Sylvie Hamel

ON THE PALINDROMIC COMPLEXITY OF INFINITE WORDS

We study the problem of constructing infinite words having a prescribed finite set P of palindromes. We first establish that the language of all words with palindromic factors in P is rational. As a consequence we derive that there exists, with some additional mild condition, infinite words having P as palindromic factors. We prove that there exist periodic words having the maximum number of palindromes as in the case of Sturmian words, by providing a simple and easy to check condition. Asymmetric words, those that are not the product of two palindromes, play a fundamental role and an enumeration is provided.

Efficient identification of design patterns with bit-vector algorithm

Design patterns are important in software maintenance because they help in designing, in understanding, and in re-engineering programs. The identification of occurrences of a design pattern consists in identifying, in a program, classes which structure and organisation match - strictly or approximately - the structure and organisation of classes as suggested by the design pattern. We express the problem of design pattern identification with operations on finite sets of bit-vectors. We use the inherent parallelism of bit-wise operations to derive an efficient bit-vector algorithm that finds exact and approximate occurrences of design patterns in a program. We apply our algorithm on three small-to-medium size programs, JHotDraw, Juzzle, and QuickUML, with the Abstract Factory and Composite design patterns and compare its performance and results with two existing constraint-based approaches

An Efficient Method for Exploring the Space of Gene Tree/Species Tree Reconciliations in a Probabilistic Framework

Background. Inferring an evolutionary scenario for a gene family is a fundamental problem with applications both in functional and evolutionary genomics. The gene tree/species tree reconciliation approach has been widely used to address this problem, but mostly in a discrete parsimony framework that aims at minimizing the number of gene duplications and/or gene losses. Recently, a probabilistic approach has been developed, based on the classical birth-and-death process, including efficient algorithms for computing posterior probabilities of reconciliations and orthology prediction. Results. In previous work, we described an algorithm for exploring the whole space of gene tree/species tree reconciliations, that we adapt here to compute efficiently the posterior probability of such reconciliations. These posterior probabilities can be either computed exactly or approximated, depending on the reconciliation space size. We use this algorithm to analyze the probabilistic landscape of the space of reconciliations for a real data set of fungal gene families and several data sets of synthetic gene trees. Conclusion. The results of our simulations suggest that, with exact gene trees obtained by a simple birth-and-death process and realistic gene duplication/loss rates, a very small subset of all reconciliations needs to be explored in order to approximate very closely the posterior probability of the most likely reconciliations. For cases where the posterior probability mass is more evenly dispersed, our method allows to explore efficiently the required subspace of reconciliations.

Space of gene/species trees reconciliations and parsimonious models.

We describe algorithms to study the space of all possible reconciliations between a gene tree and a species tree, that is counting the size of this space, uniformly generate a random reconciliation, and exploring this space in optimal time using combinatorial operators. We also extend these algorithms for optimal and sub-optimal reconciliations according to the three usual combinatorial costs (duplication, loss, and mutation). Applying these algorithms to simulated and real gene family evolutionary scenarios, we observe that the LCA (Last Common Ancestor) based reconciliation is almost always identical to the real one.

Modeling RNA tertiary structure motifs by graph-grammars

A new approach, graph-grammars, to encode RNA tertiary structure patterns is introduced and exemplified with the classical sarcin–ricin motif. The sarcin–ricin motif is found in the stem of the crucial ribosomal loop E (also referred to as the sarcin–ricin loop), which is sensitive to the α-sarcin and ricin toxins. Here, we generate a graph-grammar for the sarcin-ricin motif and apply it to derive putative sequences that would fold in this motif. The biological relevance of the derived sequences is confirmed by a comparison with those found in known sarcin–ricin sites in an alignment of over 800 bacterial 23S ribosomal RNAs. The comparison raised alternative alignments in few sarcin–ricin sites, which were assessed using tertiary structure predictions and 3D modeling. The sarcin–ricin motif graph-grammar was built with indivisible nucleotide interaction cycles that were recently observed in structured RNAs. A comparison of the sequences and 3D structures of each cycle that constitute the sarcin–ricin motif gave us additional insights about RNA sequence–structure relationships. In particular, this analysis revealed the sequence space of an RNA motif depends on a structural context that goes beyond the single base pairing and base-stacking interactions.

An Exploratory Study of Macro Co-changes

The literature describes several approaches to identify the artefacts of programs that change together to reveal the (hidden) dependencies among these artefacts. These approaches analyse historical data, mined from version control systems, and report co-changing artefacts, which hint at the causes, consequences, and actors of the changes. We introduce the novel concepts of macro co-changes (MCC), i.e., of artefacts that co-change within a large time interval, and of dephase macro co-changes (DMCC), i.e., macro co-changes that always happen with the same shifts in time. We describe typical scenarios of MCC and DMCC and we use the Hamming distance to detect approximate occurrences of MCC and DMCC. We present our approach, Macocha, to identify these concepts in large programs. We apply Macocha and compare it in terms of precision and recall with UML Diff (file stability) and association rules (co-changing files) on four systems: Argo UML, Free BSD, SIP, and XalanC. We also use external information to validate the (approximate) MCC and DMCC found by Macocha. We thus answer two research questions showing the existence and usefulness of theses concepts and explaining scenarios of hidden dependencies among artefacts.

An edit distance between RNA stem-loops

We introduce the notion of conservative edit distance and mapping between two RNA stem-loops. We show that unlike the general edit distance between RNA secondary structures, the conservative edit distance can be computed in polynomial time and space, and we describe an algorithm for this problem. We show how this algorithm can be used in the more general problem of complete RNA secondary structures comparison.

VECTOR ALGORITHMS FOR APPROXIMATE STRING MATCHING

Vector algorithms allow the computation of an output vector r = r1 r2 ⋯ rm given an input vector e = e1 e2 ⋯ em in a bounded number of operations, independent of m the length of the vectors. The allowable operations are usually restricted to bit-wise operations available in processors, including shifts and binary addition with carry. These restrictions imple that the existence of a vector algorithm for a particular problem opens the way to extremely fast implementations, using the inherent parallelism of bit-wise operations. This paper presents general results on the existence and construction of vertor algorithms, with a particular focus on problems arising from computational biology. We show that efficient vector algorithms exist for the problem of approximate string matching with arbitrary weighted distances, generalizing a previous result by G. Myers. We also characterize a class of automata for which vector algorithms can be automatically derived from the transition table of the automata.

Mining the relationship between anti-patterns dependencies and fault-proneness

Anti-patterns describe poor solutions to design and implementation problems which are claimed to make object oriented systems hard to maintain. Anti-patterns indicate weaknesses in design that may slow down development or increase the risk of faults or failures in the future. Classes in anti-patterns have some dependencies, such as static relationships, that may propagate potential problems to other classes. To the best of our knowledge, the relationship between anti-patterns dependencies (with non anti-patterns classes) and faults has yet to be studied in details. This paper presents the results of an empirical study aimed at analysing anti-patterns dependencies in three open source software systems, namely ArgoUML, JFreeChart, and XerecesJ. We show that, in almost all releases of the three systems, classes having dependencies with anti-patterns are more fault-prone than others. We also report other observations about these dependencies such as their impact on fault prediction. Software organizations could make use of these knowledge about anti-patterns dependencies to better focus their testing and reviews activities toward the most risky classes, e.g., classes with fault-prone dependencies with anti-patterns.

Detecting asynchrony and dephase change patterns by mining software repositories

Software maintenance accounts for the largest part of the costs of any program. During maintenance activities, developers implement changes (sometimes simultaneously) on artifacts in order to fix bugs and to implement new requirements. To reduce this part of the costs, previous work proposed approaches to identify the artifacts of programs that change together. These approaches analyze historical data, mined from version control systems, and report change patterns, which lead at the causes, consequences, and actors of the changes to source code files. They also introduce so‐called change patterns that describe some typical change dependencies among files. In this paper, we introduce two novel change patterns: the asynchrony change pattern, corresponding to macro co‐changes (MC), that is, of files that co‐change within a large time interval (change periods) and the dephase change pattern, corresponding to dephase macro co‐changes (DC), that is, MC that always happens with the same shifts in time. We present our approach, that we named Macocha, to identify these two change patterns in large programs. We use the k‐nearest neighbor algorithm to group changes into change periods. We also use the Hamming distance to detect approximate occurrences of MC and DC. We apply Macocha and compare its performance in terms of precision and recall with UMLDiff (file stability) and association rules (co‐changing files) on seven systems: ArgoUML, FreeBSD, JFreeChart, Openser, SIP, XalanC, and XercesC developed with three different languages (C, C++, and Java). These systems have a size ranging from 532 to 1693 files, and during the study period, they have undergone 1555 to 23,944 change commits. We use external information and static analysis to validate (approximate) MC and DC found by Macocha. Through our case study, we show the existence and usefulness of these novel change patterns to ease software maintenance and, potentially, reduce related costs. Copyright