La gestion de la connaissance des équipes de développement logiciel

RÉSUMÉ Contexte : Le développement logiciel est un travail d’équipe manipulant un produit essentiellement invisible. En conséquent, le développement logiciel nécessite des échanges de connaissances importants entre développeurs afin que l’équipe effectue une résolution de problème adéquate. Cette résolution de problème résulte en une prise de décision qui aura un impact direct sur la qualité du produit logiciel final. Objectif : Ce travail doctoral a pour objectif de mieux comprendre ces interactions entre développeurs et comment ces interactions peuvent être liées à des problèmes de qualité logicielle. Cette meilleure compréhension du phénomène permet d’améliorer les approches actuelles de développement logiciel afin d’assurer une meilleure qualité du produit final. Méthodologie : Premièrement, des revues de littérature ont été effectuées afin de mieux comprendre l’état actuel de la recherche en gestion de connaissance dans le génie logiciel. Deuxièmement, des analyses de code source et des discussions avec les développeurs ont été faites afin de mieux cerner les causes de problèmes classiques de qualité logicielle. Finalement, des observations faites dans l’industrie ont permis de comprendre la prise de décision collective, et comment cette prise de décision impacte la qualité logicielle. Résultats : Les observations effectuées ont démontré que la qualité logicielle n’est pas qu’un problème d’éducation ; l’essentiel des problèmes de qualité ont été introduits par les développeurs en toute connaissance de cause afin de répondre à d’autres impératifs plus urgents au moment de la prise de décision. Améliorer la qualité des logiciels demande de revoir la manière dont les projets de développement logiciel sont gérés afin d’assurer que les décisions prises sur le terrain n’auront pas de conséquences négatives trop coûteuses à long terme. Conclusions : Il est recommandé que les organisations se dote d’un nouveau palier décisionnel faisant la jointure entre besoins techniques (i.e. qualité logicielle) et administratifs (i.e. ressources disponibles). Ce nouveau palier décisionnel se situerait au niveau de la base de code (« codebase »), soit entre le palier organisationnel et le palier de gestion de projet. Une base de code étant modifiée de manière concurrente par plusieurs projets en parallèle, il devient nécessaire d’avoir un meilleur contrôle sur les modifications effectuées sur celle-ci. Ce nouveau palier serait le gardien des connaissances en lien avec la base de code, selon le principe « you build it, you run it » favorisé dans certaines organisations. Ce nouveau palier serait responsable d’assurer que la base de code reste d’une qualité suffisamment bonne pour supporter les activités de l’organisation dans l’avenir.----------ABSTRACT Context: Software development is a process requiring teamwork on an essentially invisible product. Therefore, software development requires important knowledge exchanges between developers in order to ensure a proper problem resolution. This problem resolution affects the decision making process, which will have a direct impact on the software quality of the final product. Objective: This thesis work aims to better understand these interactions between developers and how they can be linked to software quality problems. With a better understanding of the relation, it will be possible to improve the current software development management practices in order to ensure a better quality of the final software product. Method: First, literature reviews were made with the objective to understand the current state of the research in knowledge management in software engineering. Second, source code analyzes and discussions with the developers were executed in order to better understand the causes of typical software quality issues. Finally, observations were made in an industrial context in order to observe collective decision making in the field, and to understand how these decisions impacts software quality. Results: The bservations made demonstrated that software quality is not only an educational problem; most of the quality problems found were introduced voluntarily by the developers in order to answer a more urgent requirement at the time. Improving software quality therefore requires a review of how software development projects are managed in order to ensure that the decision made in the field do not have overly costly consequences in the long term. Conclusions: It is recommended that organization assign a new decision level linking the technical requirements (i.e. software quality) with administrative requirements (i.e. available resources). This new decision level would be situated at the codebase level, between the organizational strategy level and the project management level. A codebase being modified concurrently by multiple projects, it is therefore necessary to have a better control of the modifications made on it. The people at this new decision level would be the knowledge repository related to the codebase, under the “you build it, you run it” principle popular in some organizations. This new decision level would be responsible of ensuring that the codebase remains of a sufficient quality in order to support the future activities of the organization

Why Modern Open Source Projects Fail

Open source is experiencing a renaissance period, due to the appearance of modern platforms and workflows for developing and maintaining public code. As a result, developers are creating open source software at speeds never seen before. Consequently, these projects are also facing unprecedented mortality rates. To better understand the reasons for the failure of modern open source projects, this paper describes the results of a survey with the maintainers of 104 popular GitHub systems that have been deprecated. We provide a set of nine reasons for the failure of these open source projects. We also show that some maintenance practices -- specifically the adoption of contributing guidelines and continuous integration -- have an important association with a project failure or success. Finally, we discuss and reveal the principal strategies developers have tried to overcome the failure of the studied projects.Comment: Paper accepted at 25th International Symposium on the Foundations of Software Engineering (FSE), pages 1-11, 201

A knowledge-based perspective for software process modeling

As the acquisition and sharing of knowledge form the backbone of the software development process, it is important to identify knowledge discrepancies between the process elements. Explicit representation of the knowledge components within a software process model can provide a means to expose these discrepancies. This paper presents an extension of the Software and System Process Engineering Metamodel (SPEM), to be used as a new knowledge modeling layer. The approach, which is based on ontologies for knowledge representation, constitutes an explicit method for representing knowledge within process models. A concept matching indicator shows the state of the process model in terms of the concept gaps for each task within the process. This indicator could lead to more informed decision making and better management of the associated risks, in terms of team competency, documentation quality, and the training required to mitigate them

Proteomic analyses reveal misregulation of LIN28 expression and delayed timing of glial differentiation in human iPS cells with MECP2 loss-of-function.

Rett syndrome (RTT) is a pervasive developmental disorder caused by mutations in MECP2. Complete loss of MECP2 function in males causes congenital encephalopathy, neurodevelopmental arrest, and early lethality. Induced pluripotent stem cell (iPSC) lines from male patients harboring mutations in MECP2, along with control lines from their unaffected fathers, give us an opportunity to identify some of the earliest cellular and molecular changes associated with MECP2 loss-of-function (LOF). We differentiated iPSC-derived neural progenitor cells (NPCs) using retinoic acid (RA) and found that astrocyte differentiation is perturbed in iPSC lines derived from two different patients. Using highly stringent quantitative proteomic analyses, we found that LIN28, a gene important for cell fate regulation and developmental timing, is upregulated in mutant NPCs compared to WT controls. Overexpression of LIN28 protein in control NPCs suppressed astrocyte differentiation and reduced neuronal synapse density, whereas downregulation of LIN28 expression in mutant NPCs partially rescued this synaptic deficiency. These results indicate that the pathophysiology of RTT may be caused in part by misregulation of developmental timing in neural progenitors, and the subsequent consequences of this disruption on neuronal and glial differentiation

Visual Encoding of Social Cues Contributes to Moral Reasoning in Autism Spectrum Disorder: An Eye-Tracking Study

Eye-tracking studies suggest that visual encoding is important for social processes such as socio-moral reasoning. Alterations to the visual encoding of faces, for example, have been linked to the social phenotype of autism spectrum disorders (ASDs) and are associated with social and communication impairments. Yet, people with ASD often perform similarly to neurotypical participants on measures of moral reasoning, supporting the hypothesis of differential mechanisms of moral reasoning in ASD. The objective of this study was to document visual encoding and moral reasoning in ASD and neurotypical individuals using a visual, ecological, sociomoral reasoning paradigm paired with eye-tracking. Two groups (ASD, Control) matched for age and IQ completed the SoMoral task, a set of picture situations describing everyday moral dilemmas, while their eye movements and pupil dilation were recorded. Moral understanding, decision-making, and justification were recorded. Participants with ASD presented a longer time to first fixation on faces. They also understood fewer dilemmas and produced fewer socially adaptive responses. Despite a similar average level of moral maturity, the justifications produced by participants with ASD were not distributed in the same way as the neurotypical participants. Visual encoding was a significant predictor of moral decision-making and moral justification for both groups. The results are discussed in the context of alternative mechanisms of moral reasoning in ASD

Cross-validation of ELISA and a portable surface plasmon resonance instrument for IgG antibody serology with SARS-CoV-2 positive individuals.

We report on the development of surface plasmon resonance (SPR) sensors and matching ELISAs for the detection of nucleocapsid and spike antibodies specific to the novel coronavirus 2019 (SARS-CoV-2) in human serum, plasma and dried blood spots (DBS)

Protein-protein interaction confidence assessment and network clustering computational analysis

Protein-protein interactions represent a crucial source of information for the understanding of the biological mechanisms of the cell. In order to be useful, high quality protein-protein interactions must be computationally extracted from the noisy datasets produced by high-throughput experiments such as affinity purification. Even when filtered protein-protein interaction datasets are obtained, the task of analyzing the network formed by these numerous interactions remains tremendous. Protein-protein interaction networks are large, intricate, and require computational approaches to provide meaningful biological insights. The overall objective of this thesis is to explore algorithms assessing the quality of protein-protein interactions and facilitating the analysis of their networks. This work is divided into four results: 1) a novel Bayesian approach to model contaminants originating from affinity purifications, 2) a new method to identify and evaluate the quality of protein-protein interactions independently in different cell compartments, 3) an algorithm computing the statistical significance of clusterings of proteins sharing the same functional annotation in protein-protein interaction networks, and 4) a computational tool performing sequence motif discovery in 5' untranslated regions as well as evaluating the clustering of such motifs in protein-protein interaction networks.Les interactions protéine-protéine représentent une source d'information essentielle à la compréhension des divers méchanismes biologiques de la cellule. Cependant, les expériences à haut débit qui identifient ces interactions, comme la purification par affinité, produisent un très grand nombre de faux-positifs. Des méthodes computationelles sont donc requises afin d'extraire de ces ensembles de données les interactions protéine-protéine de grande qualité. Toutefois, même lorsque filtrés, ces ensembles de données forment des réseaux très complexes à analyser. Ces réseaux d'interactions protéine-protéine sont d'une taille importante, d'une grande complexité et requièrent des approches computationelles sophistiquées afin d'en retirer des informations possédant une réelle portée biologique. L'objectif de cette thèse est d'explorer des algorithmes évaluant la qualité d'interactions protéine-protéine et de faciliter l'analyse des réseaux qu'elles composent. Ce travail de recherche est divisé en quatre principaux résultats: 1) une nouvelle approche bayésienne permettant la modélisation des contaminants provenant de la purification par affinité, 2) une nouvelle méthode servant à la découverte et l'évaluation de la qualité d'interactions protéine-protéine à l'intérieur de différents compartiments de la cellule, 3) un algorithme détectant les regroupements statistiquement significatifs de protéines partageant une même annotation fonctionnelle dans un réseau d'interactions protéine-protéine et 4) un outil computationel qui a pour but la découverte de motifs de séquences dans les régions 5' non traduites tout en évaluant le regroupement de ces motifs dans les réseaux d'interactions protéine-protéine