Keywords
 A2. Software
 A2.1. Programming Languages
 A2.1.1. Semantics of programming languages
 A2.1.5. Constraint programming
 A2.1.9. Synchronous languages
 A2.1.10. Domainspecific languages
 A2.2. Compilation
 A2.3. Embedded and cyberphysical systems
 A2.3.1. Embedded systems
 A2.3.2. Cyberphysical systems
 A2.3.3. Realtime systems
 A2.4. Formal method for verification, reliability, certification
 A2.4.1. Analysis
 A2.4.2. Modelchecking
 A2.4.3. Proofs
 A2.5. Software engineering
 A2.5.1. Software Architecture & Design
 A2.5.2. Componentbased Design
 A3. Data and knowledge
 A3.1. Data
 A3.1.1. Modeling, representation
 A6. Modeling, simulation and control
 A6.1. Methods in mathematical modeling
 A6.1.1. Continuous Modeling (PDE, ODE)
 A6.1.3. Discrete Modeling (multiagent, people centered)
 A6.1.5. Multiphysics modeling
 A8.4. Computer Algebra
 B2. Health
 B2.4. Therapies
 B2.4.3. Surgery
 B4. Energy
 B4.4. Energy delivery
 B4.4.1. Smart grids
 B5. Industry of the future
 B5.2. Design and manufacturing
 B5.2.1. Road vehicles
 B5.2.2. Railway
 B5.2.3. Aviation
 B5.2.4. Aerospace
 B5.8. Learning and training
 B5.9. Industrial maintenance
 B7. Transport and logistics
 B7.1. Traffic management
 B7.1.3. Air traffic
 B8. Smart Cities and Territories
 B8.1. Smart building/home
 B8.1.1. Energy for smart buildings
1 Team members, visitors, external collaborators
Research Scientists
 Benoît Caillaud [Team leader, Inria, Senior Researcher, HDR]
 Albert Benveniste [Inria, Emeritus, HDR]
 Khalil Ghorbal [Inria, Researcher]
PhD Students
 Christelle Kozaily [Inria]
 Aurélien Lamercerie [Univ de Rennes I]
 Joan Thibault [Univ de Rennes I]
Technical Staff
 Mathias Malandain [Inria, Engineer]
 Bertrand Provot [Inria, Engineer, from Oct 2020]
Interns and Apprentices
 Julien Duron [Univ de Rennes I, from Jun 2020 until Jul 2020]
Administrative Assistant
 Armelle Mozziconacci [CNRS]
2 Overall objectives
Hycomes was created a local team of the Rennes  Bretagne Atlantique Inria research center in 2013 and has been created as an Inria ProjectTeam in 2016. The team is focused on two topics in cyberphysical systems design:
 Hybrid systems modelling, with an emphasis on the design of modelling languages in which software systems, in interaction with a complex physical environment, can be modelled, simulated and verified. A special attention is paid to the mathematical rigorous semantics of these languages, and to the correctness (wrt. such semantics) of the simulations and of the static analyses that must be performed during compilation. The Modelica language is the main application field. The team aims at contributing language extensions facilitating the modelling of physical domains which are poorly supported by the Modelica language. The Hycomes team is also designing new structural analysis methods for hybrid (aka. multimode) Modelica models. New simulation and verification techniques for large Modelica models are also in the scope of the team.
 Contractbased design and interface theories, with applications to requirements engineering in the context of safetycritical systems design. The objective of our research is to bridge the gap between systemlevel requirements, often expressed in natural, constrained or semiformal languages and formal models, that can be simulated and verified.
3 Research program
3.1 Hybrid Systems Modeling
Systems industries today make extensive use of mathematical modeling tools to design computer controlled physical systems. This class of tools addresses the modeling of physical systems with models that are simpler than usual scientific computing problems by using only Ordinary Differential Equations (ODE) and Difference Equations but not Partial Differential Equations (PDE). This family of tools first emerged in the 1980's with SystemBuild by MatrixX (now distributed by National Instruments) followed soon by Simulink by Mathworks, with an impressive subsequent development.
In the early 90's control scientists from the University of Lund (Sweden) realized that the above approach did not support component based modeling of physical systems with reuse 1. For instance, it was not easy to draw an electrical or hydraulic circuit by assembling component models of the various devices. The development of the Omola language by Hilding Elmqvist was a first attempt to bridge this gap by supporting some form of Differential Algebraic Equations (DAE) in the models. Modelica quickly emerged from this first attempt and became in the 2000's a major international concerted effort with the Modelica Consortium 2. A wider set of tools, both industrial and academic, now exists in this segment 3. In the EDA sector, VHDLAMS was developed as a standard 52 and also allows for differential algebraic equations. Several domainspecific languages and tools for mechanical systems or electronic circuits also support some restricted classes of differential algebraic equations. Spice is the historic and most striking instance of these domainspecific languages/tools 4. The main difference is that equations are hidden and the fixed structure of the differential algebraic results from the physical domain covered by these languages.
Despite these tools are now widely used by a number of engineers, they raise a number of technical difficulties. The meaning of some programs, their mathematical semantics, is indeed ambiguous. A main source of difficulty is the correct simulation of continuoustime dynamics, interacting with discretetime dynamics: How the propagation of mode switchings should be handled? How to avoid artifacts due to the use of a global ODE solver causing unwanted coupling between seemingly non interacting subsystems? Also, the mixed use of an equational style for the continuous dynamics with an imperative style for the mode changes and resets is a source of difficulty when handling parallel composition. It is therefore not uncommon that tools return complex warnings for programs with many different suggested hints for fixing them. Yet, these “pathological” programs can still be executed, if wanted so, giving surprising results — See for instance the Simulink examples in 24, 20 and 21.
Indeed this area suffers from the same difficulties that led to the development of the theory of synchronous languages as an effort to fix obscure compilation schemes for discrete time equation based languages in the 1980's. Our vision is that hybrid systems modeling tools deserve similar efforts in theory as synchronous languages did for the programming of embedded systems.
3.2 Background on nonstandard analysis
NonStandard analysis plays a central role in our research on hybrid systems modeling 20, 24, 22, 21. The following text provides a brief summary of this theory and gives some hints on its usefulness in the context of hybrid systems modeling. This presentation is based on our paper 2, a chapter of Simon Bliudze's PhD thesis 30, and a recent presentation of nonstandard analysis, not axiomatic in style, due to the mathematician Lindström 58.
Nonstandard numbers allowed us to reconsider the semantics of hybrid systems and propose a radical alternative to the superdense time semantics developed by Edward Lee and his team as part of the Ptolemy II project, where cascades of successive instants can occur in zero time by using ${\mathbb{R}}_{+}\times \mathbb{N}$ as a time index. In the nonstandard semantics, the time index is defined as a set $\mathbb{T}=\{n\partial \mid n\in {}^{*}\mathbb{N}\}$, where $\partial $ is an infinitesimal and ${}^{*}\mathbb{N}$ is the set of nonstandard integers. Remark that (1) $\mathbb{T}$ is dense in ${\mathbb{R}}_{+}$, making it “continuous”, and (2) every $t\in \mathbb{T}$ has a predecessor in $\mathbb{T}$ and a successor in $\mathbb{T}$, making it “discrete”. Although it is not effective from a computability point of view, the nonstandard semantics provides a framework that is familiar to the computer scientist and at the same time efficient as a symbolic abstraction. This makes it an excellent candidate for the development of provably correct compilation schemes and type systems for hybrid systems modeling languages.
Nonstandard analysis was proposed by Abraham Robinson in the 1960s to allow the explicit manipulation of “infinitesimals” in analysis 67, 45, 41. Robinson's approach is axiomatic; he proposes adding three new axioms to the basic ZermeloFraenkel (ZFC) framework. There has been much debate in the mathematical community as to whether it is worth considering nonstandard analysis instead of staying with the traditional one. We do not enter this debate. The important thing for us is that nonstandard analysis allows the use of the nonstandard discretization of continuous dynamics “as if” it was operational.
Not surprisingly, such an idea is quite ancient. Iwasaki et al. 53 first proposed using nonstandard analysis to discuss the nature of time in hybrid systems. Bliudze and Krob 29, 30 have also used nonstandard analysis as a mathematical support for defining a system theory for hybrid systems. They discuss in detail the notion of “system” and investigate computability issues. The formalization they propose closely follows that of Turing machines, with a memory tape and a control mechanism.
3.3 Structural Analysis of DAE Systems
The Modelica language is based on Differential Algebraic Equations (DAE). The general form of a DAE is given by:
where $F$ is a system of ${n}_{e}$ equations $\{{f}_{1},\cdots ,{f}_{{n}_{e}}\}$ and $x$ is a finite list of ${n}_{v}$ independent realvalued, smooth enough, functions $\{{x}_{1},\cdots ,{x}_{{n}_{v}}\}$ of the independent variable $t$. We use ${x}^{\text{'}}$ as a shorthand for the list of firstorder time derivatives of ${x}_{j}$, $j=1,\cdots ,{n}_{v}$. Highorder derivatives are recursively defined as usual, and ${x}^{\left(k\right)}$ denotes the list formed by the $k$th derivatives of the functions ${x}_{j}$. Each ${f}_{i}$ depends on the scalar $t$ and some of the functions ${x}_{j}$ as well as a finite number of their derivatives.
Let ${\sigma}_{i,j}$ denote the highest differentiation order of variable ${x}_{j}$ effectively appearing in equation ${f}_{i}$, or $\infty $ if ${x}_{j}$ does not appear in ${f}_{i}$. The leading variables of $F$ are the variables in the set
The state variables of $F$ are the variables in the set
A leading variable ${x}_{j}^{\left({\sigma}_{j}\right)}$ is said to be algebraic if ${\sigma}_{j}=0$ (in which case, neither ${x}_{j}$ nor any of its derivatives are state variables). In the sequel, $v$ and $u$ denote the leading and state variables of $F$, respectively.
DAE are a strict generalization of ordinary differential equations (ODE), in the sense that it may not be immediate to rewrite a DAE as an explicit ODE of the form $v=G\left(u\right)$. The reason is that this transformation relies on the Implicit Function Theorem, requiring that the Jacobian matrix $\frac{\partial F}{\partial v}$ have full rank. This is, in general, not the case for a DAE. Simple examples, like the twodimensional fixedlength pendulum in Cartesian coordinates 64, exhibit this behaviour.
For a square DAE of dimension $n$ (i.e., we now assume ${n}_{e}={n}_{v}=n$) to be solved in the neighborhood of some $({v}^{*},{u}^{*})$, one needs to find a set of nonnegative integers $C=\{{c}_{1},\cdots ,{c}_{n}\}$ such that system
can locally be made explicit, i.e., the Jacobian matrix of ${F}^{\left(C\right)}$ with respect to its leading variables, evaluated at $({v}^{*},{u}^{*})$, is nonsingular. The smallest possible value of ${max}_{i}{c}_{i}$ for a set $C$ that satisfies this property is the differentiation index 35 of $F$, that is, the minimal number of time differentiations of all or part of the equations ${f}_{i}$ required to get an ODE.
In practice, the problem of automatically finding a ”minimal” solution $C$ to this problem quickly becomes intractable. Moreover, the differentiation index may depend on the value of $({v}^{*},{u}^{*})$. This is why, in lieu of numerical nonsingularity, one is interested in the structural nonsingularity of the Jacobian matrix, i.e., its almost certain nonsingularity when its nonzero entries vary over some neighborhood. In this framework, the structural analysis (SA) of a DAE returns, when successful, values of the ${c}_{i}$ that are independent from a given value of $({v}^{*},{u}^{*})$.
A renowned method for the SA of DAE is the Pantelides method; however, Pryce's $\Sigma $method is introduced also in what follows, as it is a crucial tool for our works.
3.3.1 Pantelides method
In 1988, Pantelides proposed what is probably the most wellknown SA method for DAE 64. The leading idea of his work is that the structural representation of a DAE can be condensed into a bipartite graph whose left nodes (resp. right nodes) represent the equations (resp. the variables), and in which an edge exists if and only if the variable occurs in the equation.
By detecting specific subsets of the nodes, called Minimally Structurally Singular (MSS) subsets, the Pantelides method iteratively differentiates part of the equations until a perfect matching between the equations and the leading variables is found. One can easily prove that this is a necessary and sufficient condition for the structural nonsingularity of the system.
The main reason why the Pantelides method is not used in our work is that it cannot efficiently be adapted to multimode DAE (mDAE). As a matter of fact, the adjacency graph of a mDAE has both its nodes and edges parametrized by the subset of modes in which they are active; this, in turn, requires that a parametrized Pantelides method must branch every time no modeindependent MSS is found, ultimately resulting, in the worst case, in the enumeration of modes.
3.3.2 Pryce's Sigmamethod
Albeit less renowned that the Pantelides method, Pryce's $\Sigma $method 65 is an efficient SA method for DAE, whose equivalence to the Pantelides method has been proved by the author. This method consists in solving two successive problems, denoted by primal and dual, relying on the $\Sigma $matrix, or signature matrix, of the DAE $F$.
This matrix is given by:
where ${\sigma}_{ij}$ is equal to the greatest integer $k$ such that ${x}_{j}^{\left(k\right)}$ appears in ${f}_{i}$, or $\infty $ if variable ${x}_{j}$ does not appear in ${f}_{i}$. It is the adjacency matrix of a weighted bipartite graph, with structure similar to the graph considered in the Pantelides method, but whose edges are weighted by the highest differentiation orders. The $\infty $ entries denote nonexistent edges.
The primal problem consists in finding a maximumweight perfect matching (MWPM) in the weighted adjacency graph. This is actually an assignment problem, for the solving of which several standard algorithms exist, such as the pushrelabel algorithm 51 or the EdmondsKarp algorithm 47 to only give a few. However, none of these algorithms are easily parametrizable, even for applications to mDAE systems with a fixed number of variables.
The dual problem consists in finding the componentwise minimal solution $(C,D)=(\{{c}_{1},\cdots ,{c}_{n}\},\{{d}_{1},\cdots ,{d}_{n}\})$ to a given linear programming problem, defined as the dual of the aforementioned assignment problem. This is performed by means of a fixpoint iteration (FPI) that makes use of the MWPM found as a solution to the primal problem, described by the set of tuples ${\left\{(i,{j}_{i})\right\}}_{i\in \{1,\cdots ,n\}}$:
 Initialize $\{{c}_{1},\cdots ,{c}_{n}\}$ to the zero vector.
 For every $j\in \{1,\cdots ,n\}$,
 For every $i\in \{1,\cdots ,n\}$,
 Repeat Steps 2 and 3 until convergence is reached.
From the results proved by Pryce in 65, it is known that the above algorithm terminates if and only if it is provided a MWPM, and that the values it returns are independent of the choice of a MWPM whenever there exist several such matchings. In particular, a direct corollary is that the $\Sigma $method succeeds as long as a perfect matching can be found between equations and variables.
Another important result is that, if the Pantelides method succeeds for a given DAE $F$, then the $\Sigma $method also succeeds for $F$ and the values it returns for $C$ are exactly the differentiation indices for the equations that are returned by the Pantelides method. As for the values of the ${d}_{j}$, being given by ${d}_{j}={max}_{i}({\sigma}_{ij}+{c}_{i})$, they are the differentiation indices of the leading variables in ${F}^{\left(C\right)}$.
Working with this method is natural for our works, since the algorithm for solving the dual problem is easily parametrizable for dealing with multimode systems, as shown in our recent paper 34.
3.3.3 Block triangular decomposition
Once structural analysis has been performed, system ${F}^{\left(C\right)}$ can be regarded, for the needs of numerical solving, as an algebraic system with unknowns ${x}_{j}^{\left({d}_{j}\right)}$, $j=1\cdots n$. As such, (inter)dependencies between its equations must be taken into account in order to put it into block triangular form (BTF). Three steps are required:
 the dependency graph of system ${F}^{\left(C\right)}$ is generated, by taking into account the perfect matching between equations ${f}_{i}^{\left({c}_{i}\right)}$ and unknowns ${x}_{j}^{\left({d}_{j}\right)}$;
 the strongly connected components (SCC) in this graph are determined: these will be the equation blocks that have to be solved;
 the block dependency graph is constructed as the condensation of the dependency graph, from the knowledge of the SCC; a BTF of system ${F}^{\left(C\right)}$ can be made explicit from this graph.
3.4 ContractBased Design, Interfaces Theories, and Requirements Engineering
System companies such as automotive and aeronautic companies are facing significant difficulties due to the exponentially raising complexity of their products coupled with increasingly tight demands on functionality, correctness, and timetomarket. The cost of being late to market or of imperfections in the products is staggering as witnessed by the recent recalls and delivery delays that many major car and airplane manufacturers had to bear in the recent years. The specific root causes of these design problems are complex and relate to a number of issues ranging from design processes and relationships with different departments of the same company and with suppliers, to incomplete requirement specification and testing.
We believe the most promising means to address the challenges in systems engineering is to employ structured and formal design methodologies that seamlessly and coherently combine the various viewpoints of the design space (behavior, space, time, energy, reliability, ...), that provide the appropriate abstractions to manage the inherent complexity, and that can provide correctbyconstruction implementations. The following technology issues must be addressed when developing new approaches to the design of complex systems:
 The overall design flows for heterogeneous systems and the associated use of models across traditional boundaries are not well developed and understood. Relationships between different teams inside a same company, or between different stakeholders in the supplier chain, are not well supported by solid technical descriptions for the mutual obligations.
 System requirements capture and analysis is in large part a heuristic process, where the informal text and natural languagebased techniques in use today are facing significant challenges 9. Formal requirements engineering is in its infancy: mathematical models, formal analysis techniques and links to system implementation must be developed.
 Dealing with variability, uncertainty, and lifecycle issues, such as extensibility of a product family, are not welladdressed using available systems engineering methodologies and tools.
The challenge is to address the entire process and not to consider only local solutions of methodology, tools, and models that ease part of the design.
Contractbased design has been proposed as a new approach to the system design problem that is rigorous and effective in dealing with the problems and challenges described before, and that, at the same time, does not require a radical change in the way industrial designers carry out their task as it cuts across design flows of different types. Indeed, contracts can be used almost everywhere and at nearly all stages of system design, from early requirements capture, to embedded computing infrastructure and detailed design involving circuits and other hardware. Contracts explicitly handle pairs of properties, respectively representing the assumptions on the environment and the guarantees of the system under these assumptions. Intuitively, a contract is a pair $C=(A,G)$ of assumptions and guarantees characterizing in a formal way 1) under which context the design is assumed to operate, and 2) what its obligations are. Assume/Guarantee reasoning has been known for a long time, and has been used mostly as verification mean for the design of software 62. However, contract based design with explicit assumptions is a philosophy that should be followed all along the design, with all kinds of models, whenever necessary. Here, specifications are not limited to profiles, types, or taxonomy of data, but also describe the functions, performances of various kinds (time and energy), and reliability. This amounts to enrich a component's interface with, on one hand, formal specifications of the behavior of the environment in which the component may be instantiated and, on the other hand, of the expected behavior of the component itself. The consideration of rich interfaces is still in its infancy. So far, academic researchers have addressed the mathematics and algorithmics of interfaces theories and contractbased reasoning. To make them a technique of choice for system engineers, we must develop:
 mathematical foundations for interfaces and requirements engineering that enable the design of frameworks and tools;
 a system engineering framework and associated methodologies and toolsets that focus on system requirements modeling, contract specification, and verification at multiple abstraction layers.
A detailed bibliography on contract and interface theories for embedded system design can be found in 3. In a nutshell, contract and interface theories fall into two main categories:
 Assume/guarantee contracts. By explicitly relying on the notions of assumptions and guarantees, A/Gcontracts are intuitive, which makes them appealing for the engineer. In A/Gcontracts, assumptions and guarantees are just properties regarding the behavior of a component and of its environment. The typical case is when these properties are formal languages or sets of traces, which includes the class of safety properties 55, 38, 61, 19, 40. Contract theories were initially developed as specification formalisms able to refuse some inputs from the environment 46. A/Gcontracts were advocated in 23 and are is still a very active research topic, with several contributions dealing with the timed 28 and probabilistic 32, 33 viewpoints in system design, and even mixedanalog circuit design 63.
 Automata theoretic interfaces. Interfaces combine assumptions and guarantees in a single, automata theoretic specification. Most interface theories are based on Lynch's Input/Output Automata 60, 59. Interface Automata 70, 69, 71, 36 focus primarily on parallel composition and compatibility: Two interfaces can be composed and are compatible if there is at least one environment where they can work together. The idea is that the resulting composition exposes as an interface the needed information to ensure that incompatible pairs of states cannot be reached. This can be achieved by using the possibility, for an Interface Automaton, to refuse selected inputs from the environment in a given state, which amounts to the implicit assumption that the environment will never produce any of the refused inputs, when the interface is in this state. Modal Interfaces 66 inherit from both Interface Automata and the originally unrelated notion of Modal Transition System 57, 18, 31, 56. Modal Interfaces are strictly more expressive than Interface Automata by decoupling the I/O orientation of an event and its deontic modalities (mandatory, allowed or forbidden). Informally, a must transition is available in every component that realizes the modal interface, while a may transition needs not be. Research on interface theories is still very active. For instance, timed 72, 25, 27, 43, 42, 26, probabilistic 32, 44 and energyaware 37 interface theories have been proposed recently.
Requirements Engineering is one of the major concerns in large systems industries today, particularly so in sectors where certification prevails 68. Most requirements engineering tools offer a poor structuring of the requirements and cannot be considered as formal modeling frameworks today. They are nothing less, but nothing more than an informal structured documentation enriched with hyperlinks. As examples, medium size subsystems may have a few thousands requirements and the Rafale fighter aircraft has above 250,000 of them. For the Boeing 787, requirements were not stable while subcontractors were working on the development of the flybywire and of the landing gear subsystems, leading to a long and cahotic convergence of the design process.
We see ContractBased Design and Interfaces Theories as innovative tools in support of Requirements Engineering. The Software Engineering community has extensively covered several aspects of Requirements Engineering, in particular:
 the development and use of large and rich ontologies; and
 the use of Model Driven Engineering technology for the structural aspects of requirements and resulting hyperlinks (to tests, documentation, PLM, architecture, and so on).
Behavioral models and properties, however, are not properly encompassed by the above approaches. This is the cause of a remaining gap between this phase of systems design and later phases where formal model based methods involving behavior have become prevalent—see the success of Matlab/Simulink/Scade technologies. We believe that our work on contract based design and interface theories is best suited to bridge this gap.
4 Application domains
The Hycomes team contributes to the design of mathematical modeling languages and tools, to be used for the design of cyberphysical systems. In a nutshell, two major applications can be clearly identified: (i) our work on the structural analysis of multimode DAE systems has a sizeable impact on the techniques to be used in Modelica tools; (ii) our work on the verification of dynamical systems has an impact on the design methodology for safetycritical cyberphysical systems. These two applications are detailed below.
4.1 Modelica
Mathematical modeling tools are a considerable business, with major actors such as MathWorks, with Matlab/Simulink, or Wolfram, with Mathematica. However, none of these prominent tools are suitable for the engineering of large systems. The Modelica language has been designed with this objective in mind, making the best of the advantages of DAEs to support a componentbased approach. Several industries in the energy sector have adopted Modelica as their main systems engineering language.
Although multimode features have been introduced in version 3.3 of the language 48, proper tool support of multimode models is still lagging behind. The reason is not a lack of interest from tool vendors and academia, but rather that multimode DAE systems poses several fundamental difficulties, such as a proper definition of a concept of solutions for multimode DAEs, how to handle mode switchings that trigger a change of system structure, or how impulsive variables should be handled. Our work on multimode DAEs focuses on these crucial issues 6.
Thanks to the experimental coupling of Dymola (Dassault Systèmes'
commercial implementation of the Modelica language) with our IsamDAE
prototype (https://
4.2 Dynamical Systems Verification
In addition to welldefined operational semantics for hybrid systems, one often needs to provide formal guarantees about the behavior of some critical components of the system, or at least its main underlying logic. To do so, we are actively developing new techniques to automatically verify whether a hybrid system complies with its specifications, and/or to infer automatically the envelope within which the system behaves safely. The approaches we developed have been already successfully used to formally verify the intricate logic of the ACAS X, a midair collision avoidance system that advises the pilot to go upward or downward to avoid a nearby airplane which requires mixing the continuous motion of the aircraft with the discrete decisions to resolve the potential conflict 54. This challenging example is nothing but an instance of the kind of systems we are targeting: autonomous smart systems that are designed to perform sophisticated tasks with an internal tricky logic. What is even more interesting perhaps is that such techniques can be often "reverted" to actually synthesize missing components so that some property holds, effectively helping the design of such complex systems.
5 Social and environmental responsibility
5.1 Impact of research results
The expected impact of our research is to allow both better designs and better exploitation of energy production units and distribution networks, enabling largescale energy savings. At least, this is what we can observe in the context of the FUI ModeliScale collaborative project, which is focused on electric grids, urban heat networks and building thermal modeling.
The rationale is as follows: system engineering models are meant to assess the correctness, safety and optimality of a system under design. However, system models are still useful after the system has been put in operation. This is especially true in the energy sector, where systems have an extremely long lifespan (for instance, more than 50 years for some nuclear power plants) and are upgraded periodically, to integrate new technologies. Exactly like in software engineering, where a software and its model coevolve throughout the lifespan of the software, a coevolution of the system and its physical models has to be maintained. This is required in order to maintan the safety of the system, but also its optimality.
Moreover, physical models can be instrumental to the optimal exploitation of a system. A typical example are modelpredictive control (MPC) techniques, where the model is simulated, during the exploitation of the system, in order to predict system trajectories up to a boundedtime horizon. Optimal control inputs can then be computed by mathematical programming methods, possibly using multiple simulation results. This has been proved to be a practical solution 50, whenever classical optimal control methods are ineffective, for instance, when the system is nonlinear or discontinuous. However, this requires the generation of highperformance simulation code, capable of simulating a system much faster than realtime.
The structural analysis techniques implemented in IsamDAE 8 generate a conditional block dependency graph, that can be used to generate highperformance simulation code : static code can be generated for each block of equations, and a scheduling of these blocks can be computed, at runtime, at each mode switching, thanks to an inexpensive topological sort algorithm. Contrarily to other approaches (such as 49), no structural analysis, blocktrangular decompositions, or automatic differentiation has to be performed at runtime.
6 Highlights of the year
The main highlights for 2020 are the two following achievements:
 The publication of 6, a 47pages long journal paper, detailing a comprehensive theory of multimode DAE systems. A particular attention is paid to the structural analysis of (possibly impulsive) mode switchings.
 The development of the IsamDAE software (https://
team. ) became in 2020 a major undertaking for the Hycomes team. This software implements structural analysis algorithms presented in 8, 17. The development team has been strenghtened in October 2020 with the hiring of Bertrand Provot, a software engineer in charge of the consolidation, testing and documentation of the software.inria. fr/ hycomes/ software/ isamdae/
7 New software and platforms
7.1 New software
7.1.1 Demodocos
 Name: Demodocos (Examples to Generic Scenario Models Generator)
 Keywords: Surgical process modelling, Net synthesis, Process mining

Scientific Description:
Demodocos is used to construct a Test and Flip net (Petri net variant) from a collection of instances of a given procedure. The tool takes as input either standard XES log files (a standard XML file format for process mining tools) or a specific XML file format for surgical applications. The result is a Test and Flip net and its marking graph. The tool can also build a #SEVEN scenario for integration into a virtual reality environment. The scenario obtained corresponds to the generalization of the input instances, namely the instances synthesis enriched with new behaviors respecting the relations of causality, conflicts and competition observed.
Demodocos is a synthesis tool implementing a linear algebraic polynomial time algorithm. Computations are done in the Z/2Z ring. Test and Flip nets extend Elementary Net Systems by allowing test to zero, test to one and flip arcs. The effect of flip arcs is to complement the marking of the place. While the net synthesis problem has been proved to be NP hard for Elementary Net Systems, thanks to flip arcs, the synthesis of Test and Flip nets can be done in polynomial time. Test and flip nets have the required expressivity to give concise and accurate representations of surgical processes (models of types of surgical operations). Test and Flip nets can express causality and conflict relations. The tool takes as input either standard XES log files (a standard XML file format for process mining tools) or a specific XML file format for surgical applications. The output is a Test and Flip net, solution of the following synthesis problem: Given a finite input language (log file), compute a net, which language is the least language in the class of Test and Flip net languages, containing the input language.

Functional Description:
The tool Demodocos allows to build a generic model for a given procedure from some examples of instances of this procedure. The generated model can take the form of a graph, a Test 'n Flip net or a SEVEN scenario (intended for integration into a virtual reality environment).
The classic use of the tool is to apply the summary operation to a set of files describing instances of the target procedure. Several file formats are supported, including the standard XES format for log events. As output, several files are generated. These files represent the generic procedure in different forms, responding to varied uses.
This application is of limited interest in the case of an isolated use, out of context and without a specific objective when using the model generated. It was developed as part of a research project focusing in particular on surgical procedures, and requiring the generation of a generic model for integration into a virtual reality training environment. It is also quite possible to apply the same method in another context.
 Publication: hal00872284
 Authors: Benoît Caillaud, Aurélien Lamercerie
 Contacts: Benoît Caillaud, Aurélien Lamercerie
 Participants: Aurélien Lamercerie, Benoît Caillaud
7.1.2 IsamDAE
 Name: Implicit Structural Analysis of Multimode DAE systems
 Keywords: Structural analysis, Differential algebraic equations, Multimode, Scheduling

Scientific Description:
Modeling languages and tools based on Differential Algebraic Equations (DAE) bring several specific issues that do not exist with modeling languages based on Ordinary Differential Equations. The main problem is the determination of the differentiation index and latent equations. Prior to generating simulation code and calling solvers, the compilation of a model requires a structural analysis step, which reduces the differentiation index to a level acceptable by numerical solvers.
The Modelica language, among others, allows hybrid models with multiple modes, modedependent dynamics and statedependent mode switching. These Multimode DAE (mDAE) systems are much harder to deal with. The main difficulties are (i) the combinatorial explosion of the number of modes, and (ii) the correct handling of mode switchings.
The aim of the software is on the first issue, namely: How can one perform a structural analysis of an mDAE in all possible modes, without enumerating these modes? A structural analysis algorithm for mDAE systems has been designed and implemented, based on an implicit representation of the varying structure of an mDAE. It generalizes J. Pryce's Sigmamethod to the multimode case and uses Binary Decision Diagrams (BDD) to represent the modedependent structure of an mDAE. The algorithm determines, as a function of the mode, the set of latent equations, the leading variables and the state vector. This is then used to compute a modedependent blocktriangular decomposition of the system, that can be used to generate simulation code with a modedependent scheduling of the blocks of equations.

Functional Description:
IsamDAE (Implicit Structural Analysis of Multimode DAE systems) is a software library implementing new structural analysis algorithms for multimode DAE systems, based on an implicit representation of incidence graphs, matchings between equations and variables, and block decompositions. The input of the software is a variable dimension multimode DAE system consisting in a set of guarded equations and guarded variable declarations. It computes a modedependent structural index reduction of the multimode system and produces a modedependent graph for the scheduling of blocks of equations. It also computes the differentiation order of the latent equations and leading variables, as functions of the modes.
IsamDAE is coded in OCaml, and uses (at least partially) the following packages: * MLBDD by Arlen Cox, * Menhir by François Pottier and Yann RégisGianas, * GuaCaml and Snowflake by Joan Thibault, * Pprint by François Pottier, * XMLLight by Nicolas Cannasse and Jacques Garrigue.

Release Contributions:
Versions 0.3a to 0.3d (released between Mar. and Dec. 2020):
* Performance improvements: connection with the Snowflake package by Joan Thibault, based on his PhD works on RBTF (Reduced BlockTriangular Forms). The order in which variables and equations are declared in the model, and the way these declarations are grouped, has way less impact on performances when RBTF is active (now the default behaviour of IsamDAE). * New data structures were implemented in order to correct the inputs of equations blocks in the XML, text and graph outputs. Before this fix, when two or several derivatives of the same variable appeared in the same equation (as in the simple equation `der(x) + x = 0`), the lowerorder derivatives of this variable were ignored. * New examples: several examples have been added, in mechanics, electrodynamics and hydraulics. * Documentation: a comprehensive User and Developer manual is made available.
 News of the Year: It has been possible to perform the structural analysis of systems with more than 750 equations and 10 to the power 23 modes, therefore demonstrating the scalability of the method.

URL:
https://
team. inria. fr/ hycomes/ software/ isamdae/  Publication: hal02476541
 Authors: Benoît Caillaud, Mathias Malandain, Joan Thibault
 Contacts: Benoît Caillaud, Mathias Malandain, Joan Thibault
8 New results
8.1 Mathematical Foundations of Physical Systems Modeling Languages
Participants: Albert Benveniste, Benoît Caillaud, Mathias Malandain.
Modern modeling languages for general physical systems, such as Modelica or Simscape, rely on Differential Algebraic Equations (DAE), i.e., constraints of the form $f(\dot{x},x,u)=0$, when only firstorder derivatives are considered. This facilitates modeling from first principles of the physics. This year we completed and published in the Annual Reviews in Control 6 the development of the mathematical theory needed to sound, on solid mathematical bases, the design of compilers and tools for DAE based physical modeling languages.
Unlike Ordinary Differential Equations (ODE, of the form $\dot{x}=g(x,u)$), DAE exhibit subtle issues because of the notion of differentiation index and related latent equations—ODE are DAE of index zero for which no latent equation needs to be considered. Prior to generating execution code and calling solvers, the compilation of such languages requires a nontrivial structural analysis step that reduces the differentiation index to a level acceptable by DAE solvers.
Multimode DAE systems, having multiple modes with modedependent dynamics and statedependent mode switching, are much harder to deal with. The main difficulty is the handling of the events of mode change. Unfortunately, the large literature devoted to the numerical analysis of DAEs does not cover the multimode case, typically saying nothing about mode changes. This lack of foundations causes numerous difficulties to the existing modeling tools. Some models are well handled, others are not, with no clear boundary between the two classes. Basically, no tool exists that performs a correct structural analysis taking multiple modes and mode changes into account.
In our work, we developed a comprehensive mathematical approach supporting compilation and code generation for this class of languages. Its core is the structural analysis of multimode DAE systems, taking both multiple modes and mode changes into account. As a byproduct of this structural analysis, we propose well sound criteria for accepting or rejecting models at compile time.
For our mathematical development, we rely on nonstandard analysis, which allows us to cast hybrid systems dynamics to discrete time dynamics with infinitesimal step size, thus providing a uniform framework for handling both continuous dynamics and mode change events.
8.2 An implicit structural analysis method for multimode DAE systems
Participants: Albert Benveniste, Benoît Caillaud, Mathias Malandain, Joan Thibault.
Modeling languages and tools based on Differential Algebraic Equations (DAE) bring several specific issues that do not exist with modeling languages based on Ordinary Differential Equations. The main problem is the determination of the differentiation index and latent equations. Prior to generating simulation code and calling solvers, the compilation of a model requires a structural analysis step, which reduces the differentiation index to a level acceptable by numerical solvers.
The Modelica language, among others, allows hybrid models with multiple modes, modedependent dynamics and statedependent mode switching. These multimode DAE (mDAE) systems are much harder to deal with. The main difficulties are (i) the combinatorial explosion of the number of modes, and (ii) the correct handling of mode switchings.
The focus of the paper 34 is on the first issue, namely: How can one perform a structural analysis of an mDAE in all possible modes, without enumerating these modes? A structural analysis algorithm for mDAE systems is presented, based on an implicit representation of the varying structure of an mDAE. It generalizes J. Pryce's $\Sigma $method 65 to the multimode case and uses Binary Decision Diagrams (BDD) to represent the modedependent structure of an mDAE. The algorithm determines, as a function of the mode, the set of latent equations, the leading variables and the state vector. This is then used to compute a modedependent blocktriangular decomposition of the system, that can be used to generate simulation code with a modedependent scheduling of the blocks of equations.
This method has been implemented in the IsamDAE software. This has allowed the Hycomes team to evaluate the performance and scalability of the method on several examples. In particular, it has been possible to perform the structural analysis of systems with more than 2300 equations and ${10}^{77}$ modes.
8.3 Ordered Functional Decision Diagrams: A Functional Semantics For Binary Decision Diagrams
Participants: Joan Thibault, Khalil Ghorbal.
We introduce a novel framework, termed λDD, that revisits Binary Decision Diagrams from a purely functional point of view. The framework allows to classify the already existing variants, including the most recent ones like ChainDD and ESRBDD, as implementations of a special class of ordered models. We enumerate, in a principled way, all the models of this class and isolate its most expressive model. This new model, termed λDDONUCX, is suitable for both dense and sparse Boolean functions, and is moreover invariant by negation. The canonicity of λDDONUCX is formally verified using the Coq proof assistant. We furthermore give bounds on the size of the different diagrams: the potential gain achieved by more expressive models can be at most linear in the number of variables n.
8.4 Functional Decision Diagrams: A Unifying Data Structure For Binary Decision Diagrams
Participants: Joan Thibault, Khalil Ghorbal.
We present concise and canonical representations of Boolean functions akin to Binary Decision Diagrams, a versatile data structure with several applications beyond computer science. Our approach is functional: we encode the process that constructs the Boolean function of interest starting from the constant function zero (or False). This point of view makes the data structure more resilient to variable ordering, a wellknown problem in standard representations. The experiments on both dense and sparse formulas are very encouraging and show not only a better compression rate of the final representation than all existing related variants but also a lower memory peak.
8.5 Characterizing Positively Invariant Sets: Inductive and Topological Methods
Participants: Khalil Ghorbal.
Set positive invariance is an important concept in the theory of dynamical systems and one which also has practical applications in areas of computer science, such as formal verification, as well as in control theory. Great progress has been made in understanding positively invariant sets in continuous dynamical systems and powerful computational tools have been developed for reasoning about them; however, many of the insights from recent developments in this area have largely remained folklore and are not elaborated in existing literature. This article contributes an explicit development of modern methods for checking positively invariant sets of ordinary differential equations and describes two possible characterizations of positive invariants: one based on the real induction principle, and a novel alternative based on topological notions. The two characterizations, while in a certain sense equivalent, lead to two different decision procedures for checking whether a given semialgebraic set is positively invariant under the flow of a system of polynomial ordinary differential equations.
8.6 Characterizing Qmatrices
Participants: Khalil Ghorbal, Christelle Kozaily.
We show that the existence of solutions for linear complementarity problems amounts to a covering of the entire space by a set of finite cones defined by the involved vectors as well as the standard basis. We give several full characterizations for the case $n=2$ and detail how these could be used to derive several necessary conditions for higher dimensions. The local existence of solutions is also investigated. It is shown that the positivity condition on the determinant, or equivalently, the orientation of the vectors forming the complementarity cones cannot be captured purely structurally.
9 Bilateral contracts and grants with industry
 Glose (2018–2021) In the context of a framework agreement between Safran Tech. of the Safran aeronautic group and Inria, the Hycomes team, jointly with the KAIROS and DIVERSE teams, contributes to the Glose research grant funded by Safran. The contributions of the Hycomes team are structural analysis techniques for multimode DAE models resulting from the coupling of quasistatic models, expressed as nonlinear equations, with dynamical systems, in the form of systems of ordinary differential equations. The multimode features of the model come from the dynamic changes of the system structures, possibly resulting from changes of mode of operation, or mechanical failure. Current work of the Hycomes team focuses on the definition of a component model, encapsulating multimode DAE systems, and on modular structural analysis methods, capable of characterizing, from a structural point of view only, the possible environments in which a component model may be correctly instantiated.
10 Partnerships and cooperations
10.1 International research visitors
The visit of Inigo Incer Romeo, PhD student at U. Berkeley, initially planned in the Summer 2020 had to be postponed to 2021. This visit is supported by a Chateaubriand Fellowship grant of the French Ministry of Foreign Affairs. The topics of the visit is on the use of Contractbased Reasoning to support the design of CPS systems.
10.2 National initiatives
10.2.1 Inria Project Lab (IPL): ModeliScale, Languages and Compilation for CyberPhysical System Design
The project gathers researchers from three Inria teams (Hycomes, Parkas and Tripop), and from three other research labs in Paris area (ENSTA ParisTech, L2SCNRS and LIX, École Polytechnique).
The main objective of ModeliScale is to advance modeling technologies (languages, compiletime analyses, simulation techniques) for CPS combining physical interactions, communication layers and software components. We believe that mastering CPS comprising thousands to millions of components requires radical changes of paradigms. For instance, modeling techniques must be revised, especially when physics is involved. Modeling languages must be enhanced to cope with larger models. This can only be done by combining new compilation techniques (to master the structural complexity of models) with new mathematical tools (new numerical methods, in particular).
ModeliScale gathers a broad scope of experts in programming language design and compilation (reactive synchronous programming), numerical solvers (nonsmooth dynamical systems) and hybrid systems modeling and analysis (guaranteed simulation, verification). The research program is carried out in close cooperation with the Modelica community as well as industrial partners, namely, Dassault Systèmes as a Modelica/FMI tool vendor, and EDF and Engie as end users.
In 2020, two general meetings have been organized by visioconference, with presentations of the partners on new results related to hybrid systems modeling and verification.
Two PhDs are funded by the ModeliScale IPL. Both started in October 2018:
 Christelle Kozaily has started a PhD, under the supervision of Vincent Acary (TRIPOP team at Inria Grenoble), Benoît Caillaud, Khalil Ghorbal on the structural and numerical analysis of nonsmooth DAE systems. She is located in the Hycomes team at Inria Rennes.
 Ismail LahkimBennani has started a PhD under the supervision of Goran Frehse (ENSTA ParisTech.) and Marc Pouzet (PARKAS team, INRIA/ENS Paris). His PhD topic is on random testing of hybrid systems, using techniques inspired by QuickCheck 39.
10.2.2 FUI ModeliScale: Scalable Modeling and Simulation of Large CyberPhysical Systems
Participants: Albert Benveniste, Benoît Caillaud, Mathias Malandain, Bertrand Provot.
FUI ModeliScale is a French national collaborative project coordinated by Dassault Systèmes. The partners of this project are: EDF and Engie as main industrial users; DPS, Eurobios and PhiMeca are SME providing mathematical modeling expertise; CEA INES (Chambéry) and Inria are the academic partners. The project started January 2018, for a maximal duration of 42 months. Three Inria teams are contributing to the project : Hycomes, Parkas (Inria Paris / ENS) and Tripop (Inria Grenoble / LJK).
The focus of the project is on the scalable analysis, compilation and simulation of large Modelica models. The main contributions expected from Inria are:
 A novel structural analysis algorithm for multimode DAE systems, capable of handling large systems of guarded equations, that do not depend on the enumeration of a possibly exponential number of modes.
 The partitioning and highperformance distributed cosimulation of large Modelica models, based on the results of the structural analysis.
In 2020, the effort has been put on the first objective, and in
particular the improvement of the scalability of the algorithms
implemented in the IsamDAE software
(https://
A coupling of IsamDAE with Dymola (Dassault Système's commercial implementation of the Modelica language) has been implemented by Dassault Systèmes AB (Lund, Sweden), and is currently under test at the time of writing of this activity report.
11 Dissemination
11.1 Promoting scientific activities
11.1.1 Scientific events: organisation
General chair, scientific chair
Khalil Ghorbal was the coChair of the NSAD Workshop (satellite of the SPLASH 2020 Event). https://
Abstract domains are a key notion in Abstract Interpretation theory and practice. They embed the semantic choices, datastructures and algorithmic aspects, and implementation decisions. The Abstract Interpretation framework provides constructive and systematic formal methods to design, compose, compare, study, prove, and apply abstract domains. Many abstract domains have been designed so far: numerical domains (intervals, congruences, polyhedra, polynomials, etc.), symbolic domains (shape domains, trees, etc.), but also domain operators (products, powersets, completions, etc.), and have been applied to several kinds of static analyses (safety, termination, probability, etc.) on a variety of systems (hardware, software, neural networks, etc.). The goal of NSAD workshop is to discuss work in progress, recent advances, novel ideas, experiences in the theory, practice, application, implementation, and experimentation related to abstract domains and/or their combination. This year’s edition in particular welcomes abstract domains related and/or applied to analyzing neural networks, dynamical and hybrid systems.
11.1.2 Scientific events: selection
Member of the conference program committees
Benoît Caillaud has served on the program committee of FDL'20, a workshop on the domainspecific languages. The workshop took place with both physical (in Kiel, Germany) and virtual attendance (by visioconference).
11.1.3 Journal
Reviewer  reviewing activities
 Benoît Caillaud has reviewed papers for ACMTECS and IEEETAC;
 Khalil Ghorbal served as a reviewer for IEEETAC, IEEETECS, LITES, ICALP, Automatica;
 Mathias Malandain served as a reviewer for the Asian Modelica Conference 2020;
 Albert Benveniste served as a reviewer for the journals Transactions on Software Engineering, Discrete Event Dynamic Systems, Automatica and the American Control Conference.
11.1.4 Invited talks
 Benoît Caillaud has given a talk on switched DAE systems at the students seminar of the Department of Applied Mathematics at the ENS ParisSaclay,
 Khalil Ghorbal was invited to give a talk at the PolySys Seminar (LIP6, Symbolic Computation),
 Khalil Ghorbal was invited to give a talk at the University of Perpignan (Computer Science, Mathematics and Physics departments),
 Khalil Ghorbal was invited to give a talk at the RWTH Aachen University (Computer Science and control departments).
11.1.5 Scientific expertise
 Albert Benveniste was chair of the Scientific Council of Orange Labs. His term terminated by end of february 2020.
 Albert Benveniste is member of the Scientific Council of Safran. In the period January to March 2020, together with Nikos Paragios (also member of the council), he prepared a report on the impacts and opportunities for AI in Safran, and the way forward, both internally and with the ecosystem.
 Albert Benveniste participated to the activities of the Academy of technologies (Pôle Numérique) since march 2020. More specifically, he started a Working Group on Crisis Management methods and tools targeting the COVID pandemia. The moto is: modeling should be extended beyond epidemiology. In 2020, long interviews with demos were held with DassaultSystèmes, Thales, IBM, and the startup Causality Link. The report should be issued early in 2021.
11.1.6 Research administration
Benoît Caillaud is head of the Programming Languages and Software Engineering department of IRISA (UMR 6074). Part of his duties has been the preparation of the evaluation of IRISA, planned March 2021.
11.2 Teaching  Supervision  Juries
11.2.1 Teaching
 Master : Khalil Ghorbal, Category Theory, Monads, and Computation, M2, (enseignant principal), 30h EqTD, ENS Rennes, France
 Master : Khalil Ghorbal, Modeling Physics with DifferentialAlgebraic Equations, M2, (enseignant principal), 25h EqTD, Ecole Polytechnique, Palaiseau, France
 Licence : Mathias Malandain taught linear algebra and integration in multivariable calculus to 1st and 2ndyear students at the University of Rennes 1 (36 hours).
11.2.2 Supervision
 PhD: Christelle Kozaily, Structural analysis of nonsmooth dynamical systems, university of Rennes 1, cosupervised by Vincent Acary (Tripop 5 team at Inria Grenoble), Benoît Caillaud and Khalil Ghorbal, started October 2018.
 PhD: Aurélien Lamercerie, Formal analysis of cyberphysical systems requirements expressed in natural language, university of Rennes 1, cosupervised by par Benoît Caillaud et Annie Forêt (SemLIS 6 team of IRISA), started December 2017. His PhD defence is planned April 2021.
 PhD: Joan Thibault, Structural Analysis Techniques for Binary Decision Diagrams, university of Rennes 1, cosupervised by Benoît Caillaud and Khalil Ghorbal.
 Internship M1: Julien Duron, on Graph Combinatorial Optimization using Structural Analysis methods for Boolean Functions, ENS Rennes, cosupervised by Joan Thibault and Khalil Ghorbal.
12 Scientific production
12.1 Major publications
 1 articleBuilding a Hybrid Systems Modeler on Synchronous Languages PrinciplesProceedings of the IEEE1069September 2018, 15681592
 2 articleNonstandard semantics of hybrid systems modelersJournal of Computer and System Sciences783This work was supported by the SYNCHRONICS large scale initiative of INRIA2012, 877910
 3 articleContracts for System DesignFoundations and Trends in Electronic Design Automation12232018, 124400
 4 articleA Formally Verified Hybrid System for Safe Advisories in the NextGeneration Airborne Collision Avoidance SystemInternational Journal on Software Tools for Technology Transfer196November 2017, 717741
 5 articleOperational Models for PiecewiseSmooth SystemsACM Transactions on Embedded Computing Systems (TECS)165sOctober 2017, 185:1185:19
12.2 Publications of the year
International journals
 6 article The mathematical foundations of physical systems modeling languages Annual Reviews in Control December 2020
 7 articleUnveiling the implicit knowledge, one scenario at a timeVisual Computer2020, 112
International peerreviewed conferences
 8 inproceedingsImplicit structural analysis of multimode DAE systemsHSCC 2020  23rd ACM International Conference on Hybrid Systems: Computation and ControlSydney New South Wales Australia, FranceApril 2020, 111
 9 inproceedingsAn Algebra of Deterministic Propositional Acceptance Automata (DPAA)FDL 2020  Forum on specification & Design LanguagesKiel, GermanySeptember 2020, 18
Conferences without proceedings
 10 inproceedingsARES : un extracteur d'exigences pour la modélisation de systèmesEGC 2020  Extraction et Gestion des Connaissances (Atelier  Fouille de Textes  Text Mine)Bruxelles, BelgiumJanuary 2020, 14
 11 inproceedingsTransduction sémantique pour la modélisation de systèmePFIA 2020  PlateForme de l'Intelligence Artificielle (PFIA), rencontres RJCIAAngers, FranceJune 2020, 16
Reports & preprints
 12 reportStructural Analysis of Multimode DAE Systems: summary of resultsInria Rennes – Bretagne AtlantiqueJanuary 2021, 27
 13 reportThe Mathematical Foundations of Physical Systems Modeling LanguagesInriaApril 2020, 112
 14 reportMixed NondeterministicProbabilistic InterfacesInria Rennes Bretagne Atlantique; Aalborg University; Université de Toulouse 3 Paul SabatierNovember 2020, 40
 15 report Implicit Structural Analysis of Multimode DAE Systems Inria Rennes  Bretagne Atlantique; IRISA, Université de Rennes February 2020
 16 report Ordered Functional Decision Diagrams: A Functional Semantic For Binary Decision Diagrams Inria 2020
Other scientific publications
 17 miscDemo: IsamDAE, an Implicit Structural Analysis Tool for Multimode DAE SystemsSydney, AustraliaApril 2020,
12.3 Cited publications
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 19 book Principles of Model Checking MIT Press, Cambridge 2008
 20 articleBuilding a Hybrid Systems Modeler on Synchronous Languages PrinciplesProceedings of the IEEE1069September 2018, 15681592
 21 misc A TypeBased Analysis of Causality Loops In Hybrid Systems Modelers Deliverable D3.1_1 v 1.0 of the Sys2soft collaborative project ''Physics Aware Software'' December 2013
 22 misc Semantics of multimode DAE systems Deliverable D.4.1.1 of the ITEA2 Modrio collaborative project August 2013
 23 inproceedings Multiple Viewpoint ContractBased Specification and Design Proceedings of the Software Technology Concertation on Formal Methods for Components and Objects (FMCO'07) 5382 Revised Lectures, Lecture Notes in Computer Science Amsterdam, The Netherlands Springer October 2008
 24 inproceedingsA typebased analysis of causality loops in hybrid modelersHSCC '14: International Conference on Hybrid Systems: Computation and ControlProceedings of the 17th international conference on Hybrid systems: computation and control (HSCC '14)Berlin, GermanyACM PressApril 2014, 13
 25 inproceedingsA Compositional Approach on Modal Specifications for Timed Systems11th International Conference on Formal Engineering Methods (ICFEM'09)5885LNCSRio de Janeiro, BrazilSpringerDecember 2009, 679697URL: http://hal.inria.fr/inria00424356/en
 26 articleModal eventclock specifications for timed componentbased designScience of Computer Programming2011, URL: http://dx.doi.org/10.1016/j.scico.2011.01.007
 27 inproceedingsRefinement and Consistency of Timed Modal Specifications3rd International Conference on Language and Automata Theory and Applications (LATA'09)5457LNCSTarragona, SpainSpringerApril 2009, 152163URL: http://hal.inria.fr/inria00424283/en
 28 inproceedingsA proposal for realtime interfaces in SPEEDSDesign, Automation and Test in Europe (DATE'10)IEEE2010, 441446
 29 articleModelling of Complex Systems: Systems as Dataflow MachinesFundam. Inform.9122009, 251274
 30 phdthesis Un cadre formel pour l'étude des systèmes industriels complexes: un exemple basé sur l'infrastructure de l'UMTS Ecole Polytechnique 2006
 31 articleGraphical Versus Logical SpecificationsTheor. Comput. Sci.10611992, 320
 32 inproceedingsCompositional design methodology with constraint Markov chainsQEST 2010Williamsburg, Virginia, United StatesSeptember 2010, URL: http://hal.inria.fr/inria00591578/en
 33 articleConstraint Markov ChainsTheoretical Computer Science41234May 2011, 43734404URL: http://hal.inria.fr/hal00654003/en
 34 inproceedings Implicit Structural Analysis of Multimode DAE Systems 23rd ACM International Conference on Hybrid Systems: Computation and Control (HSCC 2020) to appear Sydney, Australia April 2020
 35 articleThe index of general nonlinear DAEsNumerische Mathematik722dec 1995, 173196URL: http://dx.doi.org/10.1007/s002110050165
 36 phdthesisA Framework for Compositional Design and Analysis of SystemsEECS Department, University of California, BerkeleyDec 2007, URL: http://www.eecs.berkeley.edu/Pubs/TechRpts/2007/EECS2007174.html
 37 inproceedingsResource InterfacesEMSOFT2003, 117133
 38 inproceedingsCharacterization of Temporal Property ClassesICALP1992, 474486
 39 inproceedingsQuickCheck: a lightweight tool for random testing of Haskell programsProceedings of the Fifth ACM SIGPLAN International Conference on Functional Programming (ICFP '00), Montreal, Canada, September 1821, 2000.2000, 268279URL: https://doi.org/10.1145/351240.351266
 40 book Model Checking MIT Press 1999
 41 book N. Cutland Nonstandard analysis and its applications Cambridge Univ. Press 1988
 42 inproceedingsECDAR: An Environment for Compositional Design and Analysis of Real Time SystemsAutomated Technology for Verification and Analysis  8th International Symposium, ATVA 2010, Singapore, September 2124, 2010. Proceedings2010, 365370
 43 inproceedingsTimed I/O automata: a complete specification theory for realtime systemsProceedings of the 13th ACM International Conference on Hybrid Systems: Computation and Control, HSCC 2010, Stockholm, Sweden, April 1215, 20102010, 91100
 44 inproceedingsAbstract Probabilistic AutomataVMCAI2011, 324339
 45 book Analyse non standard Hermann 1989
 46 book Trace Theory for Automatic Hierarchical Verification of SpeedIndependent Circuits ACM Distinguished Dissertations MIT Press 1989
 47 articleTheoretical improvements in algorithmic efficiency for network flow problemsJournal of the ACM1921972, 248264URL: http://dx.doi.org/10.1145/321694.321699
 48 inproceedings Modelica extensions for MultiMode DAE Systems Proceedings of the 10th International Modelica Conference, March 1012, 2014, Lund, Sweden Linköping University Electronic Press mar 2014
 49 inproceedings Modiadynamic modeling and simulation with julia Juliacon'18 University College London, UK August 2018
 50 inproceedingsSurvey of industrial applications of embedded model predictive control2016 European Control Conference (ECC)2016, 601601
 51 inproceedingsA new approach to the maximum flow problemProceedings of the eighteenth annual ACM symposium on Theory of computing (STOC'86)1986, URL: http://dx.doi.org/10.1145/12130.12144
 52 miscIEEE Standard VHDL Analog and MixedSignal Extensions, Std 1076.119991999, URL: http://dx.doi.org/10.1109/IEEESTD.1999.90578
 53 inproceedingsModeling Time in Hybrid Systems: How Fast Is ``Instantaneous''?IJCAI1995, 17731781
 54 inproceedingsFormal verification of ACAS X, an industrial airborne collision avoidance system2015 International Conference on Embedded Software, EMSOFT 2015, Amsterdam, Netherlands, October 49, 20152015, 127136
 55 articleProving the Correctness of Multiprocess ProgramsIEEE Trans. Software Eng.321977, 125143
 56 inproceedingsOn Modal Refinement and ConsistencyProc. of the 18th International Conference on Concurrency Theory (CONCUR'07)Springer2007, 105119
 57 inproceedingsA Modal Process LogicProceedings of the Third Annual Symposium on Logic in Computer Science (LICS'88)IEEE1988, 203210
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 59 inproceedingsInput/Output Automata: Basic, Timed, Hybrid, Probabilistic and DynamicCONCUR2003, 187188
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 64 articleThe consistent initialization of differentialalgebraic systemsSIAM J. Sci. Stat. Comput.921988, 213231
 65 articleA Simple Structural Analysis Method for DAEsBIT Numerical Mathematics412March 2001, 364394URL: http://dx.doi.org/10.1023/a:1021998624799
 66 articleA Modal Interface Theory for Componentbased DesignFundamenta Informaticae108122011, 119149URL: http://hal.inria.fr/inria00554283/en
 67 book NonStandard Analysis ISBN 0691044902 Princeton Landmarks in Mathematics 1996
 68 articleIndustry needs and research directions in requirements engineering for embedded systemsRequirements Engineering172012, 5778URL: http://link.springer.com/article/10.1007/s007660110144x
 69 inproceedingsGame Models for Open SystemsVerification: Theory and Practice2772Lecture Notes in Computer ScienceSpringer2003, 269289
 70 inproceedingsInterface automataProc. of the 9th ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE'01)ACM Press2001, 109120
 71 inproceedings Interfacebased design In Engineering Theories of Software Intensive Systems, proceedings of the Marktoberdorf Summer School Kluwer 2004
 72 inproceedingsTimed InterfacesProc. of the 2nd International Workshop on Embedded Software (EMSOFT'02)2491Lecture Notes in Computer ScienceSpringer2002, 108122