The microservice architecture (MSA) emerged as an evolution of existing architectural styles with the promise of improving software quality by decomposing an app into modules that can be maintained, deployed, and scaled independently. However, the transition from a monolithic to a microservice architecture is fraught with difficulties, especially when it comes to assessing qualitative aspects, as controversial results can arise. In this paper, we present an experience report on the migration of a monolithic web application and use performance, availability and energy efficiency as quality attributes to shed light on such an architectural transition. Horizontal scaling, i.e., distributing the workload across several service instances, is applied and we study its impact.Our main findings are: i) when no app component is replicated, MSA outperforms the monolithic architecture; ii) the monolithic architecture shows performance and availability improvement when replicating the entire app; iii) the replicated MSA version reaches a ceiling when not replicating its routing part (i.e., the API gateway), showing worse response times compared to the replicated monolith; iv) when replicating the API gateway, the MSA version reaches optimal performance with fewer replicates than the monolith; v) when not replicating services, MSA consumes more CPU resources than the monolithic architecture; vi) when scaling up, the MSA version is more efficient than the replicated monolith in terms of memory usage, and it can better exploit CPU resources; vii) when not replicating services, MSA consumes more energy than the monolithic architecture, whereas when scaling up, the MSA version is more efficient than the replicated monolith; MSA version reaches a good balance between CPU and memory usage.

We present ShellOnYou, a new Computer Science education tool, and analyze its use with four successive student cohorts. Developed to help instructors manage numerous students, this web application offers auto-graded exercises to acquire practical knowledge of Unix-like operating systems from the command line. For each answer, and almost instantly, students receive a score and detailed feedback. This reactive and iterative process encourages students to resubmit answers and progressively expand their procedural knowledge. The tool can also deliver individualized statements, thereby allowing students to improve their skills by combining personal research and peer learning. As an online tool, ShellOnYou affords students access flexibility, and also easily fits in distance learning programs. We found it particularly useful when teaching students with heterogeneous Unix backgrounds. The tool is available on request. We placed four successive student cohorts in a learning situation involving this tool, and asked them to fill a survey at the end of the learning period. We combine qualitative and quantitative methods to analyze their answers to the survey. We attempt to characterize their acquisition of procedural knowledge and the building of group dynamics. Several dimensions emerge: the benefits of using the tool in a learning situation, the learning process iteration as a catalyst for renewed commitment, the tool's entertaining format and its scoring system as a motivation for regular studying, and the inherent customization of the learning pace.

Historically, computing instructors and researchers have developed a wide variety of tools to support teaching and educational research, including exam and code testing suites and data collection solutions. Many are then community or individually maintained. However, these tools often find limited adoption beyond their creators. As a result, it is common for many of the same functionalities to be re-implemented by different instructional groups within the CS Education community. We hypothesize that this is due in part to accessibility, discoverability, and adaptability challenges, among others. Further, instructors often face institutional barriers to deployment, which can include hesitance of institutions to utilize community developed solutions that often lack a centralized authority. This working group will explore what solutions are currently available, what instructors need, and reasons behind the above-mentioned phenomenon. This will be accomplished via a literature review and survey to identify the tools that have been developed by the community; the solutions that are currently available and in use by instructors; what features are needed moving forward for classroom and research use; what support for extensions is needed to support further CS Education research; and what institutional challenges instructors and researchers are currently facing or have faced in the past in developing, deploying or otherwise using community software solutions. Finally, the working group will identify factors that limit adoption of solutions and ways to integrate and improve the accessibility, discoverability, and dissemination of existing community projects, as well as manage and overcome institutional challenges.

For various species, high quality sequences and complete genomes are nowadays available for many individuals. This makes data analysis challenging, as methods need not only to be accurate, but also time efficient given the tremendous amount of data to process. In this article, we introduce an efficient method to infer the evolutionary history of individuals under the multispecies coalescent model in networks (MSNC). Phylogenetic networks are an extension of phylogenetic trees that can contain reticulate nodes, which allow to model complex biological events such as horizontal gene transfer, hybridization and introgression. We present a novel way to compute the likelihood of biallelic markers sampled along genomes whose evolution involved such events. This likelihood computation is at the heart of a Bayesian network inference method called SnappNet, as it extends the Snapp method inferring evolutionary trees under the multispecies coalescent model, to networks. SnappNet is available as a package of the well-known beast 2 software. Recently, the MCMC_BiMarkers method, implemented in PhyloNet, also extended Snapp to networks. Both methods take biallelic markers as input, rely on the same model of evolution and sample networks in a Bayesian framework, though using different methods for computing priors. However, SnappNet relies on algorithms that are exponentially more time-efficient on non-trivial networks. Using simulations, we compare performances of SnappNet and MCMC_BiMarkers. We show that both methods enjoy similar abilities to recover simple networks, but SnappNet is more accurate than MCMC_BiMarkers on more complex network scenarios. Also, on complex networks, SnappNet is found to be extremely faster than MCMC_BiMarkers in terms of time required for the likelihood computation. We finally illustrate SnappNet performances on a rice data set. SnappNet infers a scenario that is consistent with previous results and provides additional understanding of rice evolution.

Motivation: A reconciliation is an annotation of the nodes of a gene tree with evolutionary events-for example, speciation, gene duplication, transfer, loss, etc.-along with a mapping onto a species tree. Many algorithms and software produce or use reconciliations but often using different reconciliation formats, regarding the type of events considered or whether the species tree is dated or not. This complicates the comparison and communication between different programs. Results: Here, we gather a consortium of software developers in gene tree species tree reconciliation to propose and endorse a format that aims to promote an integrative-albeit flexible-specification of phylogenetic reconciliations. This format, named recPhyloXML, is accompanied by several tools such as a reconciled tree visualizer and conversion utilities. Availability and implementation: http://phylariane.univ-lyon1.fr/recphyloxml/.

MOTIVATION: Reconciliation methods aim at recovering the evolutionary processes that shaped the history of a given gene family including events such as duplications, transfers and losses by comparing the discrepancies between the topologies of the associated gene and species trees. These methods are also used in the framework of host/parasite studies to recover co-diversification scenarios including co-speciation events, host-switches and extinctions. These evolutionary processes can be graphically represented as nested trees. These interconnected graphs can be visually messy and hard to interpret, and despite the fact that reconciliations are increasingly used, there is a shortage of tools dedicated to their graphical management. Here we present SylvX, a reconciliation viewer which implements classical phylogenetic graphic operators (swapping, highlighting, etc.) and new methods to ease interpretation and comparison of reconciliations (multiple maps, moving, shrinking sub-reconciliations). AVAILABILITY AND IMPLEMENTATION: SylvX is an open source, cross-platform, standalone editor available for Windows and Unix-like systems including OSX. It is publicly available at www.sylvx.org.

Gene sequences contain a gold mine of phylogenetic information. But unfortunately for taxonomists this information does not only tell the story of the species from which it was collected. Genes have their own complex histories which record speciation events, of course, but also many other events. Among them, gene duplications, transfers and losses are especially important to identify. These events are crucial to account for when reconstructing the history of species, and they play a fundamental role in the evolution of genomes, the diversification of organisms and the emergence of new cellular functions. We review reconciliations between gene and species trees, which are rigorous approaches for identifying duplications, transfers and losses that mark the evolution of a gene family. Existing reconciliation models and algorithms are reviewed and difficulties in modeling gene transfers are discussed. We also compare different reconciliation programs along with their advantages and disadvantages.

UNLABELLED: There is a large amount of tools for interactive display of phylogenetic trees. However, there is a shortage of tools for the automation of tree rendering. Scripting phylogenetic graphics would enable the saving of graphical analyses involving numerous and complex tree handling operations and would allow the automation of repetitive tasks. ScripTree is a tool intended to fill this gap. It is an interpreter to be used in batch mode. Phylogenetic graphics instructions, related to tree rendering as well as tree annotation, are stored in a text file and processed in a sequential way. AVAILABILITY: ScripTree can be used online or downloaded at www.scriptree.org, under the GPL license. IMPLEMENTATION: ScripTree, written in Tcl/Tk, is a cross-platform application available for Windows and Unix-like systems including OS X. It can be used either as a stand-alone package or included in a bioinformatic pipeline and linked to a HTTP server.

Given a set L of labels and a collection of rooted trees whose leaves are bijectively labeled by some elements of L, the Maximum Agreement Supertree (SMAST) problem is given as follows: find a tree T on a largest label set L(') is included in L that homeomorphically contains every input tree restricted to L('). The problem has phylogenetic applications to infer supertrees and perform tree congruence analyses. In this paper, we focus on the parameterized complexity of this NP-hard problem, considering different combinations of parameters as well as particular cases. We show that SMAST on k rooted binary trees on a label set of size n can be solved in O((8n)k) time, which is an improvement with respect to the previously known O(n3k2) time algorithm. In this case, we also give an O((2k)pkn2) time algorithm, where p is an upper bound on the number of leaves of L missing in a SMAST solution. This shows that SMAST can be solved efficiently when the input trees are mostly congruent. Then, for the particular case where any triple of leaves is contained in at least one input tree, we give O(4pn3) and O(3:12p + n4) time algorithms, obtaining the first fixed-parameter tractable algorithms on a single parameter for this problem. We also obtain intractability results for several combinations of parameters, thus indicating that it is unlikely that fixed-parameter tractable algorithms can be found in these particular cases.

MOTIVATION: Developing methods for computing phylogenetic networks from biological data is an important problem posed by molecular evolution and much work is currently being undertaken in this area. Although promising approaches exist, there are no tools available that biologists could easily and routinely use to compute rooted phylogenetic networks on real datasets containing tens or hundreds of taxa. Biologists are interested in clades, i.e. groups of monophyletic taxa, and these are usually represented by clusters in a rooted phylogenetic tree. The problem of computing an optimal rooted phylogenetic network from a set of clusters, is hard, in general. Indeed, even the problem of just determining whether a given network contains a given cluster is hard. Hence, some researchers have focused on topologically restricted classes of networks, such as galled trees and level-k networks, that are more tractable, but have the practical draw-back that a given set of clusters will usually not possess such a representation. RESULTS: In this article, we argue that galled networks (a generalization of galled trees) provide a good trade-off between level of generality and tractability. Any set of clusters can be represented by some galled network and the question whether a cluster is contained in such a network is easy to solve. Although the computation of an optimal galled network involves successively solving instances of two different NP-complete problems, in practice our algorithm solves this problem exactly on large datasets containing hundreds of taxa and many reticulations in seconds, as illustrated by a dataset containing 279 prokaryotes. AVAILABILITY: We provide a fast, robust and easy-to-use implementation of this work in version 2.0 of our tree-handling software Dendroscope, freely available from http://www.dendroscope.org.

Given a set of leaf-labeled trees with identical leaf sets, the well-known Maximum Agreement SubTree (MAST) problem consists in finding a subtree homeomorphically included in all input trees and with the largest number of leaves. MAST and its variant called Maximum Compatible Tree (MCT) are of particular interest in computational biology. This article presents a linear-time approximation algorithm to solve the complement version of MAST, namely identifying the smallest set of leaves to remove from input trees to obtain isomorphic trees. We also present an O ( n 2 + kn ) algorithm to solve the complement version of MCT. For both problems, we thus achieve significantly lower running times than previously known algorithms. Fast running times are especially important in phylogenetics where large collections of trees are routinely produced by resampling procedures, such as the nonparametric bootstrap or Bayesian MCMC methods.

BACKGROUND: Supertree methods combine phylogenies with overlapping sets of taxa into a larger one. Topological conflicts frequently arise among source trees for methodological or biological reasons, such as long branch attraction, lateral gene transfers, gene duplication/loss or deep gene coalescence. When topological conflicts occur among source trees, liberal methods infer supertrees containing the most frequent alternative, while veto methods infer supertrees not contradicting any source tree, i.e. discard all conflicting resolutions. When the source trees host a significant number of topological conflicts or have a small taxon overlap, supertree methods of both kinds can propose poorly resolved, hence uninformative, supertrees. RESULTS: To overcome this problem, we propose to infer non-plenary supertrees, i.e. supertrees that do not necessarily contain all the taxa present in the source trees, discarding those whose position greatly differs among source trees or for which insufficient information is provided. We detail a variant of the PhySIC veto method called PhySIC_IST that can infer non-plenary supertrees. PhySIC_IST aims at inferring supertrees that satisfy the same appealing theoretical properties as with PhySIC, while being as informative as possible under this constraint. The informativeness of a supertree is estimated using a variation of the CIC (Cladistic Information Content) criterion, that takes into account both the presence of multifurcations and the absence of some taxa. Additionally, we propose a statistical preprocessing step called STC (Source Trees Correction) to correct the source trees prior to the supertree inference. STC is a liberal step that removes the parts of each source tree that significantly conflict with other source trees. Combining STC with a veto method allows an explicit trade-off between veto and liberal approaches, tuned by a single parameter.Performing large-scale simulations, we observe that STC+PhySIC_IST infers much more informative supertrees than PhySIC, while preserving low type I error compared to the well-known MRP method. Two biological case studies on animals confirm that the STC preprocess successfully detects anomalies in the source trees while STC+PhySIC_IST provides well-resolved supertrees agreeing with current knowledge in systematics. CONCLUSION: The paper introduces and tests two new methodologies, PhySIC_IST and STC, that demonstrate the interest in inferring non-plenary supertrees as well as preprocessing the source trees. An implementation of the methods is available at: http://www.atgc-montpellier.fr/physic_ist/.

Given a set of evolutionary trees on a same set of taxa, the maximum agreement subtree problem (MAST), respectively, maximum compatible tree problem (MCT), consists of finding a largest subset of taxa such that all input trees restricted to these taxa are isomorphic, respectively compatible. These problems have several applications in phylogenetics such as the computation of a consensus of phylogenies obtained from different data sets, the identification of species subjected to horizontal gene transfers and, more recently, the inference of supertrees, e.g., Trees Of Life. We provide two linear time algorithms to check the isomorphism, respectively, compatibility, of a set of trees or otherwise identify a conflict between the trees with respect to the relative location of a small subset of taxa. Then, we use these algorithms as subroutines to solve MAST and MCT on rooted or unrooted trees of unbounded degree. More precisely, we give exact fixed-parameter tractable algorithms, whose running time is uniformly polynomial when the number of taxa on which the trees disagree is bounded. The improves on a known result for MAST and proves fixed-parameter tractability for MCT.

We present fast new algorithms for phylogenetic reconstruction from distance data or weighted quartets. The methods are conservative-they will only return edges that are well supported by the input data. This approach is not only philosophically attractive; the conservative tree estimate can be used as a basis for further tree refinement or divide and conquer algorithms. The capability to process quartet data allows these algorithms to be used in tandem with ordinal or qualitative phylogenetic analysis methods. We provide algorithms for three standard conservative phylogenetic constructions: the Buneman tree, the Refined Buneman tree, and split decomposition. We introduce and exploit combinatorial formalisms involving trees, quartets, and splits, and make particular use of an attractive duality between unrooted trees, splits, and dissimilarities on one hand, and rooted trees, clusters, and similarity measures on the other. Using these techniques, we achieve O(n) improvements in the time complexity of the best previously published algorithms (where n is the number of studied species). Our algorithms will be included in the next edition of the popular Splitslkee software package.