2017/05/23 by Josef Spillner, Spillner, Josef
Computer Science · Decision Sciences · #C.2.4 #D.2.1 #Distributed #FOS: Computer and information sciences #I.2.2 #Parallel #Scientific Computing and Data Management #Software Engineering (cs.SE) #Software Engineering Research #Software System Performance and Reliability #and Cluster Computing (cs.DC) #cs.DC #cs.SE
paper · pdf · doi:10.48550/arxiv.1705.08169
14 pages, 2 tables, 5 figures, repeatable, unreviewed
arxiv created 2017/05/23 · openalex publication_date 2017/05/23 · arxiv updated 2017/05/24 · openalex created_date 2017/06/05 · openalex updated_date 2026/07/28
New cloud programming and deployment models pose challenges to software application engineers who are looking, often in vain, for tools to automate any necessary code adaptation and transformation. Function-as-a-Service interfaces are particular non-trivial targets when considering that most cloud applications are implemented in non-functional languages. Among the most widely used of these languages is Python. This starting position calls for an automated approach to transform monolithic Python code into modular FaaS units by partially automated decomposition. Hence, this paper introduces and evaluates Lambada, a Python module to dynamically decompose, convert and deploy unmodified Python code into AWS Lambda functions. Beyond the tooling in the form of a measured open source prototype implementation, the paper contributes a description of the algorithms and code rewriting rules as blueprints for transformations of other scripting languages.