No description available.

Techn. Universiẗat, Diss., 2005--München.

Würzburg, Univ., Diss., 2009.

To automatically/semi-automatically improve internal structures of a legacy system, there are several challenges: most available software analysis algorithms focus on only one particular granularity level (e.g., method level, class level) without considering possible side effects on other levels during the process; the quality of a software system cannot be judged by a single algorithm; software analysis is a time-consuming process which typically requires lengthy interactions. In this thesis, we present a framework, IFSO (Integrated Framework for automatic/semi-automatic Software refactoring and analysis), as a foundation for automatic/semi-automatic software refactoring and analysis. Our proposed conceptual model, LSR (Layered Software Representation Model), defines an abstract representation for software using a layered approach. Each layer corresponds to a granularity level. The IFSO framework, which is built upon the LSR model for component-based software, represents software at the system level, component level, class level, method level and logic unit level. Each level can be customized by different algorithms such as cohesion metrics, design heuristics, design problem detection and operations independently. Cooperating between levels together, a global view and an interactive environment for software refactoring and analysis are presented by IFSO. A prototype was implemented for evaluation of our technology. Three case studies were developed based on the prototype: three metrics, dead code removing, low coupled unit detection.

Software transactional memory (STM) is an optimistic concurrent lock free mechanism that has the potential of positively transforming how concurrent programming is performed. STM, despite its many desirable attributes, is not yet a ubiquitous programming language feature in the commercial software domain. There are many implementation challenges with retrofitting STM into pre-existing language frameworks. Furthermore, existing software systems will also need to be refactored in order to take advantage of STM’s unique benefits. As with other time consuming and error prone refactoring processes, refactoring for STM is best done with automated tool support; it is the aim of this paper to propose such a tool. / text

Software has been subject to change, at all times, in order to make parts of it, for instance, more reusable, better to understand by humans, or to increase efficiency under a certain point of view. Restructurings of existing software can be complex. To prevent developers from doing this manually, they got tools at hand being able to apply such restructurings automatically. These automatic changes of existing software to improve quality while preserving its behaviour is called refactoring. Refactoring is well investigated for programming languages and mature tools exist for executing refactorings in integrated development environments (IDEs). In recent years, the development paradigm of Model-Driven Software Development (MDSD) became more and more popular and we experience a shift in the sense that development artefacts are considered as models which conform metamodels. This can be understood as abstraction, which resulted in the trend that a plethora of new so-called model-based Domain-Specific Languages (DSLs) arose. DSLs have become an integral part in the MDSD and it is obvious that models are subject to change, as well. Thus, refactoring support is required for DSLs in order to prevent users from doing it manually. The problem is that the amount of DSLs is huge and refactorings should not be implemented for new for each of them, since they are quite similar from an abstract viewing. Existing approaches abstract from the target language, which is not flexible enough because some assumptions about the languages have to be made and arbitrary DSLs are not supported. Furthermore, the relation between a strategy which finds model deficiencies that should be improved, a resolving refactoring, and the improved quality is only implicit. Focussing on a particular quality and only detecting those deficiencies deteriorating this quality is difficult, and elements of detected deficient structures cannot be referred to in the resolving refactoring. In addition, heterogeneous models in an IDE might be connected physically or logically, thus, they are dependent. Finding such connections is difficult and can hardly be achieved manually. Applying a restructuring in a model implied by a refactoring in a dependent model must also be a refactoring, in order to preserve the meaning. Thus, this kind of dependent refactorings require an appropriate abstraction mechanism, since they must be specified for dependent models of different DSLs. The first contribution, Role-Based Generic Model Refactoring, uses role models to abstract from refactorings instead of the target languages. Thus, participating structures in a refactoring can be specified generically by means of role models. As a consequence, arbitrary model-based DSLs are supported, since this approach does not make any assumptions regarding the target languages. Our second contribution, Role-Based Quality Smells, is a conceptual framework and correlates deficiencies, their deteriorated qualities, and resolving refactorings. Roles are used to abstract from the causing structures of a deficiency, which then are subject to resolving refactorings. The third contribution, Role-Based Co-Refactoring, employs the graph-logic isomorphism to detect dependencies between models. Dependent refactorings, which we call co-refactorings, are specified on the basis of roles for being independent from particular target DSLs. All introduced concepts are implemented in our tool Refactory. An evaluation in different scenarios complements the thesis. It shows that role models emerged as very powerful regarding the reuse of generic refactorings in arbitrary languages. Role models are suited as an interface for certain structures which are to be refactored, scanned for deficiencies, or co-refactored. All of the presented approaches benefit from it.

Software has been subject to change, at all times, in order to make parts of it, for instance, more reusable, better to understand by humans, or to increase efficiency under a certain point of view. Restructurings of existing software can be complex. To prevent developers from doing this manually, they got tools at hand being able to apply such restructurings automatically. These automatic changes of existing software to improve quality while preserving its behaviour is called refactoring. Refactoring is well investigated for programming languages and mature tools exist for executing refactorings in integrated development environments (IDEs). In recent years, the development paradigm of Model-Driven Software Development (MDSD) became more and more popular and we experience a shift in the sense that development artefacts are considered as models which conform metamodels. This can be understood as abstraction, which resulted in the trend that a plethora of new so-called model-based Domain-Specific Languages (DSLs) arose. DSLs have become an integral part in the MDSD and it is obvious that models are subject to change, as well. Thus, refactoring support is required for DSLs in order to prevent users from doing it manually. The problem is that the amount of DSLs is huge and refactorings should not be implemented for new for each of them, since they are quite similar from an abstract viewing. Existing approaches abstract from the target language, which is not flexible enough because some assumptions about the languages have to be made and arbitrary DSLs are not supported. Furthermore, the relation between a strategy which finds model deficiencies that should be improved, a resolving refactoring, and the improved quality is only implicit. Focussing on a particular quality and only detecting those deficiencies deteriorating this quality is difficult, and elements of detected deficient structures cannot be referred to in the resolving refactoring. In addition, heterogeneous models in an IDE might be connected physically or logically, thus, they are dependent. Finding such connections is difficult and can hardly be achieved manually. Applying a restructuring in a model implied by a refactoring in a dependent model must also be a refactoring, in order to preserve the meaning. Thus, this kind of dependent refactorings require an appropriate abstraction mechanism, since they must be specified for dependent models of different DSLs. The first contribution, Role-Based Generic Model Refactoring, uses role models to abstract from refactorings instead of the target languages. Thus, participating structures in a refactoring can be specified generically by means of role models. As a consequence, arbitrary model-based DSLs are supported, since this approach does not make any assumptions regarding the target languages. Our second contribution, Role-Based Quality Smells, is a conceptual framework and correlates deficiencies, their deteriorated qualities, and resolving refactorings. Roles are used to abstract from the causing structures of a deficiency, which then are subject to resolving refactorings. The third contribution, Role-Based Co-Refactoring, employs the graph-logic isomorphism to detect dependencies between models. Dependent refactorings, which we call co-refactorings, are specified on the basis of roles for being independent from particular target DSLs. All introduced concepts are implemented in our tool Refactory. An evaluation in different scenarios complements the thesis. It shows that role models emerged as very powerful regarding the reuse of generic refactorings in arbitrary languages. Role models are suited as an interface for certain structures which are to be refactored, scanned for deficiencies, or co-refactored. All of the presented approaches benefit from it.:List of Figures xv List of Tables xvii List of Listings xix 1. Introduction 1 1.1. Language-Tool Generation Without Consideration Of Time And Space . . . . . 4 1.2. Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.3. Generic Quality-Aware Refactoring and Co-Refactoring in Heterogeneous Model Environments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2. Foundations 15 2.1. Refactoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.2. Model-Driven Software Development . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2.1. Levels of Abstraction and Metamodelling . . . . . . . . . . . . . . . . . 17 2.2.2. Model Transformations . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.3. Role-Based Modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3. Related Work 23 3.1. Model Refactoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.1.1. Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.1.2. Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 3.1.3. Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.2. Determination of Quality-Related De ciencies . . . . . . . . . . . . . . . . . . . 32 3.2.1. Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.2.2. Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.2.3. Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 3.3. Co-Refactoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 3.3.1. Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 3.3.2. Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 3.3.3. Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3.4. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 4. Role-Based Generic Model Refactoring 51 4.1. Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 4.2. Specifying Generic Refactorings with Role Models . . . . . . . . . . . . . . . . . 53 4.2.1. Specifying Structural Constraints using Role Models . . . . . . . . . . . 55 4.2.2. Mapping Roles to Language Concepts Using Role Mappings . . . . . . . 57 4.2.3. Specifying Language-Independent Transformations using Refactoring Speci cations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 4.2.4. Composition of Refactorings . . . . . . . . . . . . . . . . . . . . . . . . . 67 4.3. Preserving Semantics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 4.4. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 5. Suggesting Role Mappings as Concrete Refactorings 73 5.1. Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 5.2. Automatic Derivation of Suggestions for Role Mappings with Graph Querying . 74 5.3. Reduction of the Number of Valid Matches . . . . . . . . . . . . . . . . . . . . . 76 5.4. Comparison to Model Matching . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 5.5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 6. Role-Based Quality Smells as Refactoring Indicator 79 6.1. Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 6.2. Correlating Model De ciencies, Qualities and Refactorings . . . . . . . . . . . . 80 6.2.1. Quality Smell Repository . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 6.2.2. Quality Smell Calculation Repository . . . . . . . . . . . . . . . . . . . . 85 6.3. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 6.4. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 7. A Quality Smell Catalogue for Android Applications 89 7.1. Quality Smell Catalogue Schema . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 7.2. Acquiring Quality Smells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 7.3. Structure-Based Quality Smells—A Detailed Example . . . . . . . . . . . . . . . 92 7.3.1. The Pattern Language . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 7.3.2. Quality Smell: Interruption from Background . . . . . . . . . . . . . . . 93 7.4. Quality Smells for Android Applications . . . . . . . . . . . . . . . . . . . . . . 96 7.4.1. Quality Smell: Data Transmission Without Compression . . . . . . . . . 96 7.4.2. Quality Smell: Dropped Data . . . . . . . . . . . . . . . . . . . . . . . . 98 7.4.3. Quality Smell: Durable WakeLock . . . . . . . . . . . . . . . . . . . . . 98 7.4.4. Quality Smell: Internal Use of Getters/Setters . . . . . . . . . . . . . . . 99 7.4.5. Quality Smell: No Low Memory Resolver . . . . . . . . . . . . . . . . . 101 7.4.6. Quality Smell: Rigid AlarmManager . . . . . . . . . . . . . . . . . . . . 101 7.4.7. Quality Smell: Unclosed Closeable . . . . . . . . . . . . . . . . . . . . . 102 7.4.8. Quality Smell: Untouchable . . . . . . . . . . . . . . . . . . . . . . . . . 103 7.5. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 8. Role-Based Co-Refactoring in Multi-Language Development Environments 105 8.1. Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 8.2. Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 8.3. Dependency Knowledge Base . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 8.3.1. Categories of Model Dependencies . . . . . . . . . . . . . . . . . . . . . 108 8.3.2. When to Determine Model Dependencies . . . . . . . . . . . . . . . . . 110 8.3.3. How to Determine Model Dependencies . . . . . . . . . . . . . . . . . . 111 8.4. Co-Refactoring Knowledge Base . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 8.4.1. Specifying Coupled Refactorings with Co-Refactoring Speci cations . . 114 8.4.2. Specifying Bindings for Co-Refactorings . . . . . . . . . . . . . . . . . . 116 8.4.3. Determination of Co-Refactoring Speci cations . . . . . . . . . . . . . . 118 8.5. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 8.6. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 9. Refactory: An Eclipse Tool For Quality-Aware Refactoring and Co-Refactoring 121 9.1. Refactoring Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 9.1.1. Role Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 9.1.2. Refactoring Speci cation . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 9.1.3. Role Model Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 9.1.4. Refactoring Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 9.1.5. Custom Refactoring Extensions . . . . . . . . . . . . . . . . . . . . . . . 129 9.1.6. Pre- and Post-conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 9.1.7. Integration Into the Eclipse Refactoring Framework . . . . . . . . . . . . 130 9.2. Quality Smell Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 9.3. Co-Refactoring Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 9.3.1. Concrete Syntax of a CoRefSpec . . . . . . . . . . . . . . . . . . . . . . . 138 9.3.2. Expression Evaluation by Using an Expression Language . . . . . . . . . 138 9.3.3. UI and Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 9.4. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 10. Evaluation 143 10.1. Case Study: Reuse of Generic Refactorings in many DSLs . . . . . . . . . . . . . 143 10.1.1. Threats to validity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 10.1.2. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 10.1.3. Experience Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 10.2. Case Study: Suggestion of Valid Role Mappings . . . . . . . . . . . . . . . . . . 147 10.2.1. Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 10.2.2. Evaluation and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . 151 10.3. Proof of Concept: Co-Refactoring OWL and Ecore Models . . . . . . . . . . . . 155 10.3.1. Coupled OWL-Ecore Refactorings . . . . . . . . . . . . . . . . . . . . . 156 10.3.2. Realisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 10.3.3. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 11. Summary, Conclusion and Outlook 161 11.1. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 11.2. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 11.3. Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166 Appendix 169 A. List of Role Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 B. Comparison to Role Feature Model . . . . . . . . . . . . . . . . . . . . . . . . . 171 C. Complete List of Role Mappings . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 D. List of all IncPL Patterns for Detecting Quality Smells . . . . . . . . . . . . . . . 176 E. Post-Processor of the Extract CompositeState refactoring for UML State Machines 183 F. Speci cation of the Conference Language . . . . . . . . . . . . . . . . . . . . . . 185 List of Abbreviations 187 Bibliography 191

This study assesses how maintainability can be improved by manual and automatic refactoring strategies. Firstly, the structure of the CSS is important and CSS rules should conform to a certain order depending on their purpose. Secondly, dead code makes files unnecessarily large and more difficult to read. Removing dead code is an important step for improving maintenance. These refactoring strategies were taken from the book CSS Refactoring by Lindstrom. The refactoring strategies were tested on a large CSS code base from an ASP.NET application called AktiveraMera. The structure was manually applied by following a step by step process where each CSS rule was classified and sorted into files and folders. For example, rules styling a specific button were put in a file which is then placed in the \emph{component-styles} folder. All these separate files are then concatenated into one file which is then minimized in order to keep it small when it is later served to the user. The divided structure makes it easier for developers to add new component-, structure-, or browser-specific CSS in the correct place. It also makes it easier to keep refactoring limited and the developer knows all rules that are relevant to a certain element are kept in the same place. The new structure introduced some visual regression. It is difficult to assess how much extra time it adds if all visual regression must be remedied, but some of the changes could probably be ignored while fixing the more egregious changes. Either way, some extra work needs to be done but according to interviewed developers it would probably be worth it. The assessment is that the new structure does improve maintainability. The tool CSS-analyser was then used to find and remove duplicated CSS, a form of dead CSS code, in order to reduce the size of the CSS files. Smaller file size (fewer lines of code) is correlated to readability and by extent maintainability since it is less code to read through and understand. However, while the results did show a reduction in file size it did introduce a lot of very obvious visual regression which means a lot more work. In an industry setting there are often time constraints and if something adds more work it might not be a good strategy. The visual regression was akin to a broken website where the entire layout is changed, so it could not be ignored if it was used on the live application in question. Maintainability can be improved by introducing some structure to the CSS code in the form of a folder structure with sorted and classified CSS rules. Removing dead CSS code is difficult to do automatically without introducing website breaking visual regression. It is much more important to make sure the structure of the CSS is good than to directly try to remove dead code, especially since the structure can make other refactoring strategies more effective.

Thesis (MComm) -- University of Stellenbosch, 2001. / ENGLISH ABSTRACT: Software restructuring is a form of perfective maintenance that modifies the structure of a program's source code. lts goal is increased maintainability to better facilitate other maintenance activities, such as adding new functionality or correcting previously undetected errors. The modification of structure is achieved by applying transformations to the source code of a software system. Software engineers often attempt to restructure software by manually transforming the source code. This approach may lead to undesirable and undetectable changes in its behaviour. Ensuring that manual transformations preserve functionality during restructuring is difficult; guaranteeing it is almost impossible. One solution to the problem of manual restructuring is automation through use of a restructuring tool. The tool becomes responsible to examine each transformation and determine its impact on the software's behaviour. If a transformation preserves functionality, it may be applied to produce new source code. The tool only automates the application of transformations. The decision regarding which transformation to apply in a specific situation still resides with the maintainer. This thesis describes the design and implementation of a restructuring tool for the Oberon language, a successor of Pascal and Modula-2, under the PC Native Oberon operating system. The process of creating an adequate abstraction of a program's structure and its use to apply transformations and generate new source code are investigated. Transformations can be divided into different classes: Scoping, Syntactic, Control flow and Abstraction transformations. The restructuring tool described in this thesis contains implementations from all four classes. Informal arguments regarding the correctness of each transformation are also presented. / AFRIKAANSE OPSOMMING: Die herstrukturering van programmatuur is daarop gemik om die struktuur van 'n program se bronkode te wysig. Hierdie strukturele veranderings dien in die algemeen as voorbereiding vir meer omvangryke onderhoudsaktiwiteite, soos byvoorbeeld die toevoeging van nuwe funksionaliteit of die korrigering van foute wat voorheen verskuil was. Die verandering in struktuur word teweeggebring deur die toepassing van transformasies op die bronkode. Programmatuur-ontwikkelaars voer dikwels sulke transformasies met die hand uit. Sulke optrede kan problematies wees indien 'n transformasie die funksionaliteit, in terme van programgedrag, van die programmatuur beïnvloed. Dit is moeilik om te verseker dat bogenoemde metode funksionaliteit sal behou; om dit te waarborg is so te sê onmoontlik. 'n Oplossing vir bogenoemde probleem is die outomatisering van die herstruktureringsproses deur die gebruik van gespesialiseerde programmatuur. Hierdie programmatuur is in staat om die nodige transformasies toe te pas en terselfdertyd funksionaliteit te waarborg. Die keuse vir die toepassing van 'n spesifieke transformasie lê egter steeds by die programmeerder. Hierdie tesis bespreek die ontwerp en implementering van programmatuur om bronkode, geskryf in Oberon (die opvolger van Pascal en Modula-2), te herstruktureer. Die skep van 'n voldoende abstrakte voorstelling van bronkode, die gebruik van sodanige voorstelling in die toepassing van transformasies en die reprodusering van nuwe bronkode, word bespreek. Transformasies kan in vier breë klasse verdeel word: Bestek, Sintaks, Kontrolevloei en Abstraksie. Die programmatuur wat ontwikkel is vir hierdie tesis bevat voorbeelde uit elkeen van die voorafgenoemde klasse. Informele argumente word aangebied om die korrektheid van die onderskeie transformasies te staaf.

Refactoring is an important Software Engineering technique for improving the structure of a program after it has been written. Refactorings improve the maintainability, readability, and design of a program without affecting its external behaviour. In analogy, this thesis introduces proof refactoring to make structured, semantics preserving changes to the proof documents constructed by interactive theorem provers as part of a formal proof development. In order to formally study proof refactoring, the first part of this thesis constructs a proof language framework, Hiscript. The Hiscript framework consists of a procedural tactic language, a declarative proof language, and a modular theory language. Each level of this framework is equipped with a formal semantics based on a hierarchical notion of proof trees. Furthermore, this framework is generic as it does not prescribe an underlying logical kernel. This part contributes an investigation of semantics for formal proof documents, which is proved to construct valid proofs. Moreover, in analogy with type-checking, static well-formedness checks of proof documents are separated from evaluation of the proof. Furthermore, a subset of the SSReflect language for Coq, called eSSence, is also encoded using hierarchical proofs. Both Hiscript and eSSence are shown to have language elements with a natural hierarchical representation. In the second part, proof refactoring is put on a formal footing with a definition using the Hiscript framework. Over thirty refactorings are formally specified and proved to preserve the semantics in a precise way for the Hiscript language, including traditional structural refactorings, such as rename item, and proof specific refactorings such as backwards proof to forwards proof and declarative to procedural. Finally, a concrete, generic refactoring framework, called Polar, is introduced. Polar is based on graph rewriting and has been implemented with over ten refactorings and for two proof languages, including Hiscript. Finally, the third part concludes with some wishes for the future.