Jacopo Mauro

University of Southern Denmark | SDU · Department of Mathematics and Computer Science

Meta-solver approaches exploit many individual solvers to potentially build a better solver. To assess the performance of meta-solvers, one can adopt the metrics typically used for individual solvers (e.g., runtime or solution quality) or employ more specific evaluation metrics (e.g., by measuring how close the meta-solver gets to its virtual best...

When a robot adapts a learned task for a novel environment, any changes to objects in the novel environment have an unknown effect on its task execution. For example, replacing an object in a pick-and-place task affects where the robot should target its actions, but does not necessarily affect the underlying action model. In contrast, replacing a t...

State-of-the-art serverless platforms use hardcoded scheduling policies that are unaware of the possible topological constraints of functions. Considering these constraints when scheduling functions leads to sensible performance improvements, e.g., minimising loading times or data-access latencies. This issue becomes more pressing when considered i...

Increased levels of digitalization in society expose companies to new security threats, requiring them to establish adequate security and privacy measures. Additionally, the presence of exogenous forces like new regulations, e.g., GDPR and the global COVID-19 pandemic, pose new challenges for companies that should preserve an adequate level of secu...

Meta-solver approaches exploits a number of individual solvers to potentially build a better solver. To assess the performance of meta-solvers, one can simply adopt the metrics typically used for individual solvers (e.g., runtime or solution quality), or employ more specific evaluation metrics (e.g., by measuring how close the meta-solver gets to i...

Microservices is an emerging paradigm for developing distributed systems. With their widespread adoption, more and more work investigated the relation between microservices and security. Alas, the literature on this subject does not form a well-defined corpus : it is spread over many venues and composed of contributions mainly addressing specific s...

The advent of cloud computing radically changed the way organisations operate their applications and allows them to achieve high availability of services at affordable cost. Most cloud-computing platforms fostered Kubernetes for their container orchestration and service management. The scheduler is a key component of Kubernetes, as it is responsibl...

SUNNY is an Algorithm Selection (AS) technique originally tailored for Constraint Programming (CP). SUNNY is based on the k-nearest neighbors algorithm and enables one to schedule, from a portfolio of solvers, a subset of solvers to be run on a given CP problem. This approach has proved to be effective for CP problems. In 2015, the ASlib benchmarks...

DevOps advocates the usage of Virtualization Technologies (VT), such as Virtual Machines and Containers. However, it is complex to predict how the usage of a given VT will impact on the performance of an application. In this paper, we present a collection of reference benchmarks that developers can use to orient when looking for the best-performing...

We develop a novel approach for run-time global adaptation of microservice applications, based on synthesis of architecture-level reconfiguration orchestrations. More precisely, we devise an algorithm for automatic reconfiguration that reaches a target system Maximum Computational Load by performing optimal deployment orchestrations. To conceive an...

We develop a novel approach for run-time global adaptation of microservice applications, based on synthesis of architecture-level reconfiguration orchestrations. More precisely, we devise an algorithm for automatic reconfiguration that reaches a target system Maximum Computational Load by performing optimal deployment orchestrations. To conceive an...

Increased levels of digitalization in society expose companies to new security threats, requiring them to establish adequate security and privacy measures. Additionally, the presence of exogenous forces like new regulations, e.g., GDPR and the global COVID-19 pandemic, pose new challenges for companies that should preserve an adequate level of secu...

Serverless computing is a Cloud development paradigm where developers write and compose stateless functions, abstracting from their deployment and scaling. In this paper, we address the problem of function-execution scheduling, i.e., how to schedule the execution of Serverless functions to optimise their performance against some user-defined goals....

SUNNY is an Algorithm Selection (AS) technique originally tailored for Constraint Programming (CP). SUNNY enables to schedule, from a portfolio of solvers, a subset of solvers to be run on a given CP problem. This approach has proved to be effective for CP problems, and its parallel version won many gold medals in the Open category of the MiniZinc...

Following previous work on the automated deployment orchestration of component based applications, where orchestrations are expressed in terms of behaviours satisfying component interface functional dependences, we develop a formal model specifically tailored for microservice architectures. The first result that we obtain is decidability of the pro...

Feature Models are a mechanism to organize the configuration space and facilitate the construction of software variants by describing configuration options using features, i.e., a name representing a functionality. The development of Feature Models is an error prone activity and detecting their anomalies is a challenging and important task needed t...

Software Product Lines (SPLs) are a common technique to capture families of software products in terms of commonalities and variabilities. On a conceptual level, functionality of an SPL is modeled in terms of features in Feature Models (FMs). As other software systems, SPLs and their FMs are subject to evolution that may lead to the introduction of...

Highly-configurable software systems can have thousands of interdependent configuration options across different subsystems. In the resulting configuration space, discovering a valid product configuration for some selected options can be complex and error prone. The configuration space can be organized using a feature model, fragmented into smaller...

Following previous work on the automated deployment of component-based applications, we present a formal model specifically tailored for reasoning on the deployment of microservice architectures. The first result that we present is a formal proof of decidability of the problem of synthesizing optimal deployment plans for microservice architectures,...

In Choreographic Programming, a choreography specifies in a single artefact the expected behaviour of all the participants in a distributed system. The choreography is used to synthesise correct-by-construction programs for each participant.In previous work, we defined Dynamic Choreographies to support the update of distributed systems at runtime.I...

We investigate the problem of modeling the optimal and automatic deployment of cloud applications. We follow an approach based on three main pillars: (i) the specification of the computing resources needed by software components and those provided by the executing environment (e.g. virtual machines or containers), (ii) the declarative description o...

Microservices are highly modular and scalable Service Oriented Architectures. They underpin automated deployment practices like Continuous Deployment and Autoscaling. In this paper we formalize these practices and show that automated deployment — proven undecidable in the general case — is algorithmically treatable for microservices. Our key assump...

Microservices are highly modular and scalable Service Oriented Architectures. They underpin automated deployment practices like Continuous Deployment and Autoscaling. In this paper, we formalize these practices and show that automated deployment - proven undecidable in the general case - is algorithmically treatable for microservices. Our key assum...

Software Product Lines (SPLs) are a common technique to capture families of software products in terms of commonalities and variabilities. On a conceptual level, functionality of an SPL is modeled in terms of features in Feature Models (FMs). As other software systems, SPLs and their FMs are subject to evolution that may lead to the introduction of...

Software Product Lines (SPLs) are a mechanism for large-scale reuse where families of related software systems are represented in terms of commonalities and variabilities, e.g., using Feature Models (FMs). While FMs define all possible configurations of an SPL, when considering dynamic SPLs and environmental conditions, not every possible configura...

It is well-known that the difference between theory and practice seems smaller in theory than in practice. From the perspective of the coordinator, the coordinated components play the role of wild beasts, fortunately imprisoned in boxes. From the perspective of the care-free semanticist, the development of tools is merely a minor step away (possibl...

Background: Exceptional circumstances like major incidents or natural disasters may cause a huge number of victims that might not be immediately and simultaneously saved. In these cases it is important to define priorities avoiding to waste time and resources for not savable victims. Trauma and Injury Severity Score (TRISS) methodology is the well...

A software product line (SPL) uses a variability model, such as a feature model (FM), to describe the configuration options for a set of closely related software systems. Context-aware SPLs also consider possible environment conditions for their configuration options. Errors in modeling the FM and its context may lead to anomalies, such as dead fea...

Humans are social animals and usually organize activities in groups. However, they are often willing to split temporarily a bigger group in subgroups to enhance their preferences. In this work we present NightSplitter, an on-line tool that is able to plan movie and dinner activities for a group of users, possibly splitting them in subgroups to opti...

In Constraint Programming (CP) a portfolio solver combines a variety of different constraint solvers for solving a given problem. This fairly recent approach enables to significantly boost the performance of single solvers, especially when multicore architectures are exploited. In this work we give a brief overview of the portfolio solver sunny-cp,...

Programming distributed applications free from communication deadlocks and race conditions is complex. Preserving these properties when applications are updated at runtime is even harder. We present a choreographic approach for programming updatable, distributed applications. We define a choreography language, called Dynamic Interaction-Oriented Ch...

Modern cloud applications consist of software components deployed on multiple virtual machines. Deploying such applications is error prone and requires detailed system expertise. The deployment optimization problem is about how to configure and deploy applications correctly while at the same time minimizing resource cost on the cloud. This problem...

Software Product Lines (SPLs) are a mechanism to capture families of closely related software systems by modeling commonalities and variability. Although user customization has a growing importance in software systems and is a vital sales argument, SPLs currently only allow user customization at deploy-time. In this paper, we extend the notion of c...

Traditional development methodologies that separate software design from application deployment have been replaced by approaches such as continuous delivery or DevOps, according to which deployment issues should be taken into account already at the early stages of development. This calls for the definition of new modeling and specification language...

The Resource-Constrained Project Scheduling Problem (RCPSP) is a well-known scheduling problem aimed at minimizing the makespan of a project subject to temporal and resource constraints. In this paper we show that hard RCPSPs can be efficiently tackled by a portfolio approach that combines the strengths of different constraint solvers Our approach...

The Aeolus component problem of automatic deployment of complex distributed component systems. In the general setting, the task of checking if a distributed application can be deployed is an undecidable problem. However, the current undecidability proof in Aeolus assumes the possibility to perform in a synchronized way atomic configuration actions...

Microservices is an emerging paradigm for the development of distributed systems that, originating from Service-Oriented Architecture, focuses on the small dimension, the loose coupling, and the dynamic topology of services. Microservices are particularly appropriate for the development of distributed systems in the Cloud. However, their dynamic na...

Software Product Lines (SPLs) are a mechanism for large-scale reuse where families of related software systems are represented in terms of commonalities and variabilities, e.g., using Feature Models (FMs). While FMs define all possible configurations of the SPL, when considering dynamic SPLs not every possible configuration may be valid in all poss...

In the context of Constraint Programming, a portfolio approach exploits the complementary strengths of a portfolio of different constraint solvers. The goal is to predict and run the best solver(s) of the portfolio for solving a new, unseen problem. In this work we reproduce, simulate, and evaluate the performance of different portfolio approaches...

We present Aeolus Blender (Blender in the following), a software product for the automatic deployment and configuration of complex service-based, distributed software systems in the “cloud”. By relying on a configuration optimiser and a deployment planner, Blender fully automates the deployment of real-life applications on OpenStack cloud deploymen...

It is well recognized that a single, arbitrarily efficient solver can be significantly outperformed by a portfolio solver exploiting a combination of possibly slower on-average different solvers. Despite the success of portfolio solvers within the context of solving competitions, they are rarely used in practice. In this paper we give an overview o...

In modern software systems, deployment is an integral and critical part of application development (see, e.g., the DevOps approach to software development). Nevertheless, deployment is usually overlooked at the modeling level, thus losing the possibility to perform deployment conscious decisions during the early stages of development. In this paper...

In distributed systems like those based on cloud or service-oriented frameworks, applications are typically assembled by deploying and connecting a large number of heterogeneous software components, spanning from fine-grained packages to coarse-grained complex services. Automation techniques and tools have been proposed to ease the deployment proce...

In previous works we have proved that component reconfiguration in the presence of conflicts among components is non-primitive recursive, while it becomes poly-time if there are no conflicts and under the assumption that there are no components in the initial configuration. The case with non-empty initial configurations was left as an open problem,...

Programming distributed applications free from communication deadlocks and races is complex. Preserving these properties when applications are updated at runtime is even harder. We present DIOC, a language for programming distributed applications that are free from deadlocks and races by construction. A DIOC program describes a whole distributed ap...

Within the Constraint Satisfaction Problems (CSP) context, a methodology that has proven to be particularly performant consists of using a portfolio of different constraint solvers. Nevertheless, comparatively few studies and investigations have been done in the world of Constraint Optimization Problems (COP). In this work, we provide a generalizat...

The Constraint Programming (CP) paradigm allows to model and solve Constraint Satisfaction/Optimization Problems (CSPs/COPs). A CP Portfolio Solver is a particular constraint solver that takes advantage of a portfolio of different CP solvers in order to solve a given problem by properly exploiting Algorithm Selection techniques. In this work we pre...

In Constraint Programming (CP), a portfolio solver uses a variety of different solvers for solving a given Constraint Satisfaction / Optimization Problem. In this paper we introduce sunny-cp2: the first parallel CP portfolio solver that enables a dynamic, cooperative, and simultaneous execution of its solvers in a multicore setting. It incorporates...

Cloud computing allows to build sophisticated software sys-tems on virtualized infrastructures at a fraction of the cost that was necessary just a few years ago. The deployment of such complex systems, though, is still a serious issue due to the need of deploying a large number of packages and services, their elaborated interdependencies, and the n...

We develop a methodology for verifying distributed, adaptive software systems.•The cornerstone of our framework is the use of choreography languages.•We integrate also different techniques based on abstract interpretation and on dynamic verification.

We introduce the Aeolus component model, which is specifically designed to capture realistic scenarii arising when configuring and deploying distributed applications in the so-called cloud environments, where interconnected components can be deployed on clusters of heterogeneous virtual machines, which can be in turn created, destroyed, and connect...

Proving deadlock freedom for distributed applications is complex. It becomes even harder if those applications dynamically adapt to face needs which were unexpected when the application was deployed or even started. We present a framework ensuring this key property by construction. Our framework includes a language called Adaptive Interaction-Orien...

We present AIOCJ, a framework for programming distributed adaptive applications. Applications are programmed using AIOC, a choreographic language suited for expressing patterns of interaction from a global point of view. AIOC allows the programmer to specify which parts of the application can be adapted. Adaptation takes place at runtime by means o...

Choreographies allow designers to specify the protocols followed by participants of a distributed interaction. In this context, adaptation may be necessary to respond to external requests or to better suit a changing environment (a self-update). Adapting the behavior of a participant requires to update in a coordinated way possibly all the particip...

A constraint is something that restricts, limits, or regulates. From this notion of constraint, a new field of computer science has been created: Constraint Programming (CP).

The past decade has witnessed a significant increase in the number of constraint solving systems deployed for solving constraint satisfaction problems (CSP).

In Service-oriented computing (SOC) interaction with remote services may incur in errors of different kinds: the remote service may disconnect, messages may be lost on the net, received data items may be outside the desired range of values, or a client may decide to interrupt the interaction with a remote service exactly in between the request and...

The idea of approaching hard combinatorial optimization problems through a combination of search and constraint solving appeared first in logic programming. Despite the continued support of logic programming for constraint programmers, research efforts were initiated to import constraint technologies into other paradigms.

Cloud computing, introduced in Sect. 3. 1. 3, can be a powerful infrastructure for solving Constraint Satisfaction Problems (CSPs) in parallel, since sometimes dedicated machines are too expensive to be afforded. In a scenario where a lot of CSPs need to be solved concurrently, the resources provided by a cloud can be used with four main advantages...

The original theoretical operational semantics for CHR, denoted by \(\omega _t\), is nondeterministic, as usual for many other rule based and concurrent languages. Such a nondeterminism has to be resolved in the implementations by choosing a suitable execution strategy. Most implementations indeed use the, so-called, refined operational semantics,...

Given the spread of small computing device, it can be very useful to implement a language like CHR that runs concurrently in a given environment.

Service-Oriented Computing (SOC), presented in Sect. 3. 5 is a paradigm for programming distributed applications by means of the composition of services. Services are autonomous, self-descriptive computational entities that can be dynamically discovered and composed in order to build more complex functionalities.

Concurrency in computer science is a property of systems in which more than one execution context can be active at the same time.

Disasters like terrorist attacks, earthquakes, hurricanes, and volcano eruptions are usually unpredictable events that affect a high number of people. We propose an approach that could be used as a decision support tool for a post-disaster response that allows the assignment of victims to hospitals and organizes their transportation via emergency v...

Within the context of constraint solving, a portfolio approach allows one to exploit the synergy between different solvers in order to create a globally better solver. In this paper we present SUNNY: a simple and flexible algorithm that takes advantage of a portfolio of solvers in order to dynamically compute a schedule of (a subset of) them for so...

Cloud computing offers the possibility to build sophisticatedsoftware systems on virtualized infrastructures at a fractionof the cost necessary just a few years ago. Nevertheless, thedeployment of such complex systems is a serious issue due tothe large number of involved software packages and services, and to their elaborated interdependencies. In...

In distributed systems like clouds or service oriented frameworks, applications are typically assembled by deploying and connecting a large number of heterogeneous software components, spanning from fine-grained packages to coarse-grained complex services. The complexity of such systems requires a rich set of techniques and tools to support the aut...

Cloud computing offers the possibility to build sophisticated software systems on virtualized infrastructures at a fraction of the cost necessary just few years ago, but deploying/maintaining/reconfiguring such software systems is a serious challenge. The main objective of the Aeolus project, an initiative funded by ANR (the French “Agence National...

Recent research has shown that a single arbitrarily efficient solver can be significantly outperformed by a portfolio of possibly slower on-average solvers. The solver selection is usually done by means of (un)supervised learning techniques which exploit features extracted from the problem specification. In this paper we present an useful and flexi...

Components are traditionally modeled as black-boxes equipped with interfaces that indicate provided/required ports and, often, also conflicts with other components that cannot coexist with them. In modern tools for automatic system management, components become grey-boxes that show relevant internal states and the possible actions that can be acted...

Constraint Handling Rules (CHR) is a committed-choice declarative language which has been originally designed for writing constraint solvers and which is nowadays a general purpose language. Recently the language has been extended by introducing user-definable (static or dynamic) rule priorities. The resulting language allows a better control over...

Disasters like terrorist attacks, earthquakes, hurricanes, and volcano eruptions are usually unpredictable events that affect a high number of people. We propose an approach that can be used as a decision support tool for a post-disaster response that allows the assignment of victims to hospitals and organizes their transportation via emergency veh...

Recent research in areas such as SAT solving and Integer Linear Programming has shown that the performances of a single arbitrarily efficient solver can be significantly outperformed by a portfolio of possibly slower on-average solvers. We report an empirical evaluation and comparison of portfolio approaches applied to Constraint Satisfaction Probl...

In the context of Service-Oriented Architectures (SOAs), the integration of services is an important aspect that is usually addressed by using specific tools, such as Enterprise Service Bus (ESB). In this paper we propose a framework to perform service integration building on the extension of service interfaces, capturing a class of service integra...

Service-oriented architectures (SOAs) usually comprehend in-the- middle entities such as proxies or service mediators that compose services abstracting from the order in which they exchange messages. Although widely used, these entities are usually implemented by means of ad-hoc solutions. In this paper we generalise this composition mechanism by i...

Gecode is one of the most efficient libraries that can be used for constraint solving. However, using it requires dealing with C++ programming details. On the other hand several formats for representing constraint networks have been proposed. Among them, XCSP has been proposed as a format based on XML which allows us to represent constraints define...

Bi-directional request-response interaction is a standard communication pattern in Service Oriented Computing (SOC). Such a pattern should be interrupted in case of faults. In the literature, different approaches have been considered: WS-BPEL discards the response, while Jolie waits for it in order to allow the fault handler to appropriately close...

A fundamental aspect which affects the efficiency and the performance of Service-Oriented Architectures is the mechanism which allows to manage sessions and, in particular, to assign incoming messages to the correct sessions (also known as service instances). A relevant mechanism for solving this problem, first introduced by BPEL and then used in o...

Constraint Handling Rules (CHR) is a committed-choice declarative language which has been originally designed for writing constraint solvers and which is nowadays a general purpose language. Recently the language has been extended by introducing user-definable (static or dynamic) rule priorities. The resulting language, called CHRrp, allows a bette...

We developed a compiler from SICStus Prolog CLP(FD) to Gecode as well as a compiler from MiniZinc to Gecode. We compared the running times of the executions of (standard) codes directly written in the three languages and of the compiled codes for a series of classical problems. Performances of the com- piled codes in Gecode improve those in the ori...

Recent years have witnessed growing interest in parallelising constraint solving based on tree search (see [1] for a brief overview). One approach is search-space splitting in which different parts of the tree are explored in parallel (e.g. [2]). Another approach is the use of algorithm portfolios. This technique exploits the significant variety in...

Planning Domain Denition Language (PDDL) is the most used language to encode and solve planning problems. In this paper we propose two PDDL-like languages that extend PDDL with new con- structs such as static causal laws and time uents with the aim of im- proving the expressivity of PDDL language. We study the complexity of the main computational p...