Goals and Roadmap


Since the inception of this project, which is the beginning of March 2014, a number of milestones have been achieved and many components are feature complete at this point. However, there are still many new and exciting features to be designed and implemented ahead that can greatly enhance the coreVM’s capability and versatility. There are several major features that are envisioned after the initial version, and they are:

Debugging and Profiling API

These are a set of interfaces and facilities that provide developers powerful capabilities to debug executable code running on coreVM. This includes the typical debugging capabilities such as pause/resume executions, variables examination, call stack unwinding and rewinding, etc. In addition, there will be a set of facilities for instrumenting a number of aspects regarding executions, such as process introspections, memory footprint statistics, heap allocation heat map, to name a few.

Embedder API

The Embedder API provide developers the capabilities to create virtual execution runtimes in their applications by interacting with a set of interfaces and abstract models that define the entities and behaviors of executions of coreVM’s internal runtime. For example, a developer who wants to build a lightweight scripting engine in his or her application can employ the Embedder API to accomplish the heavy liftings of executing user provided scripts. All the work for that developer is to parse user provided scripts, and the rest can be left for coreVM to handle.

Extension API

The Extension API is at the frontier of the next wave of heavy development with the goal of greatly enhance the capability and versatility of coreVM. The foundation of this is a scripting engine that allows developers to modify the functionalities of existing instructions and to create their own ones to performs custom functionalities. Developers can use a set of micro-instructions to program their desired functionalities for existing and new instructions.

The next feature is called the Reactive Event Model, which is a model that provides the runtime the capability to react to a set of defined events that are occurring to the execution environment. For example, a developer may want to implement a language feature which passively reacts to certain events happening in the host operating system.

The last feature to support is native plugins, which allows developers to incorporate the execution of native code in conjunction with coreVM’s execution, in order to allow more interactions with the operating system.

Threading API

Thread management and concurrent executions are essential to most modern languages. Developers want to work with languages that have robust concurrency support and thread management capabilities, in order to take advantage of modern hardware and to achieve higher program throughput.

The Threading API aims to provide language developers a set of intuitive interfaces for managing threaded and concurrent executions.

Just-In-Time Compilation

Just-in-time compilation, or simply JIT, once a novel idea and powerful technique for statically typed languages, are now becoming prevalent for dynamic languages as well. Many modern dynamic languages use a combination of techniques to compile portions of bytecode into native machine code, in order to speed up executions of critical code paths.

Future versions of coreVM will be equipped with a JIT engine that performs the same task by employing a variety of techniques, such as OSR, type inference, live code analysis, to name a few.

Project Pyta

Besides the set of powerful features described above, another monumental endeavor in the project is to engineer a different implementation of the Python programming language, codenamed Project Pyta, using an approach that is completely different than that of CPython’s by utilizing the capabilities of coreVM. Having the ability to support a real reference language complements the development of coreVM as it helps to test the system and provides meaningful feedbacks to improve its stability and performance, as well as to enhance its functionalities and versatilities.

Milestones and Roadmap

Below is a table of all the past milestones and some of the goals defined in the roadmap in the near future, with their respective completion dates and ETAs:

Milestone Completion date/ETA
Memory allocation schemes (done) Mar, 2014
Dynamic object management (done) Mar, 2014
Native types system (done) Jun, 2014
Instruction execution (done) Aug, 2014
Signal handling (done) Aug, 2014
GC implementation and integration (done) Aug, 2014
Bytecode loading and validation (done) Feb, 2015
Frontend and runtime integration (done) Feb, 2015
Bug fixes and regression tests (done) Mar, 2015
Support basic features in Python (done) Mar, 2015
Python features convergence (done) Apr, 2015
Optimizations (done) May, 2015
Benchmark infrastructure Jun, 2015
Python features convergence (cont’d) Oct, 2015
Optimizations (cont’d) Feb, 2016
Core API (cont’d) Jul, 2016
Intermediate Representation (done) Jan, 2017
JIT pipeline TBD
Multi-threaded runtime TBD
Debugging and Profiling API TBD
Embedder API TBD
Extension API TBD
Threading API TBD
Parallelism support TBD
Address space layout randomization TBD