相关论文: Static analysis tools in the era of cloud-native s…

In recent decades, it has become a significant tendency for industrial manufacturers to adopt decentralization as a new manufacturing paradigm. This enables more efficient operations and facilitates the shift from mass to customized…

Context: Several companies are migrating their information systems into the Cloud. Microservices and DevOps are two of the most common adopted technologies. However, there is still a lack of understanding how to adopt a microservice-based…

When faults occur in microservice applications -- as they inevitably do -- developers depend on observability data to quickly identify and diagnose the issue. To collect such data, microservices need to be instrumented and the respective…

Static Application Security Testing (SAST) is a popular quality assurance technique in software engineering. However, integrating SAST tools into industry-level product development and security assessment poses various technical and…

As Clouds are complex, large-scale, and heterogeneous distributed systems, management of their resources is a challenging task. They need automated and integrated intelligent strategies for provisioning of resources to offer services that…

In this paper, we present a novel marriage of static and dynamic analysis. Given a large code base with many functions and a mature test suite, we propose using static analysis to find functions 1) with assertions or other evident…

The evolution of decentralized microservice-based systems is challenging. These challenges are classified into static and dynamic categories. Regarding the static perspective, documenting and visualizing the fluid application topology is…

Machine learning is now a central part of how modern systems are built and used, powering everything from personalized recommendations to large-scale business analytics. As its role grows, organizations are facing new challenges in…

Microservice architecture can be modeled as a network of microservices making calls to each other, commonly known as the service dependency graph. Network Science can provide methods to study such networks. In particular, temporal network…

Static analysis techniques enhance the security, performance, and reliability of programs by analyzing and portraiting program behaviors without the need for actual execution. In essence, static analysis takes the Intermediate…

Microservices have gained wide recognition and acceptance in software industries as an emerging architectural style for autonomic, scalable, and more reliable computing. The transition to microservices has been highly motivated by the need…

With the increased dependence on software, there is a pressing need for engineering long-lived software. As architectures have a profound effect on the life-span of the software and the provisioned quality of service, stable architectures…

An increasing number of Analytics-as-a-Service solutions has recently seen the light, in the landscape of cloud-based services. These services allow flexible composition of compute and storage components, that create powerful data ingestion…

Microservice architectures promote small, independently developed services, but increase overall architectural complexity. It is crucial that developers understand the architecture and how changes to a service affect the overall system, but…

The idea behind microservices architecture is to develop a single large, complex application as a suite of small, cohesive, independent services. On the other way, monolithic systems get larger over the time, deviating from the intended…

Microservices are used to build complex applications composed of small, independent and highly decoupled processes. Recently, microservices are often mentioned in one breath with container technologies like Docker. That is why operating…

In recent years, there has been significant progress in the development and industrial adoption of static analyzers. Such analyzers typically provide a large, if not huge, number of configurable options controlling the precision and…

As organizations increasingly migrate their applications to the cloud, the optimization of microservices architectures becomes imperative for achieving sustainability goals. Nonetheless, sustainable deployments may increase costs and…

Where full static analysis of systems fails to scale up due to system size, dynamic monitoring has been increasingly used to ensure system correctness. The downside is, however, runtime overheads which are induced by the additional…

With the maturity of web services, containers, and cloud computing technologies, large services in traditional systems (e.g. the computation services of machine learning and artificial intelligence) are gradually being broken down into many…