Serverless computing has emerged as a new compelling paradigm for the deployment of applications and services. It represents an evolution of cloud programming models, abstractions, and platforms, and is a testament to the maturity and wide adoption of cloud technologies. In this chapter, we survey existing serverless platforms from industry, academia, and open source projects, identify key characteristics and use cases, and describe technical challenges and open problems.

Jalapeño is a virtual machine for Java TM servers written in the Java language. To be able to address the requirements of servers (performance and scalability in particular), Jalapeño was designed "from scratch" to be as self-sufficient as possible. Jalapeño's unique object model and memory layout allows a hardware null-pointer check as well as fast access to array elements, fields, and methods. Run-time services conventionally provided in native code are implemented primarily in Java. Java threads are multiplexed by virtual processors (implemented as operating system threads). A family of concurrent object allocators and parallel type-accurate garbage collectors is supported. Jalapeño's interoperable compilers enable quasi-preemptive thread switching and precise location of object references. Jalapeño's dynamic optimizing compiler is designed to obtain high quality code for methods that are observed to be frequently executed or computationally intensive.

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This paper addresses the challenge of sound typestate verification, with acceptable precision, for real-world Java programs.We present a novel framework for verification of typestate properties, including several new techniques to precisely treat aliases without undue performance costs. In particular, we present a flowsensitive, context-sensitive, integrated verifier that utilizes a parametric abstract domain combining typestate and aliasing information. To scale to real programs without compromising precision, we present a staged verification system in which faster verifiers run as early stages which reduce the workload for later, more precise, stages.We have evaluated our framework on a number of real Java programs, checking correct API usage for various Java standard libraries. The results show that our approach scales to hundreds of thousands of lines of code, and verifies correctness for 93% of the potential points of failure.