Identifiers play a key role in code quality and comprehension, as poorly named identifiers hinder the developers’ ability to understand, debug, and maintain programs. To address these issues, several studies have proposed methods to automatically rename low-quality or inconsistent identifiers. Recently, machine learning has been used to predict potential renaming opportunities for identifiers. However, there is none or little work done that reviews the key machine learning-based methods used to rename identifiers. To that end, this project aims to conduct a systematic literature review that will answer: a) what key machine learning-based approaches exist for recommeding renamings of identifiers; b) how accurate are the different approaches; and c) what datasets are used for their evaluation. As a result of the literature review, we selected 14 learning-based identifier renaming approaches published between 2014-2021. From the extracted data, we identified a total of 19 machine learning techniques, which we categorized into a taxonomy of "deep" and "shallow" learning. In this process, we found that a majority of studies since 2019 have used deep learning techniques. Specifically, two context-based approaches achieved the best performance in detecting and renaming inconsistent identifiers. As a result, we discussed how the use of different techniques might have influenced the performance, evaluation methods, and research practices in the area of rename refactoring.

(in English): The aim of this thesis is to present persistent identification system of digital object identifier and analyze of use of DOI on a sample of public universities in the Czech Republic. The first part introduce the DOI system, its structure, advantages and examples of use in recent time. The second part is focused on analysis of current use of DOI in public univeristies. To fullfil this purpose researched questions were stated. Data was collected were determined in questionaire survey and semi structured interview. The conclusion of thesis proposes a direction of further reflection towards improvement of current situation.

The problem of parameter and state estimation of a class of nonlinear systems is addressed. An adaptive identifier and observer are used to estimate the parameters and the state variables simultaneously. The proposed method is derived using a new formulation. Uncertainty sets are defined for the parameters and a set of auxiliary variables for the state variables. An algorithm is developed to update these sets using the available information. The algorithm proposed guarantees the convergence of parameters and the state variables to their true value. In addition to its application in difficult estimation problems, the algorithm has also been adapted to handle fault detection problems. The technique of estimation is applied to two broad classes of systems. The first involves a class of continuous time nonlinear systems subject to bounded unknown exogenous disturbance with constant parameters. Using the proposed set-based adaptive estimation, the parameters are updated only when an improvement in the precision of the parameter estimates can be guaranteed. The formulation provides robustness to parameter estimation error and bounded disturbance. The parameter uncertainty set and the uncertainty associated with an auxiliary variable is updated such that the set is guaranteed to contain the unknown true values. The second class of system considered is a class of nonlinear systems with timevarying parameters. Using a generalization of the set-based adaptive estimation technique proposed, the estimates of the parameters and state are updated to guarantee convergence to a neighborhood of their true value. The algorithm proposed can also be extended to detect the fault in the system, injected by drastic change in the time-varying parameter values. To study the practical applicability of the developed method, the estimation of state variables and time-varying parameters of salt in a stirred tank process has been performed. The results of the experimental application demonstrate the ability of the proposed techniques to estimate the state variables and time-varying parameters of an uncertain practical system. / Thesis (Master, Chemical Engineering) -- Queen's University, 2011-10-31 22:04:58.762

Le surcoût de fonctionnement d'un BRM immergé a pour origine essentielle la dépense d'énergie liée à la maîtrise de la perméabilité membranaire par aération. La littérature montre les liens qui existent entre concentration en biomasse dans le réacteur et présence de produits microbiens solubles liés à l'activité bactérienne. Réduire la demande en énergie signifie réduire l'aération membrane, voire l'aération process liée aux besoins en oxygène des populations épuratrices. Pour ce faire, il est donc déterminant de réduire l'activité biologique au sein du réacteur sans pour autant dégrader la qualité de l'eau traitée. Pour répondre à ce défi, il a été proposé de développer un BRM en association avec un prétraitement physico-chimique dont le rôle est de retenir une grande part de la matière organique (mais aussi probablement les phosphates), le BRM n'a alors pour rôle que de traiter le résiduel de matière organique et d'éliminer les composés azotés peu retenus par précipitation physico-chimiques. Ainsi, la demande en oxygène sera réduite car il reste peu de DCO à dégrader et la croissance cellulaire limitée car les populations seraient essentiellement autotrophes. Ce travail de thèse a donc été centré sur les points suivants : (i) les performances d'un bioréacteur à membrane fonctionnant sous une charge essentiellement azotée, ces performances sont analysées en termes de réactions d'élimination des fractions polluantes et de filtrabilité des suspensions, (ii) suivi et modélisation des cinétiques de réactions, (iii) définition d'outils simples de dimensionnement. Des méthodologies expérimentales originales ont été mises en place, réacteur pilote et méthodes d'analyses spécifiques (suivi en ligne des composés azotés, méthodes respirométriques notamment). Les résultats obtenus ont permis d'évaluer (i) les capacités de nitrification en régime permanent, (ii) les grandeurs cinétiques propres aux populations autotrophes suivant le modèle ASM1 (XBA, YA, KSH, bA), (iii) la filtrabilité des suspensions sur membranes poreuses avec une contribution significative de la résistance hydraulique due à un biofilm qui se développe en surface de membrane (par rapport aux autres processus, notamment les phénomènes d'adsorption ou bouchage de pores). Ces résultats ont permis de définir des nouveaux outils simples d'extrapolation, notamment des grandeurs réactionnelles spécifiques propres aux espèces nitrifiantes comme le ratio rSNHmax/OURendaut exprimant un rapport de vitesse de nitrification par une grandeur proportionnelle à la concentration en biomasse nitrifiante. / Membrane bioréactor, coupling bioreactions and porous membrane separation in a same unit, allows working with high biomass concentrations what improves bioreaction rates but penalizes the separation step. This work had as objective to study the nitrifiers micro-organisms on the membrane fouling dynamic and on the nitrogen removal efficiency. According to precedent works of the laboratory and the analyses of references, the objective was axed on the modeling tools available for heterotrophe and autotrophe biomass caracterisation. Then, specific methodologies were carried out, lab scale pilots and analytical methods, notably for active biomass observations and identification. Theses tools underline the role of these dominant populations (i) the use of ASM to simulate the biomass performances in relation with working conditions and (ii) the respirometric methods to experimentally quantify the specific biomass activity. Then results clearly pointed out the role of the COD/N ratio on the biomass and MBR performances. Passing from the urban wastewater to synthetic substrate with a final COD/N ratio of 1.5, the proportion of autotrophic bacteria in active biomass increased from 16 to 72%. Specific criteria were defined to characterise the biomass activity as rnitrif/ OURAutoend or rDCO / OURHetend allowing universal parameters definition

Knowledge of the lane that a target is located in is of particular interest in on-road surveillance and target tracking systems. We formulate the problem and propose two approaches for on-road target estimation with lane tracking. The first approach for lane tracking is lane identification based ona Hidden Markov Model (HMM) framework. Two identifiers are developed according to different optimality goals of identification, i.e., the optimality for the whole lane sequence and the optimality of the current lane where the target is given the whole observation sequence. The second approach is on-road target tracking with lane estimation. We propose a 2D road representation which additionally allows to model the lateral motion of the target. For fusion of the radar and image sensor based measurement data we develop three, IMM-based, estimators that use different fusion schemes: centralized, distributed, and sequential. Simulation results show that the proposed two methods have new capabilities and achieve improved estimation accuracy for on-road target tracking.

We consider a class of problems characterized by the need for a string based identifier that reflect the ontology of the application domain. We present rules for string-based identifier schemas that facilitate fast filtering in databases used for this class of problems. We provide runtime analysis of our schema and experimentally compare it with another solution. We also discuss performance in our solution to a game engine. The string-based identifier schema can be used in addition scenarios such as cloud computing. An identifier schema adds metadata about an element. So the solution hinges on additional memory but as long as queries operate only on the included metadata there is no need to load the element from disk which leads to huge performance gains.

The main aim of this thesis is to analyze the approaches of identification of individuals in the Czech Republic. The next part of the thesis are the characteristics of personal data protection in the Czech Republic, an overview of legislative changes in the identification of individuals and in particular the analysis of the Regulation No 910/2014 of the European Parliament and of the Council. Based on the characteristics of the legislation identification in the Czech Republic , the analysis of the above mentioned Regulation and compared with the identification systems that are in place in other European Union states and several other countries around the world , is created draft a universal identifier for the Czech Republic as a vision of the future with specific recommended elements and their reasoning . The main contribution of this work is the analysis of legislation in the Czech Republic and its changes following the adoption of new EU legislation, as well as the inclusion of the new legislation in a model for the identification of individuals in the Czech Republic.

Diploma thesis is focused on identifiers of vehicles and their parts. The thesis gives an overview about available identifiers situated on the vecihles. Further more the thesis deal with potentional forgery and altering of identifiers and as a next shows potentional ways how to detect a manipulation with them. Practipal part of thesis includes a proposal of methodology for checking vehicles based on identifiers. There was also created a cathalogue of the Skoda vehicles. It gives an overview of identifiers for selected vehicles of the brand Skoda.

Code comprehension is crucial for software development, as it ensures that code is easy to read andunderstand.Identifiers, such as variable-, function-, and methodnames playa significant role in code comprehension, and it isimportantthat they are written using meaningful names so thateveryone understands their usage. However, sometimes theycontainabbreviations that can have significantly differentexplanationsdepending on the context they are written in, which couldnegatively impact comprehension if the context is notfully known.Large code bases can be hard to navigate but with thehelp ofCode Visualization Tool (CVT) they can provide anoverviewthat helpfully displays the program’s flow and call graphs.Tohelp with abbreviations in large code bases this studywasconducted to investigate the use of Abbreviation Resolver(AR)techniques integrated into a CVT called Doxygen to seethe effecton identifier comprehension. A survey was performed ontwoopen-source projects with questions about thecomprehensionof different methods using their identifiers with bothresolvedidentifiers and abbreviated identifiers. The survey utilizedAR toanalyze participant ́s understanding of abbreviations todetermine it ́s usefulness. The findings suggest that the use ofa CVTwith an integrated AR helps in understanding uncommonanddomain-knowledge abbreviations which contribute toimprovedcode comprehension.

京都大学 / 新制・課程博士 / 博士(人間健康科学) / 甲第24809号 / 人健博第115号 / 新制||人健||8(附属図書館) / 京都大学大学院医学研究科人間健康科学系専攻 / (主査)教授 中尾 恵, 教授 岡 昌吾, 教授 浅野 雅秀 / 学位規則第4条第1項該当 / Doctor of Human Health Sciences / Kyoto University / DFAM