A manutenção é uma fase do ciclo de vida do software reconhecida por demandar uma grande quantidade de esforço em comparação às outras, como o desenvolvimento. As tarefas da manutenção envolvem a modificação do software, mais especificamente os artefatos que o compõe. O fato de modificar um determinado artefato pode afetar outras partes do software, cujo fenômeno é conhecido como impacto de mudança. Técnicas e ferramentas para apoiar a análise de impacto de mudança geralmente são baseadas em tipos de acoplamentos e têm sido propostas por diversos trabalhos na literatura, como as Regras de Associação e Aprendizado de Máquina usando Classificação. No entanto, essas técnicas não foram avaliadas do ponto de vista prático. Motivado pela falta de uma avaliação dessa perspectiva, esse trabalho realizou um experimento com uma ferramenta que implementa tais técnicas. Para tanto, foi desenvolvida uma ferramenta para automatizar a execução dessas técnicas para realizar predição de mudanças conjuntas de artefatos e apresentá-las ao desenvolvedor, além de coletar o feedback dos desenvolvedores na ferramenta. Com a ferramenta desenvolvida, foi realizada uma prova de conceito com o uso da ferramenta em tarefas de manutenção (defeitos) do projeto de software livre da Apache denominado CXF, por colaboradores novatos representados pelos alunos do curso de Ciência da Computação. Apesar de depender do desempenho das técnicas de predição de mudanças conjuntas, os resultados mostraram evidências que a ferramenta pode apoiar colaboradores novatos e, também, diminuir o esforço para realizar uma tarefa de manutenção de software, comparando quando nenhuma técnica é usada. / Maintenance is a stage of the software life cycle recognized by demanding a lot of effort in comparison to others, such as development. The maintenance tasks involve software modification, specifically the artifacts that compose it. Modifying a particular artifact can affect other parts of the software. This phenomenon is known as change impact. Techniques and tools to support the change impact analysis are usually based on types of couplings and have been proposed by several studies in the literature, such as the Association Rules and Machine Learning using Classification. However, these techniques have not been evaluated from the practical point of view. Therefore, a tool was developed to automate the execution of these techniques to predict joint changes of artifacts and present them to the developer, as well as collecting developers’ feedback on the tool. With the developed tool, a proof of concept was performed using the tool in maintenance tasks (bugs) of the Apache free software project called CXF, by novice collaborators represented by the students of the Computer Science course. Although it depends on the performance of joint change prediction techniques, the results showed evidence that the tool can support novice collaborators and also decrease the effort to perform a software maintenance task, comparing when no technique is used.

L’existence de plusieurs copies d’un même fragment de code (nommées des clones dans lalittérature) dans un logiciel peut compliquer sa maintenance et son évolution. La duplication decode peut poser des problèmes de consistance, notamment lors de la propagation de correction debogues. La détection de clones est par conséquent un enjeu important pour préserver et améliorerla qualité logicielle, propriété primordiale pour le succès d’un logiciel.L’objectif général de cette thèse est de contribuer à l’usage des détecteurs de clones dans destâches de maintenance logicielle. Nous avons centré nos contributions sur deux axes de recherche.Premièrement, la méthodologie pour comparer et évaluer les détecteurs de clones, i.e. les benchmarksde clones. Nous avons empiriquement évalué un benchmark de clones et avons montré queles résultats dérivés de ce dernier n’étaient pas fiables. Nous avons également identifié des recommandationspour fiabiliser la construction de benchmarks de clones. Deuxièmement, la spécialisationdes détecteurs de clones dans des tâches de maintenance logicielle.Nous avons développé uneapproche spécialisée dans un langage et une tâche (la réingénierie) qui permet aux développeursd’identifier et de supprimer la duplication de code de leurs logiciels. Nous avons mené des étudesde cas avec des experts du domaine pour évaluer notre approche. / The existence of several copies of a same code fragment—called code clones in the literature—in a software can complicate its maintenance and evolution. Code duplication can lead to consistencyproblems, especially during bug fixes propagation. Code clone detection is therefore a majorconcern to maintain and improve software quality, which is an essential property for a software’ssuccess.The general objective of this thesis is to contribute to the use of code clone detection in softwaremaintenance tasks. We chose to focus our contributions on two research topics. Firstly, themethodology to compare and assess code clone detectors, i.e. clone benchmarks. We perform anempirical assessment of a clone benchmark and we found that results derived from this latter arenot reliable. We also identified recommendations to construct more reliable clone benchmarks.Secondly, the adaptation of code clone detectors in software maintenance tasks. We developed aspecialized approach in one language and one task—refactoring—allowing developers to identifyand remove code duplication in their softwares. We conducted case studies with domain experts toevaluate our approach.

As formigas são criaturas fascinantes que, além dos avanços na biologia também inspiraram pesquisas sobre teoria da informação. Em particular, o estudo resultou na criação da Teoria da Forragem de Informação, que descreve como os agentes de buscam informações em seu ambiente. Esta teoria também explica fenômenos recentes e bem-sucedidos, como crowd sourcing. Crowdsourcing tem sido aplicado a muitas atividades em engenharia de software, incluindo desenvolvimento, tradução e testes, mas uma atividade parece resistir: depuração. No entanto, os desenvolvedores sabem que a depuração pode exigir dedicação, esforço, longas horas de trabalho, por vezes, para mudar uma linha de código único. Nós introduzimos o conceito de Depuração em Enxame, para trazer crowd sourcing para a atividade de depuração. Através de crowd sourcing, pretendemos ajudar os desenvolvedores, capitalizando a sua dedicação, esforço e longas horas de trabalho para facilitar atividades de depuração. Mostramos que a depuração enxame requer uma abordagem específica para recolher informações relevantes, e descrevemos sua infra-estrutura. Mostramos também que a depuração em enxame pode reduzir o esforço desenvolvedores. Concluímos com as vantagens e limitações atuais de depuração enxame, e sugerir caminhos para superar estas limitações e ainda mais a adoção de crowd sourcing para atividades de depuração. / Ants are fascinating creatures that beyond the advances in biology have also inspired research on information theory. In particular, their study resulted in the creation of the Information Foraging Theory, which describes how agents forages for information in their environment. This theory also explains recent and fruitful phenomena, such as crowdsourcing. Many activities in software engineering have applied crowdsourcing, including development, translation, and testing, but one action seems to resist: debugging. Developers know that debugging can require dedication, effort, long hours of work, sometimes for changing one line of code only. We introduce the concept of Swarm Debugging, to bring crowdsourcing to the activity of debugging. Through crowdsourcing, we aim at helping developers by capitalizing on their dedication, effort, and long hours of work to ease debugging activities of their peers or theirs, on other bugs. We show that swarm debugging requires a particular approach to collect relevant information, and we describe the Swarm Debugging Infrastructure. We also show that swarm debugging minimizes developers effort. We conclude with the advantages and current limitations of swarm debugging and suggest directions to overcome these limitations and further the adoption of crowdsourcing for debugging activities.

Thesis (MTech (Information Technology))--Cape Peninsula University of Technology, 2016. / Software often requires patches to be installed post-implementation for a variety of reasons. Organisations and individuals, however, do not always promptly install these patches as and when they are released. This study investigated the reasons for the delay or hesitation, identified the challenges, and proposed a model that could assist organisations in overcoming the identified challenges. The research investigated the extent to which the integration of software patch management and enterprise data security is an important management responsibility, by reviewing relevant documents and interviewing key role players currently involved in the patch management process. The current challenges and complexities involved in patch management at an enterprise level could place organisations at risk by compromising their enterprise-data security. This research primarily sought to identify the challenges causing the management of software patches to be complex, and further attempted to establish how organisations currently implement patch management. The aim of the study was to explore the complexities of software patch management in order to enhance enterprise data security within organisations. A single case study was used, and data were obtained from primary sources and literature. The study considered both technological and human factors, and found that both factors play an equally important role with regard to the successful implementation of a patch management program within an organisation.

As formigas são criaturas fascinantes que, além dos avanços na biologia também inspiraram pesquisas sobre teoria da informação. Em particular, o estudo resultou na criação da Teoria da Forragem de Informação, que descreve como os agentes de buscam informações em seu ambiente. Esta teoria também explica fenômenos recentes e bem-sucedidos, como crowd sourcing. Crowdsourcing tem sido aplicado a muitas atividades em engenharia de software, incluindo desenvolvimento, tradução e testes, mas uma atividade parece resistir: depuração. No entanto, os desenvolvedores sabem que a depuração pode exigir dedicação, esforço, longas horas de trabalho, por vezes, para mudar uma linha de código único. Nós introduzimos o conceito de Depuração em Enxame, para trazer crowd sourcing para a atividade de depuração. Através de crowd sourcing, pretendemos ajudar os desenvolvedores, capitalizando a sua dedicação, esforço e longas horas de trabalho para facilitar atividades de depuração. Mostramos que a depuração enxame requer uma abordagem específica para recolher informações relevantes, e descrevemos sua infra-estrutura. Mostramos também que a depuração em enxame pode reduzir o esforço desenvolvedores. Concluímos com as vantagens e limitações atuais de depuração enxame, e sugerir caminhos para superar estas limitações e ainda mais a adoção de crowd sourcing para atividades de depuração. / Ants are fascinating creatures that beyond the advances in biology have also inspired research on information theory. In particular, their study resulted in the creation of the Information Foraging Theory, which describes how agents forages for information in their environment. This theory also explains recent and fruitful phenomena, such as crowdsourcing. Many activities in software engineering have applied crowdsourcing, including development, translation, and testing, but one action seems to resist: debugging. Developers know that debugging can require dedication, effort, long hours of work, sometimes for changing one line of code only. We introduce the concept of Swarm Debugging, to bring crowdsourcing to the activity of debugging. Through crowdsourcing, we aim at helping developers by capitalizing on their dedication, effort, and long hours of work to ease debugging activities of their peers or theirs, on other bugs. We show that swarm debugging requires a particular approach to collect relevant information, and we describe the Swarm Debugging Infrastructure. We also show that swarm debugging minimizes developers effort. We conclude with the advantages and current limitations of swarm debugging and suggest directions to overcome these limitations and further the adoption of crowdsourcing for debugging activities.

Context: Over the last two decades, software architecture has introduced a new trend insoftware development. This new trend has completely changed the normal methods andpractices of software engineering. The focus has become the architectural elements ratherthan code and sub-routines. Architecture description languages (ADLs) have been proposedfor this kind of architecture based software development. There are a number of differentADLs both in academia and industry; they are not totally adopted by the software engineeringcommunity, but they are not avoided either. In this research work, an investigation has beenperformed based on the ADLs evaluation in practice. Objectives: The main aim of this study is to investigate evaluation of ADLs in academia andindustry. To explore the benefits and drawbacks of ADLs in practice. The study also exploresthe different quality factors improved by ADLs. Further different methods used to buildarchitecture with ADLs and then how to use architecture described with an ADL in softwaredevelopment and maintenance have also been reported. Methods: This research study has been carried out using the systematic literature reviewmethod. The systematic literature review follows the guidelines suggested by Kitchenham[21]. Results: This research review has resulted in total of 102 different ADLs. It has been foundthat out of the 102 different ADLs, 69 ADLs have been evaluated in academia and only 33ADLs have been evaluated in industry. ADLs have also been classified based on theirindustrial and academia evaluation. There are total 31 different benefits and 19 differentdrawbacks of ADLs have been identified. This review also extracted 20 different qualityfactors from literature that are improved by using ADLs in practice. Further 13 differentmethods used to build architecture with ADL have also been reported. Finally 9 differentmethods of ADLs used in software development and maintenance have been identified. Conclusions: The Large number of ADLs with little evaluation in industry suggests thatmore work needs to be done in order to improve ADLs evaluation in practice. ADLs providemore benefits compared to their drawbacks which suggests that ADLs can be very beneficial.Knowledge gained during this research study, suggests that ADLs are mostly unrecognized.More awareness about ADLs should be provided in education and practice.

The need of change is essential for a software system to reside longer in the market. Change implementation is only done through the maintenance and successful software maintenance gives birth to a new software release that is a refined form of the previous one. This phenomenon is known as the evolution of the software. To transfer software from lower to upper or better form, maintainers have to get familiar with the particular aspects of software i.e. source code and documentation. Due to the poor quality of documentation maintainers often have to rely on source code. So, thorough understanding of source code is necessary for effective change implementation. This study explores the code comprehension problems discussed in the literature and prioritizes them according to their severity level given by maintenance personnel in the industry. Along with prioritizing the problems, study also presents the maintenance personnel suggested methodologies for improving code comprehension. Consideration of these suggestions in development might help in shortening the maintenance and evolution time. / Usman Akhlaq Mirpur, Azad Kashmir, Pakistan Muhammad Usman Yousaf Bhimber, Azad Kashmir, Pakistan

One of the inevitable negative effects of software evolution is design erosion. Refactoring is a technique that aims at counteracting this phenomenon by successively improving the design of software without changing its observable behaviour. Design erosion occurs also in the context of executable UML models, i.e. models that are detailed enough to be automatically compiled to executable applications. This thesis presents results of a study on applying refactoring to the area of maintenance of executable UML models. It contains an overview of recent approaches to UML model refactoring and to executable modelling, followed by identification of refactoring areas in models built in Telelogic TAU, a state-of-the art UML CASE tool. It proposes a systematic approach to specification of both executable UML model refactorings as well as associated bad smells in models. Additionally, it shows how refactorings can be implemented in Telelogic TAU.

This master thesis was performed in cooperation with SchlumbergerSema. During the project we identified several maintenance methodologies and studied the characteristics of both the ISO and IEEE standard. The base for our evaluation of the CURE maintenance model (developed by SchlumbergerSema) were both the result of our case study that comprised interviews from five maintenance projects as well as maintenance literature available. Both the interviews and the literature studies resulted in lists of requirements that each area make on a maintenance model. We compare the CURE model to the requirements found within these two areas. Based on the result of the comparison we give our recommendations for maintenance in general, maintenance within SchlumbergerSema as well as specific recommendations for the CURE development team. Our conclusions drawn from our work were mostly positive about CURE. However we have suggested several issues for further development such as e.g. certification to a standard. Other conclusions are that no matter what model you choose as a maintenance model, make sure that you implement the model fully. A major pitfall is to allow it to become "just a fancy book on the shelf". / Erik Björling - erik@bjorling.com Anna Hoff - pt97hol@student.bth.se

Due to improved computing power, connectivity and interaction capability of mobile devices, their popularity and general acceptance in mass population has increased in recent years. Mobile applications are software systems running on mobile hand-held devices such as smart phones and tablets. Due to obvious differences in mobile applications, the evolution studies on them is of high importance. The primary objective is to study and compare the mobile applications evolution with the Lehman's laws of software evolution. Next is to identify and report how the software development team size influences mobile applications evolution. The study is conducted on 9 different open source mobile applications among which 5 were developed by single core developer and 4 were developed by multiple core developers. The selected projects' code repository is cloned into local copy and a number of tools are used on those repositories for extraction of relevant metrics from the artifacts. The Lehman laws are tested graphically, analytically and in some cases statistically. Six of the Lehman's laws are tested for validation in sample mobile applications. Among the six laws, I-Continuing Change is found supportive, III-Self Regulation and VI-Continuing Growth are found partial supportive in mobile applications. The II-Increasing complexity and V-Conservation of Familiarity are inconclusive. The IV-Conservation of Organizational Stability is not supportive in our sample mobile applications. Moreover, mobile applications are developed by a single or a few developers. Small team mobile projects have less time between releases compared to large team projects. The growth pattern of mobile applications is different than that predicted by Lehman laws.