along the dimension of AI-based HA systems as, for example, the probabilistic nature of the decision-making process and the security concerns. There are also open issues of data sparsity, explainability and accountability, as well as security concerns.

    Artificial Intelligence for High-Availability Systems: A Comprehensive Review · 2026 · DOI

  • First, the information extraction (IE) module still depends on supervised annotations for entities and relations; for some rare but safety-critical types, labeled examples are scarce even after applying imbalance-aware training.

    Graph-Augmented Fault Diagnosis in Power Systems with Imbalanced Text Data: A Knowledge Extraction and Agent-Based Reasoning Framework · 2026 · DOI

  • Tool implementation alone is insufficient; discovery metadata must also be correct. Multiple Claude Code sessions against the same server started “looking at a different repository”, indicating that session data was mixed across workspaces.

    Real Faults in Model Context Protocol (MCP) Software: a Comprehensive Taxonomy · 2026 · DOI

  • Future research could explore ways to optimize these components further or experiment with their integration with other techniques to address more complex or data-scarce situations. For example, when the pseudo-labeling mechanism was removed, the model showed a decline in performance, especially in cases where labeled data was limited.

    ELFA-Log: Cross-System Log Anomaly Detection via Enhanced Pseudo-Labeling and Feature Alignment · 2025 · DOI

  • Feature engineering processes must be refined and updated continuously to adapt to the evolving landscape of web technologies and ensure that the most relevant predictors are included.

    A Novel Approach for Evaluating Web Page Performance Based on Machine Learning Algorithms and Optimization Algorithms · 2025 · DOI

  • By integrating temporal logicalmodeling with adaptive detection mechanisms, TLAN effectively addresses the challenges of capturing complex temporal dependencies and component interactions in distributed systems.

    Temporal Logical Attention Network for Log-Based Anomaly Detection in Distributed Systems · 2024 · DOI

  • Cross-system, cross-workload, unseen-fault, and concurrent multi-fault generalization remain to be evaluated. Finally, traceability is demonstrated through explicit intermediate reasoning artifacts, but operator benefit has not been quantified.

    A Knowledge-Enhanced Iterative Reasoning Framework for Accurate and Traceable Fault Diagnosis in Distributed Service Systems · 2026 · DOI

  • This limitation is particularly evident in industrial applications, where the lack of standardized benchmarks complicates the evaluation of identification strategy efficacy.

    The Ontology-Based Mapping of Microservice Identification Approaches: A Systematic Study of Migration Strategies from Monolithic to Microservice Architectures · 2025 · DOI

  • Field-validated incident labels are scarce in practice, and legitimate shifts in the workload mix can also raise anomaly indicators.

    Toward a Context-Aware AIOps Framework for High-Energy Physics Computing Clusters: A Design Proposal with Isolation Forest Scoring and Operator-Controlled Response · 2026 · DOI

  • The need for efficient mechanisms of message exchange between system components in modern distributed information systems. The lack of understanding of the pros and cons of RabbitMQ and Apache Kafka in terms of performance.

    Application of Message Brokers (RabbitMQ, Kafka): Performance Analysis and Use Cases · 2026 · DOI

  • Although challenges such as data consistency, service discovery, and security remain inherent to distributed systems, modern tools and practices such as API gateways, JWT-based authentication, and centralized monitoring offer effective solutions. Overall, adopting a Python-based microservice architecture provides a strong foundation for building resilient, flexible, and future-ready applications.

    Enhancing System Modularity through Python-Based Micro services Development · 2026 · DOI

  • Future research should focus on deploying the ARCH framework in real cloud environments to evaluate its performance, scalability, and robustness under practical conditions. Future work will focus on improving real-time performance, reducing computational overhead, and enhancing security mechanisms to ensure safe and reliable deployment in production environments.

    Agentic Generative AI Framework for Predictive Fault Detection in Self-Healing Cloud Environments · 2026 · DOI

  • The gap is the lack of a flexible and efficient system for log and data analytics. The gap is the need for a system that can handle large amounts of data quickly and efficiently.

    Dashboard Application for Log and Data Analytics · 2026 · DOI

  • One challenge is the need for deterministic failover, workload-aware replication, and controlled change management. Another challenge is the requirement for synchronous replication and continuous validation of availability guarantees for regulated workloads. The paper also highlights the challenge of considering the broader obligation of data platforms to public trust and institutional accountability.

    Designing Zero-Downtime, High-Availability Data Platforms for Real-Time and Regulated Systems · 2026 · DOI

  • The gap in current high-availability designs is the inability to provide zero-downtime operation for real-time and regulated systems. The gap is due to the residual tolerance for brief interruptions during planned maintenance, upgrades, and failover transitions. The paper identifies the need for a framework that can provide a foundation for designing and operating zero-downtime data platforms.

    Designing Zero-Downtime, High-Availability Data Platforms for Real-Time and Regulated Systems · 2026 · DOI

  • It identifies the need for a Zero-Data-Loss strategy to ensure financial integrity and regulatory compliance.

    Zero-Data-Loss Disaster Recovery for Hybrid Financial ERP Landscapes: An AI-Driven Approach · 2026 · DOI

  • The lack of technical expertise among non-technical users to diagnose connectivity issues. The complexity of home networks due to the rapid increase in internet-connected devices.

    Smart Network Analyzer: A Real-Time Home Network Monitoring Platform · 2026 · DOI

  • Future work should explore adaptive profiling and optimization strategies that target different metrics depending on application characteristics—for instance, prioritizing memory events for memory-bound programs, lock events for synchronization-heavy workloads, and CPU cycles for compute-bound kernels.

    SysLLMatic: Large language models are software system optimizers · 2026 · DOI

  • The combined effect of live migration and rejuvenation strategies in microservice-based distributed edge storage is still unclear.

    Distributed Edge Storage Systems: Proactive High-Availability Microservices with Live Migration and Rejuvenation Strategies · 2026 · DOI

  • Existing deployment systems lack automation and do not provide real-time integration and continuous delivery mechanisms. Many traditional systems still lack fully automated pipelines integrated with cloud deployment and real-time monitoring dashboards.

    Simple CI/CD Pipeline for Web Application Using Azure · 2026 · DOI

  • Future research directions include integrating PROTEA with existing toolchains and frameworks. Future research directions include improving the scalability and efficiency of PROTEA for very large workflows.

    PROTEA: Offline Evaluation and Iterative Refinement for Multi-Agent LLM Workflows · 2026

  • The preferred structure gives a safe and strong cloud-based design to address the utmost problems in present e-governance platforms.

    Towards A Secure and Scalable Cloud Architecture for High Performance Government E-Service Delivery · 2026 · DOI

  • Prior work does not address the problem of straggler detection and node health management in large-scale training clusters.

    Guard: Scalable Straggler Detection and Node Health Management for Large-Scale Training · 2026

  • This study presented VIRTUOSO, a multilayer security framework that combines deep automation with ML-based detection to provide evidence-driven security…

    VIRTUOSO: A Multilayer Cloud Security and Risk Management Framework · 2026 · DOI

  • Traditional static defense mechanisms and reactive stabilization strategies lag in prediction and fail to prevent cascading failures. Contemporary system stabilization employs layered defenses, but treats them as independent components, creating critical gaps.

    Cascading Resilience Through Predictive Multi-Dimensional Safeguards: System Stability Architecture for Billion-Scale Concurrent Platforms · 2026 · DOI

Most-cited papers in Software System Performance and Reliability

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Open questions raised by papers listed on this page include: (1) The information extraction (IE) module still depends on supervised annotations for entities and relations; for some rare but safety-critical types, labeled examples are scarce even after applying imbalance-aware training (“Graph-Augmented Fault Diagnosis in Power Systems with Imbalanced Text Data: A…”, 2026); (2) Cross-system, cross-workload, unseen-fault, and concurrent multi-fault generalization remain to be evaluated (“A Knowledge-Enhanced Iterative Reasoning Framework for Accurate and Traceable…”, 2026); (3) Field-validated incident labels are scarce in practice, and legitimate shifts in the workload mix can also raise anomaly indicators (“Toward a Context-Aware AIOps Framework for High-Energy Physics Computing…”, 2026); (4) The lack of understanding of the pros and cons of RabbitMQ and Apache Kafka in terms of performance (“Application of Message Brokers (RabbitMQ, Kafka): Performance Analysis and Use…”, 2026); (5) Future research should focus on deploying the ARCH framework in real cloud environments to evaluate its performance, scalability, and robustness under practical conditions (“Agentic Generative AI Framework for Predictive Fault Detection in Self-Healing…”, 2026). 203 gap statements have been mined from Software System Performance and Reliability papers in our 7.9M-paper local library, which holds 980 papers on the topic; the gaps come from whichever of those papers state one. They are mostly the research gaps the authors state and the papers' abstracts, plus future-work, limitations and challenges passages. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one, so you can read the original claim in context.

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