Computer-algebra systems have been advertised for decades as software
for “doing mathematics by computer” . For
instance, computer-algebra libraries can uniformly generate a corpus
of mathematical properties about special functions so as to display
them on an interactive website. This was recently shown by the
computer-algebra component of the
team . Such
an automated generation significantly increases the reliability of the
mathematical corpus, in comparison to the content of existing static
authoritative handbooks. The importance of the validity of these
contents can be measured by the very wide audience that such handbooks
have had, to the point that a book
like remains one of the most cited
mathematical publications ever and has motivated the 10-year-long
project of writing its
successor .
However, can the mathematics produced “by computer” be considered as
*true* mathematics? More specifically, whereas it is nowadays
well established that the computer helps in discovering and observing
new mathematical phenomenons, can the mathematical statements produced
with the aid of the computer and the mathematical results computed by
it be accepted as valid mathematics, that is, as having the status of
mathematical *proofs*?
Beyond the reported weaknesses or
controversial design choices of mainstream computer-algebra systems,
the issue is more of an epistemological nature. It will not find its
solution even in the advent of the ultimate computer-algebra system:
the social process of peer-reviewing just falls short of evaluating
the results produced by computers, as reported by
Th. Hales after the publication of his proof of
the Kepler Conjecture about sphere packing.

A natural answer to this deadlock is to move to an alternative kind of
mathematical software and to use a proof assistant to check the
correctness of the desired properties or formulas. The recent success
of large-scale formalization projects, like the Four-Color Theorem of
graph theory , the above-mentioned Kepler
Conjecture , and, very recently, the Odd Order
Theorem of group theory

The Dynamic Dictionary of Mathematical Functions

The formal-proofs component of the team emanates from another project
of the MSR–Inria Joint Centre, namely the Mathematical Components
project (MathComp)

The present team takes benefit from these recent advances to explore the formal certification of the results collected in DDMF. The aim of this project is to concentrate the formalization effort on this delimited area, building on DDMF and the Algolib library, as well as on the Coq system and on the libraries developed by MathComp.

The following few opinions on computer algebra are, we believe, typical of computer-algebra users' doubts and difficulties when using computer-algebra systems:

Fredrik Johansson, expert in the multi-precision numerical evaluation
of special functions and in fast computer-algebra algorithms, writes
on his blog : “Mathematica is great for
cross-checking numerical values, but it's not unusual to run into
bugs, so *triple checking is a good habit*.” One answer in the
discussion is: “We can claim that Mathematica has [...] *an
impossible to understand semantics*: If Mathematica's output is
wrong then change the input. If you don't like the answer, change the
question. That seems to be the philosophy behind.”

Jacques Carette, former head of the maths group at Maplesoft, about a
bug when asking Maple to take the limit
`limit(f(n) * exp(-n), n = infinity)` for an undetermined
function `f`: “The problem is that there is an *implicit
assumption in the implementation* that unknown functions do not
`grow too fast'.”

As explained by the expert views above, complaints by computer-algebra users are often due to their misunderstanding of what a computer-algebra systems is, namely a purely syntactic tool for calculations, that the user must complement with a semantics. Still, robustness and consistency of computer-algebra systems are not ensured as of today, and, whatever Zeilberger may provocatively say in his opinion 94 , a firmer logical foundation is necessary. Indeed, the fact is that many “bugs” in a computer-algebra system cannot be fixed by just the usual debugging method of tracking down the faulty lines in the code. It is sort of “by design”: assumptions that too often remain implicit are really needed by the design of symbolic algorithms and cannot easily be expressed in the programming languages used in computer algebra A similar certification initiative has already been undertaken in the domain of numerical computing, in a successful manner , . It is natural to undertake a similar approach for computer algebra.

Some of the mathematical objects that interest us are still totally untouched by formalization. When implementing them and their theory inside a proof assistant, we have to deal with the pervasive discrepancy between the published literature and the actual implementation of computer-algebra algorithms. Interestingly, this forces us to clarify our computer-algebraic view on them, and possibly make us discover holes lurking in published (human) proofs. We are therefore convinced that the close interaction of researchers from both fields, which is what we do in this team, is a strong asset.

For a concrete example, the core of Zeilberger's creative telescoping manipulates rational functions up to simplifications. In summation applications, checking that these simplifications do not hide problematic divisions by 0 is most often left to the reader. In the same vein, in the case of integrals, the published algorithms do not check the convergence of all integrals, especially in intermediate calculations. Such checks are again left to the readers. In general, we expect to revisit the existing algorithms to ensure that they are meaningful for genuine mathematical sequences or functions, and not only for algebraic idealizations.

Another big challenge in this project originates in
the scientific difference between computer algebra and formal proofs.
Computer algebra seeks speed of calculation on *concrete
instances* of algebraic data structures (polynomials, matrices,
etc). For their part, formal proofs manipulate
symbolic expressions in terms of *abstract variables*
understood to represent generic elements of algebraic data
structures. In view of this, a continuous challenge is
to develop the right, hybrid thinking attitude that is able to
effectively manage concrete and abstract values simultaneously,
alternatively computing and proving with them.

Applications in combinatorics and mathematical physics frequently involve equations of so high orders and so large sizes, that computing or even storing all their coefficients is impossible on existing computers. Making this tractable is an extraordinary challenge. The approach we believe in is to design algorithms of good, ideally quasi-optimal, complexity in order to extract precisely the required data from the equations, while avoiding the computationally intractable task of completely expanding them into an explicit representation.

Typical applications with expected high impact are the automatic discovery and proof of results in combinatorics and mathematical physics for which human proofs are currently unattainable.

The implementation of certified symbolic computations on special functions in the Coq proof assistant requires both investigating new formalization techniques and renewing the traditional computer-algebra viewpoint on these standard objects. Large mathematical objects typical of computer algebra occur during formalization, which also requires us to improve the efficiency and ergonomics of Coq. In order to feed this interdisciplinary activity with new motivating problems, we additionally pursue a research activity oriented towards experimental mathematics in application domains that involve special functions. We expect these applications to pose new algorithmic challenges to computer algebra, which in turn will deserve a formal-certification effort. Finally, DDMF is the motivation and the showcase of our progress on the certification of these computations. While striving to provide a formal guarantee of the correctness of the information it displays, we remain keen on enriching its mathematical content by developing new computer-algebra algorithms.

Our formalization effort consists in organizing a cooperation between a computer-algebra system and a proof assistant. The computer-algebra system is used to produce efficiently algebraic data, which are later processed by the proof assistant. The success of this cooperation relies on three main ingredients.

The appropriate framework for the study of efficient algorithms for
special functions is *algebraic*.
Representing algebraic theories as Coq formal libraries
takes benefit from the methodology emerging from the success of
ambitious projects like the formal proof of a major classification
result in finite-group theory (the Odd Order
Theorem) .

Yet, a number of the objects we need to formalize in the present context has never been investigated using any interactive proof assistant, despite being considered as commonplaces in computer algebra. For instance there is up to our knowledge no available formalization of the theory of non-commutative rings, of the algorithmic theory of special-functions closures, or of the asymptotic study of special functions. We expect our future formal libraries to prove broadly reusable in later formalizations of seemingly unrelated theories.

Another peculiarity of the mathematical objects we are going to manipulate
with the Coq system is their size. In order to provide a formal guarantee
on the data displayed by DDMF, two related axes of research have to be
pursued.
First, efficient algorithms dealing with these large objects have
to be programmed and run in Coq.
Recent evolutions of the Coq system to improve the efficiency of
its internal computations , make this objective
reachable. Still, how to combine the aforementioned formalization
methodology with these cutting-edge evolutions of Coq remains
one of the prospective aspects of our project.
A second need is to help users *interactively*
manipulate large expressions occurring in their conjectures, an objective
for which little has been done so far. To address this need,
we work on improving the ergonomics of the system
in two ways: first, ameliorating the reactivity of Coq in its interaction
with the user; second, designing and implementing extensions of its
interface to ease our formalization activity. We expect the outcome of
these lines of research to be useful to a wider audience, interested in
manipulating large formulas on topics possibly unrelated to special functions.

Our algorithm certifications inside Coq intends to simulate
well-identified components of our Maple packages, possibly by
reproducing them in Coq. It would however not have been judicious to
re-implement them inside Coq, since for a number of its
components, the output of the algorithm is more easily checked than
found, like for instance the solving of a linear system.
Rather, we delegate the discovery of the solutions to an
external, untrusted oracle like Maple. Trusted computations inside
Coq then formally validate the correctness of the a priori
untrusted output. More often than not, this consists in
implementing and executing normalization procedures *inside*
Coq. A challenge of this automation is to make sure they go to scale
while remaining efficient, which requires a Coq version of
non-trivial computer-algebra algorithms. A good example we expect to
work on is a non-commutative generalization of the normalization
procedure for elements of rings .

Generally speaking, we design algorithms for manipulating special functions symbolically, whether univariate or with parameters, and for extracting algorithmically any kind of algebraic and analytic information from them, notably asymptotic. Beyond this, the heart of our research is concerned with parametrised definite summations and integrations. These very expressive operations have far-ranging applications, for instance, to the computation of integral transforms (Laplace, Fourier) or to the solution of combinatorial problems expressed via integrals (coefficient extractions, diagonals). The algorithms that we design for them need to really operate on the level of linear functional systems, differential and of recurrence.

Our long-term goal is to design fast algorithms for a general method
for special-function integration (*creative telescoping*), and
make them applicable to general special-function inputs. Still, our
strategy is to proceed with simpler, more specific classes first
(rational functions, then algebraic functions, hyperexponential
functions, D-finite functions, non-D-finite functions; two variables,
then many variables); as well, we isolate analytic questions by
first considering types of integration with a more purely algebraic
flavor (constant terms, algebraic residues, diagonals of
combinatorics). In particular, we expect to extend our recent new
approach to more general classes
(algebraic with nested radicals, for example). Homologous problems
for summation will be addressed as well.

The algorithms of good complexity mentioned in the previous paragraphs naturally help us deal with applications that involve equations of high orders and large sizes.

With regard to combinatorics, we expect to advance the algorithmic classification of combinatorial classes like walks and urns. Here, the goal is to determine if enumerating generating series are rational, algebraic, or D-finite, for example. Physical problems whose modelling involves special-function integrals comprise the study of models of statistical mechanics, like the Ising model for ferro-magnetism, or questions related to Hamiltonian systems.

Number theory is another promising domain of applications. Here, we attempt an experimental approach to the automated certification of integrality of the coefficients of mirror maps for Calabi–Yau manifolds. This could also involve the discovery of new Calabi–Yau operators and the certification of the existing ones. We also plan to algorithmically discover and certify new recurrences yielding good approximants needed in irrationality proofs.

It is to be noted that in all of these application domains, we would so far use general algorithms, as was done in earlier works of ours , , . To push the scale of applications further, we plan to consider in each case the specifics of the application domain to tailor our algorithms.

In continuation of our past project of an encyclopedia at
http://

the algorithmic discussion of equations with parameters, leading to certified automatic case analysis based on arithmetic properties of the parameters;

lists of summation and integral formulas involving special functions, including validity conditions on the parameters;

guaranteed large-precision numerical evaluations.

This year, we complete a first work emblematic of the
interdisciplinary activity of the team: a computer-algebra based
formal proof of irrationality of the mathematical constant

Computer algebra manipulates symbolic representations of exact mathematical objects in a computer, in order to perform computations and operations like simplifying expressions and solving equations for “closed-form expressions”. The manipulations are often fundamentally of algebraic nature, even when the ultimate goal is analytic. The issue of efficiency is a particular one in computer algebra, owing to the extreme swell of the intermediate values during calculations.

Our view on the domain is that research on the algorithmic manipulation of special functions is anchored between two paradigms:

adopting linear differential equations as the right data structure for special functions,

designing efficient algorithms in a complexity-driven way.

It aims at four kinds of algorithmic goals:

algorithms combining functions,

functional equations solving,

multi-precision numerical evaluations,

guessing heuristics.

This interacts with three domains of research:

computer algebra, meant as the search for quasi-optimal algorithms for exact algebraic objects,

symbolic analysis/algebraic analysis;

experimental mathematics (combinatorics, mathematical physics, ...).

This view is made explicit in the present section.

Numerous special functions satisfy linear differential and/or
recurrence equations. Under a mild technical condition, the existence
of such equations induces a finiteness property that makes the main
properties of the functions decidable. We thus speak of
*D-finite functions*. For example, 60 % of the chapters in the
handbook describe D-finite functions.
In addition, the class is closed under a rich set of algebraic operations.
This makes linear functional equations just the right data structure
to encode and manipulate special functions. The power of this
representation was observed in the early
1990s , leading to the design of many
algorithms in computer algebra.
Both on the theoretical and algorithmic sides, the study of D-finite
functions shares much with neighbouring mathematical domains:
differential algebra,
D-module theory,
differential Galois theory,
well as their counterparts for recurrence equations.

Differential/recurrence equations that define special functions can be
recombined to define: additions and
products of special functions; compositions of special functions;
integrals and sums involving special functions. Zeilberger's fast
algorithm for obtaining recurrences satisfied by parametrised binomial
sums was developed in the early 1990s already .
It is the basis of all modern definite summation and integration
algorithms. The theory was made fully rigorous and algorithmic in
later works, mostly by a group in Risc (Linz, Austria) and by members
of the
team , , , , , .
The past ÉPI Algorithms contributed several implementations
(*gfun* ,
*Mgfun* ).

Encoding special functions as defining linear functional equations postpones some of the difficulty of the problems to a delayed solving of equations. But at the same time, solving (for special classes of functions) is a sub-task of many algorithms on special functions, especially so when solving in terms of polynomial or rational functions. A lot of work has been done in this direction in the 1990s; more intensively since the 2000s, solving differential and recurrence equations in terms of special functions has also been investigated.

A major conceptual and algorithmic difference exists for numerical
calculations between data structures that fit on a machine word and
data structures of arbitrary length, that is, *multi-precision*
arithmetic. When multi-precision floating-point numbers became
available, early works on the evaluation of special functions were
just promising that “most” digits in the output were correct, and
performed by heuristically increasing precision during intermediate
calculations, without intended rigour. The original theory
has evolved in a
twofold way since the 1990s:
by making computable all constants hidden in asymptotic
approximations, it became possible to guarantee a *prescribed*
absolute precision; by employing state-of-the-art algorithms on
polynomials, matrices, etc, it became possible to have evaluation
algorithms in a time complexity that is not more than a few times the
output size. On the implementation side, several original works
exist, one of which (*NumGfun* ) is
used in our DDMF.

“Differential approximation”, or “Guessing”, is an operation to get an ODE likely to be satisfied by a given approximate series expansion of an unknown function. This has been used at least since the 1970s and is a key stone in spectacular applications in experimental mathematics . All this is based on subtle algorithms for Hermite–Padé approximants . Moreover, guessing can at times be complemented by proven quantitative results that turn the heuristics into an algorithm . This is a promising algorithmic approach that deserves more attention than it has received so far.

The main concern of computer algebra has long been to prove the feasibility of a given problem, that is, to show the existence of an algorithmic solution for it. However, with the advent of faster and faster computers, complexity results have ceased to be of theoretical interest only. Nowadays, a large track of works in computer algebra is interested in developing fast algorithms, with time complexity as close as possible to linear in their output size. After most of the more pervasive objects like integers, polynomials, and matrices have been endowed with fast algorithms for the main operations on them , the community, including ourselves, started to turn its attention to differential and recurrence objects in the 2000s. The subject is still not as developed as in the commutative case, and a major challenge remains to understand the combinatorics behind summation and integration. On the methodological side, several paradigms occur repeatedly in fast algorithms: “divide and conquer” to balance calculations, “evaluation and interpolation” to avoid intermediate swell of data, etc. .

Handbooks collecting mathematical properties aim at serving as
reference, therefore trusted, documents. The decision of
several authors or maintainers of such knowledge bases to move from paper
books , , to websites and wikis

Several attempts have been made in order to extend existing computer-algebra systems with symbolic manipulations of logical formulas. Yet, these works are more about extending the expressivity of computer-algebra systems than about improving the standards of correctness and semantics of the systems. Conversely, several projects have addressed the communication of a proof system with a computer-algebra system, resulting in an increased automation available in the proof system, to the price of the uncertainty of the computations performed by this oracle.

More ambitious projects have tried to design a new computer-algebra system providing an environment where the user could both program efficiently and elaborate formal and machine-checked proofs of correctness, by calling a general-purpose proof assistant like the Coq system. This approach requires a huge manpower and a daunting effort in order to re-implement a complete computer-algebra system, as well as the libraries of formal mathematics required by such formal proofs.

The move to machine-checked proofs of the mathematical correctness of the output of computer-algebra implementations demands a prior clarification about the often implicit assumptions on which the presumably correctly implemented algorithms rely. Interestingly, this preliminary work, which could be considered as independent from a formal certification project, is seldom precise or even available in the literature.

A number of authors have investigated ways to organize the communication of a chosen computer-algebra system with a chosen proof assistant in order to certify specific components of the computer-algebra systems, experimenting various combinations of systems and various formats for mathematical exchanges. Another line of research consists in the implementation and certification of computer-algebra algorithms inside the logic , , or as a proof-automation strategy. Normalization algorithms are of special interest when they allow to check results possibly obtained by an external computer-algebra oracle . A discussion about the systematic separation of the search for a solution and the checking of the solution is already clearly outlined in .

Significant progress has been made in the certification of numerical applications by formal proofs. Libraries formalizing and implementing floating-point arithmetic as well as large numbers and arbitrary-precision arithmetic are available. These libraries are used to certify floating-point programs, implementations of mathematical functions and for applications like hybrid systems.

To be checked by a machine, a proof needs to be expressed in a constrained, relatively simple formal language. Proof assistants provide facilities to write proofs in such languages. But, as merely writing, even in a formal language, does not constitute a formal proof just per se, proof assistants also provide a proof checker: a small and well-understood piece of software in charge of verifying the correctness of arbitrarily large proofs. The gap between the low-level formal language a machine can check and the sophistication of an average page of mathematics is conspicuous and unavoidable. Proof assistants try to bridge this gap by offering facilities, like notations or automation, to support convenient formalization methodologies. Indeed, many aspects, from the logical foundation to the user interface, play an important role in the feasibility of formalized mathematics inside a proof assistant.

While many logical foundations for mathematics have been proposed, studied, and implemented, type theory is the one that has been more successfully employed to formalize mathematics, to the notable exception of the Mizar system , which is based on set theory. In particular, the calculus of construction (CoC) and its extension with inductive types (CIC) , have been studied for more than 20 years and been implemented by several independent tools (like Lego, Matita, and Agda). Its reference implementation, Coq , has been used for several large-scale formalizations projects (formal certification of a compiler back-end; four-color theorem). Improving the type theory underlying the Coq system remains an active area of research. Other systems based on different type theories do exist and, whilst being more oriented toward software verification, have been also used to verify results of mainstream mathematics (prime-number theorem; Kepler conjecture).

The most distinguishing feature of CoC is that computation is promoted to the status of rigorous logical argument. Moreover, in its extension CIC, we can recognize the key ingredients of a functional programming language like inductive types, pattern matching, and recursive functions. Indeed, one can program effectively inside tools based on CIC like Coq. This possibility has paved the way to many effective formalization techniques that were essential to the most impressive formalizations made in CIC.

Another milestone in the promotion of the computations-as-proofs feature of Coq has been the integration of compilation techniques in the system to speed up evaluation. Coq can now run realistic programs in the logic, and hence easily incorporates calculations into proofs that demand heavy computational steps.

Because of their different choice for the underlying logic, other proof assistants have to simulate computations outside the formal system, and indeed fewer attempts to formalize mathematical proofs involving heavy calculations have been made in these tools. The only notable, but still unfinished, exception, the Kepler conjecture, required a significant work to optimize the rewriting engine that simulates evaluation in Isabelle/HOL.

Programs run and proved correct inside the logic are especially useful for the conception of automated decision procedures. To this end, inductive types are used as an internal language for the description of mathematical objects by their syntax, thus enabling programs to reason and compute by case analysis and recursion on symbolic expressions.

The output of complex and optimized programs external
to the proof assistant can also be stamped with a formal proof of
correctness when their result is easier to *check* than to
*find*. In that case one can benefit from their efficiency
without compromising the level of confidence on their output at the
price of writing and certify a
checker inside the logic. This approach, which has been successfully
used in various contexts,
is very relevant to the present research team.

Representing abstract algebra in a proof assistant has been studied for long. The libraries developed by the MathComp team for the proof of the Odd Order Theorem provide a rather comprehensive hierarchy of structures; however, they originally feature a large number of instances of structures that they need to organize. On the methodological side, this hierarchy is an incarnation of an original work based on various mechanisms, primarily type inference, typically employed in the area of programming languages. A large amount of information that is implicit in handwritten proofs, and that must become explicit at formalization time, can be systematically recovered following this methodology.

The MathComp library was consistently designed after uniform principles of software engineering. These principles range from simple ones, like naming conventions, to more advanced ones, like generic programming, resulting in a robust and reusable collection of formal mathematical components. This large body of formalized mathematics covers a broad panel of algebraic theories, including of course advanced topics of finite group theory, but also linear algebra, commutative algebra, Galois theory, and representation theory. We refer the interested reader to the online documentation of these libraries , which represent about 150,000 lines of code and include roughly 4,000 definitions and 13,000 theorems.

Topics not addressed by these libraries and that might be relevant to the present project include real analysis and differential equations. The most advanced work of formalization on these domains is available in the HOL-Light system , , , although some existing developments of interest , are also available for Coq. Another aspect of the MathComp libraries that needs improvement, owing to the size of the data we manipulate, is the connection with efficient data structures and implementations, which only starts to be explored.

The user of a proof assistant describes the proof he wants to formalize in the system using a textual language. Depending on the peculiarities of the formal system and the applicative domain, different proof languages have been developed. Some proof assistants promote the use of a declarative language, when the Coq and Matita systems are more oriented toward a procedural style.

The development of the large, consistent body of MathComp libraries has prompted the need to design an alternative and coherent language extension for the Coq proof assistant , , enforcing the robustness of proof scripts to the numerous changes induced by code refactoring and enhancing the support for the methodology of small-scale reflection.

The development of large libraries is quite a novelty for the Coq system. In particular any long-term development process requires the iteration of many refactoring steps and very little support is provided by most proof assistants, with the notable exception of Mizar . For the Coq system, this is an active area of research.

Applications in combinatorics and mathematical physics frequently involve equations of so high orders and so large sizes, that computing or even storing all their coefficients is impossible on existing computers. Making this tractable is another challenge of our project. The approach we believe in is to design algorithms of good, ideally quasi-optimal, complexity in order to extract precisely the required data from the equations, while avoiding the computationally intractable task of completely expanding them into an explicit representation.

Typical applications with expected high impact are the automatic discovery and proof of results in combinatorics and mathematical physics for which human proofs are currently unattainable.

(1994–): Maple package for symbolic summation, integration, and other closure properties of multivariate special functions.

Now distributed as part of
Algolib, a collection of packages for combinatorics and
manipulations of special functions, available at
http://

(2007–): Web site consisting
of interactive tables of mathematical formulas on elementary and
special functions. The formulas are automatically generated by
OCaml and computer-algebra routines. Users can ask for more terms
of the expansions, more digits of the numerical values, proofs of
some of the formulas, etc. See
http://

(2007–): Programming tool
for controlling the generation of mathematical websites that embed
dynamical mathematical contents generated by computer-algebra
calculations. Written in OCaml. See
http://

(2004–): Coq normalization tool and decision procedure for expressions in commutative ring theories. Written in Coq and OCaml. Integrated in the standard distribution of the Coq proof assistant since 2005.

(2006–):
Extension of the language of the Coq system. Originally written by
G. Gonthier for his formal proof of the Four-Color Theorem.
A. Mahboubi and E. Tassi
participate to its development, maintenance, distribution,
user support and have written its user manual. See
http://

(2006–):
Coq libraries that cover the mechanization of the proof of the
Odd Order Theorem. Stable libraries are distributed with the
SSReflect extension. A. Mahboubi is one of the main contributors to
the code and its documentation. E. Tassi contributed to the design
of core data structures and to parts of the formalization. A formal
proof was completed in September 2012, and the content of the
libraries, under continued improvements in view of potential reuse,
is available online at
http://

Uncoupling algorithms transform a linear differential system of first
order into one or several scalar differential equations. We examined
in two approaches to uncoupling: the
cyclic-vector method (*CVM*) and the
Danilevski-Barkatou-Zürcher algorithm (*DBZ*). We gave tight
size bounds on the scalar equations produced by *CVM*, and
designed a fast variant of *CVM* whose complexity is
quasi-optimal with respect to the output size. We exhibited a strong
structural link between *CVM* and *DBZ* enabling to show
that, in the generic case, *DBZ* has polynomial complexity and
that it produces a single equation, strongly related to the output of
*CVM*. We proved that algorithm *CVM* is faster than
*DBZ* by almost two orders of magnitude, and provided
experimental results that validate the theoretical complexity
analyses.

The number of excursions (finite paths starting and ending at the
origin) having a given number of steps and obeying various geometric
constraints is a classical topic of combinatorics and probability
theory. We proved in that the sequence
of numbers of excursions in the quarter plane corresponding to a
nonsingular step set

Gessel walks are planar walks confined to the positive quarter plane, that move by unit steps in any of the following directions: West, North-East, East, and South-West. In 2001, Ira Gessel conjectured a closed-form expression for the number of Gessel walks of a given length starting and ending at the origin. In 2008, Kauers, Koutschan, and Zeilberger gave a computer-aided proof of this conjecture. The same year, Bostan and Kauers showed, using again computer algebra tools, that the trivariate generating function of Gessel walks is algebraic. We proposed in the first “human proofs” of these results. They are derived from a new expression for the generating function of Gessel walks.

In an effort to improve the reactivity of Coq, the way it processes and checks a single document has been completely redesigned . The current development version is able to reschedule the tasks to be performed in order to minimize the time required to give interactive feedback to the user. On typical documents taken from the formal proof of the Odd Order Theorem, the worst reaction time of the tool dropped from 5 minutes to 9 seconds. This improvement will be part of the next stable release of the Coq system.

The implementation of Coq's proof commands for manipulation of ring/field expressions has been
improved in response to the demand for better efficiency that emerged
in the formalization of Apéry's irrationality proof of

The device employed to model a hierarchy of algebraic structures with overloaded notations in Coq has been documented in and in the user manual of the tool.

The Small Scale Reflection extension of Coq has been maintained together with its user manual. Some new linguistic constructs to model non-structural reasoning and to enable the user to better factor out repeated arguments have been developed and documented. Some language constructs have been made compatible with the type-classes mechanism offered by Coq. The release of version 1.5 has been prepared.

We have obtained a formal proof, machine-checked by the Coq
proof assistant, of the irrationality of the constant

The approach to finite-group theory adopted in the libraries formalizing in Coq the proof of the Odd Order Theorem has been documented in .

The team is involved in two Common Research Agreements in the MSR–Inria Joint Centre:

*DDMF (Dynamic Dictionary of Mathematical Functions)*.

Goal: Automate exact computations of the mathematical formulas on the special functions of mathematical analysis and present them on an interactive mathematical dictionary online.

Leader: F. Chyzak. Participants: A. Bostan, P. Lairez.

Website: http://

*Mathematical Components*.

Goal: Investigate the design of large-scale, modular and reusable libraries of formalized mathematics. Developed using the Coq proof assistant. This project successfully formalized the proof of the Odd Order Theorem, resulting in a corpus of libraries related to various areas of algebra.

Leader: G. Gonthier (MSR Cambridge). Participants: A. Mahboubi, E. Tassi.

Website: http://

Project *Coquelicot*, funded jointly by the Fondation de
Coopération Scientifique “Campus Paris-Saclay” and Digiteo.

Goal: Create a new Coq library for real numbers of mathematics.

Leader: S. Boldo (Inria Saclay, Toccata). Participant: A. Mahboubi.

Website: http://

*Psi* (ANR-09-JCJC-0006).

Duration: 2009-2013. Goal: Proof-Search control in Interaction with domain-specific methods. Coordinator: Stéphane Lengrand (CNRS, LIX).

Participant: A. Mahboubi.

*ParalITP* (ANR-11-INSE-001).

Goal: Improve the performances and the ergonomics of interactive provers by taking advantage of modern, parallel hardware.

Leader: B. Wolff (University of Orsay, Paris XI). Participants: A. Mahboubi, E. Tassi.

PEPS Grant *Holonomix*.

Goal: Asymptotics of special functions arising in physics, computer science, and number theory.

Leader: Cyril Banderier (CNRS, LIPN). Participant: A. Bostan, F. Chyzak.

*Formalisation of Mathematics* (*ForMath*, EU FP7 STREP FET-open project).

Partners: University of Gothenburg (Sweden); Radboud University Nijmegen (The Netherlands); Inria (France); Universidad de La Rioja (Spain).

Goal: Investigate how recent advances in the methodology and design of computer-checked libraries of formalized mathematics apply to so-far-unexplored areas of mathematics, like real analysis or certified efficient computations.

Leader: Th. Coquand (University of Gothenburg, Sweden). Participant: A. Mahboubi (work package leader for WP1).

Website:
http://

The team started a seminar, first on an irregular basis, but with the view of running more regular sessions. It attracted researchers from teams in the neighbouring environment and had 8 sessions in 2013.

F. Chyzak is part of the scientifique committee of the *Journées
Nationales de Calcul Formel*, the annual meeting of the French
computer algebra community.

A. Mahboubi and E. Tassi have organized the 5th edition of the Coq international workshop (satellite of the Itp 2013 conference, Rennes, July 2013).

A. Mahboubi has participated to the organization of the Lix Colloquium (November 2013) and of the satellite PSATT international workshop.

A. Mahboubi has served in the program committee of the 5th edition of the Coq international workshop.

A. Mahboubi has served in the program committee of the ITP 2013 international conference.

A. Bostan has served as the Poster Committee Chair for the ISSAC 2013 international conference.

A. Bostan has served in the program committee of the MEGA 2013 international conference.

A. Bostan has served in the program committee of the FPSAC 2013 international conference.

A. Bostan has served in the program committee of the SYNASC 2013 international conference.

A. Bostan is part of the Scientific advisory board of the MEGA conference series.

A. Mahboubi and E. Tassi have given an invited tutorial at the ITP 2013 international conference (Rennes, France).

A. Mahboubi has given an invited talk at the Calculemus 2013 conference (Bath, United Kingdom).

A. Mahboubi has given an invited talk at the Colloquium of the Institute of Mathematics at the University of Nantes (France).

A. Mahboubi has given an invited talk, joint with G. Gonthier at the Dutch Mathematical Congress 2013 (Nijmegen, Netherlands).

A. Mahboubi has given an invited talk at the British Colloquium for Theoretical Computer Sciences (Bath, United Kingdom).

Master : A. Bostan, *Algorithmes efficaces en calcul formel*, 12h, M2, MPRI, France

Master : F. Chyzak, *Algorithmes efficaces en calcul formel*, 12h, M2, MPRI, France

Master : A. Mahboubi, *Assistants de preuves*, 18h, M2, MPRI, France

Agrégation de Mathématiques : A. Bostan, *Préparation épreuve de modélisation, option C*, 12h, ÉNS Cachan, France

PhD: B. Morcrette, *Combinatoire analytique et modèles d'urnes*, June 2013, Ph. Flajolet, M. Soria and Ph. Dumas

PhD in progress: A. Barillec, *Asymptotique automatique certifiée des fonctions spéciales*, September 2013, F. Chyzak and A. Mahboubi

PhD in progress: L. Dumont, *Algorithmique efficace pour les diagonales, applications en combinatoire, physique et théorie des nombres*, September 2013, A. Bostan and B. Salvy

PhD in progress: P. Lairez, *Algorithmique efficace pour la création télescopique, et ses applications*, September 2011, A. Bostan and B. Salvy

L3: D. Rouhling, ÉNS Lyon, *Proof search modulo a
theory in sequent calculus*, June–July 2013, S. Graham-Lengrand
(CNRS, LIX) and A. Mahboubi

A. Mahboubi has served as examiner in the PhD jury of Mahfuza
Farooque, *Automated reasoning techniques as proof-search in sequent
calculus*, December 19, 2013.

A. Bostan has served as examiner in the PhD jury of Basile Morcrette, *Combinatoire analytique et modèles d'urnes*, Université Paris 6, June 26, 2013.

A. Mahboubi has given a lecture to laureates of the
*Olympiades académiques de mathématiques, académie de Créteil*.

A. Mahboubi has been involved in the scientific committee for the
elaboration of the board game *Mémoire Vive* produced by the
Inria communication services.

A. Mahboubi has given a talk at the forum STIC Paris-Saclay (Palaiseau, France) in November 2013.