Choral is a language for the programming of choreographies. A choreography is a multiparty protocol that defines how some roles (the proverbial Alice, Bob, etc.) should coordinate with each other to do something together.

Choral is designed to help developers program distributed authentication protocols, cryptographic protocols, business processes, parallel algorithms, or any other protocol for concurrent and distributed systems. At the press of a button, the Choral compiler translates a choreography into a library for each role. Developers can use the generated libraries to make sure that their programs (like a client, or a service) follow your choreography correctly. Choral makes sure that the generated libraries are compliant implementations of the source choreography, making programmers more productive, and preventing them from writing incompatible implementations of communications.

Choral is currently interoperable with Java (and it is planned to support also other programming languages). Choral is compatible with Java in three ways: 1) its syntax is a direct extension of Java (if you know Java, Choral is just a step away); 2) Choral code can reuse Java libraries; 3) the libraries generated by Choral are in pure Java with APIs that the programmer controls, and that can be used inside of other Java projects directly.

My contribution

I am part of the Choral team, working on the theory behind the language and its development.

Ransomware is one of the most infamous kinds of malware, particularly the “crypto” subclass, which encrypts users’ files, asking for some monetary ransom in exchange for the decryption key. Recently, crypto-ransomware has grown into a scourge for enterprises and governmental institutions, threatening hospitals, institutional services, and firms. Ranflood is an open-source anti-ransomware tool developed within the Data-Flooding-against-Ransomware family of solutions and able to mix honeypots, resource contention, and moving target defence to effectively contrast ransomware attacks.

At its core, Ranflood buys time for the user to counteract an ongoing attack, e.g., to access an unresponsive, attacked server and shut it down manually. Ranflood implements a dynamic honeypot approach, which consists in generating decoy files and confusing the genuine files of the user with bait ones that the ransomware is lured into encrypting (making it waste time on them rather than on the actual files of the user). This confusion constitutes the moving-target-defence part of the approach. The third prong, that of resource contention, happens over IO access (e.g., for reading and writing on disk), which the ransomware must share with the (IO-heavy) Ranflood flooding routines.

My contribution

I am one of the main contributors in the design of the Data-Flooding-against-Ransomware family and the main developer of Ranflood.

Serverless is a Cloud service that lets users deploy distributed applications as compositions of stateless functions, delegating all system administration tasks to the Cloud platform. Serverless offers users two main benefits: 1) save time by delegating resource allocation, maintenance, and scaling to the platform; 2) pay only for the resources that perform work, avoiding the costs of running idle servers. The industry standard is to let the platform manage the allocation of function execution over the available computing resources, also called workers. However, not all workers are equal when allocating functions, and some workers can be better suited for certain tasks, e.g., equipping hardware accelerators or enduring lower latencies.

APP (Allocation Priority Policies) is a declarative language that supports a scheduling model where users/providers can define function-specific allocation policies so that the scheduler applies the scheduling policy that implements their functional requirements (e.g., prevent trusted and untrusted functions from running on the same workers) and optimise their performance (also considering the ongoing load status of workers).

APP is currently implemented as an open-source prototype extension of theServerless Apache OpenWhisk platform freely available. The deployment of the prototype ishighly automatised, thanks to the provided companion Infrastructure-as-Codescripts, Kubernetes clusters, and the provision of its components ascontainers.

My contribution

I am one of the main contributors in the design of the APP language and in the supervision of its development.

JoT is a testing framework for Microservice Architectures based on technology agnosticism, a core principle of microservices.

The main advantage of JoT is that it reduces the amount of work for a) testing microservices that use different technology stacks, b) writing tests that involve multiple services, and c) reusing tests under different deployment configurations or after changing some of its components (e.g., when, for performance, one reimplements a service with a different technology).

In JoT, tests are orchestrators that can both consume or offer operations from/to the MSA under test. The language for writing JoT tests is Jolie, which provides constructs that support technology agnosticism and the definition of terse test behaviours.

My contribution

I am one of the contributors in the design of the JoT framework and one of its developers/maintainers.

Jolie is a general-purpose service-oriented programming language. It brings elegance, simplicity, and pragmatism in the development of modular, integrated, distributed, and concurrent applications.

The development of the Jolie language is based on a positive loop between formal theory and practical requirements. One of the strongest values of Jolie is the freedom it gives when designing distributed solutions. Depending on the requirements and the constraints of a specific problem, a programmer can choose whether to build a basic, immediate, yet lightweight solution to integrate applications from different domains or to model the solution by exploiting the language’s advanced composition primitives, forging an highly modular distributed system.

The language is continuously maintained and enhanced, with the contribution of researchers from many universities (UniBo, SDU, ITU, DTU, Innopolis University).

Jolie programs strive for minimality, the same minimality advocated by the microservices architectural style.

My contribution

I am part of the Jolie team, working on the theory behind the language and its development. I am also one of the administrators of the official website and a maintainer of the official documentation.