Towards Semantic Detection of Smells in Cloud Infrastructure Code
Indika Kumara, Zoe Vasileiou, Georgios Meditskos, Damian A. Tamburri, Willem-Jan Van Den Heuvel, Anastasios Karakostas, Stefanos Vrochidis, Ioannis Kompatsiaris
备注：
5 pages, 6 figures. The 10 th International Conference on Web Intelligence, Mining and Semantics (WIMS 2020)
发表信息：
In The 10th International Conference on Web Intelligence, Mining and Semantics (WIMS 2020), June 30-July 3, 2020, Biarritz, France. ACM, New York, NY, USA, 5 pages
Automated deployment and management of Cloud applications relies on descriptions of their deployment topologies, often referred to as Infrastructure Code. As the complexity of applications and their deployment models increases, developers inadvertently introduce software smells to such code specifications, for instance, violations of good coding practices, modular structure, and more. This paper presents a knowledge-driven approach enabling developers to identify the aforementioned smells in deployment descriptions. We detect smells with SPARQL-based rules over pattern-based OWL 2 knowledge graphs capturing deployment models. We show the feasibility of our approach with a prototype and three case studies.
Cloud-based software-as-a-service (SaaS) have gained popularity due to their low cost and elasticity. However, like other software, SaaS applications suffer from code smells, which can drastically affect functionality and resource usage. Code smell is any design in the source code that indicates a deeper problem. The software community deploys automated refactoring to eliminate smells which can improve performance and also decrease the usage of critical resources. However, studies that analyze the impact of automatic refactoring smells in SaaS on resources such as CPU and memory have been cond…
Infrastructure as Code (IaC) is the process of managing IT infrastructure via programmable configuration files (also called IaC scripts). Like other software artifacts, IaC scripts may contain security smells, which are coding patterns that can result in security weaknesses. Automated analysis tools to detect security smells in IaC scripts exist, but they focus on specific technologies such as Puppet, Ansible, or Chef. This means that when the detection of a new smell is implemented in one of the tools, it is not immediately available for the technologies supported by the other tools -- the on…
Context: Security smells are recurring coding patterns that are indicative of security weakness, and require further inspection. As infrastructure as code (IaC) scripts, such as Ansible and Chef scripts, are used to provision cloud-based servers and systems at scale, security smells in IaC scripts could be used to enable malicious users to exploit vulnerabilities in the provisioned systems. Goal: The goal of this paper is to help practitioners avoid insecure coding practices while developing infrastructure as code scripts through an empirical study of security smells in Ansible and Chef script…
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Green software engineering aims at reducing the environmental impact due to developing, deploying, and managing software systems. Meanwhile, Cloud-IoT paradigms can contribute to improving energy and carbon efficiency of application deployments by (i) reducing the amount of data and the distance they must travel across the network, (ii) by exploiting idle edge devices to support application deployment. In this article, we propose a declarative methodology and its Prolog prototype for determining placements of application services onto Cloud-IoT infrastructures so to optimise energy and carbon …
