Studying Late Propagations in Code Clone Evolution Using Software Repository Mining

In the code clone evolution community, the Late Propagation (LP) has been identified as one of the clone evolution patterns that can potentially lead to software defects. An LP occurs when instances of a clone pair are changed consistently, but not at the same time. The clone instance, which receives the update at a later time, might exhibit unintended behavior if the modification was a bugfix. In this paper, we present an approach to extract LPs from software repositories. Subsequently, we study LPs in four software systems, which allows us to investigate the propagation time, the clone dispersion and the effects of LPs on the software

An approach to safely evolve preprocessor-based C program families.

Desde os anos 70, o pré-processador C é amplamente utilizado na prática para adaptar sistemas para diferentes plataformas e cenários de aplicação. Na academia, no entanto, o pré-processador tem recebido fortes críticas desde o início dos anos 90. Os pesquisadores têm criticado a sua falta de modularidade, a sua propensão para introduzir erros sutis e sua ofuscação do código fonte. Para entender melhor os problemas de usar o pré-processador C,considerando a percepção dos desenvolvedores, realizamos 40 entrevistas e uma pesquisa entre 202 desenvolvedores. Descobrimos que os desenvolvedores lidam com três problemas comuns na prática: erros relacionados à configuração, testes combinatórios e compreensão do código. Os desenvolvedores agravam estes problemas ao usar diretivas não disciplinadas, as quais não respeitam a estrutura sintática do código. Para evoluir famílias de programas de forma segura, foram propostas duas estratégias para a detecção de erros relacionados à configuração e um conjunto de 14 refatoramentos para remover diretivas não disciplinadas. Para lidar melhor com a grande quantidade de configurações do código fonte, a primeira estratégia considera todo o conjunto de configurações do código fonte e a segunda estratégia utiliza amostragem. Para propor um algoritmo de amostragem adequado, foram comparados 10 algoritmos com relação ao esforço (número de configurações para testar) e capacidade de detecção de erros (número de erros detectados nas configurações da amostra). Com base nos resultados deste estudo, foi proposto um algoritmo de amostragem. Estudos empíricos foram realizados usando 40 sistemas C do mundo real. Detectamos 128 erros relacionados à configuração, enviamos 43 correções para erros ainda não corrigidos e os desenvolvedores aceitaram 65% das correções. Os resultados de nossa pesquisa mostram que a maioria dos desenvolvedores preferem usar a versão refatorada,ou seja,disciplinada do código fonte,ao invés do código original com as diretivas não disciplinadas. Além disso,os desenvolvedores aceitaram 21 (75%) das 28 sugestões enviadas para transformar diretivas não disciplinadas em disciplinadas. Nossa pesquisa apresenta resultados úteis para desenvolvedores de código C durante suas tarefas de desenvolvimento, contribuindo para minimizar o número de erros relacionados à configuração, melhorar a compreensão e a manutenção do código fonte e orientar os desenvolvedores para realizar testes combinatórios.Since the 70s, the C preprocessor is still widely used in practice in a numbers of projects, including Apache,Linux ,and Libssh, totail or systems to different platforms and application scenarios. In academia,however, the preprocess or has received strong critic is msinceatl east the early 90s. Researchers have criticized its lack of separation of concerns, its proneness to introduce subtle errors, and its obfuscation of the source code. To better understand the problems of using the C preprocessor, taking the perception of developers into account, we conducted 40 interviewsandasurveyamong 202 developers. We found that developers deal with three common problems in practice: configuration-related bugs, combinatorial testing, and code comprehension. Developers aggravate these problems when using undisciplined directives (i.e., bad smells regarding preprocessor use), which are preprocessor directives thatdo notrespect thesyntactic structureof thesource code. To safely evolve preprocessor based program families, we proposed strategies to detect configuration-relatedbugs and bad smells, and a set of 14 refactorings to remove bad smells. To better deal with exponential configuration spaces, our strategies uses variability-aware analysis that considers the entire set of possible configurations, and sampling, which allows to reuse C tools that consider only one configuration at a time to detect bugs. To propose a suitable sampling algorithm, we compared 10 algorithms with respect to effort (i.e., number of configurations to test) andbug-detection capabilities (i.e.,numberofbugs detected in the sampled configurations). Based on the results, we proposed a sampling algorithm with an useful balance between effort and bug-detection capability. We performed empirical studies using a corpus of 40 C real-world systems. We detected 128 configuration-related bugs, submitted 43 patches to fix bugs not fixed yet, and developers accepted 65% of the patches. The results of our survey show that most developers prefer to use the refactored (i.e., disciplined) version of the code instead of the original code with undisciplined directives. Furthermore, developers accepted 21 (75%) out of 28 patches submitted to refactor undisciplined into disciplined directives. Our work presents useful findings for C developers during their development tasks, contributing to minimize the chances of introducing configuration-related bugs and bad smells, improve code comprehension, and guide developers to perform combinatorial testing

Analysis on a release history database to assist management of the software maintenance

Software maintenance is the most time consuming activity in the life cycle of software. Software maintenance suffers from missed deadlines and from being over budget. Managers usually pay more attention to development than to maintenance: for example, they prefer to assign senior developers to the development phase tasks and neglect maintenance ones. Managers have difficulty identifying problems, and their causes, in maintenance. This thesis presents techniques for analysis on the proposed release history database to provide metrics for improvement of the maintenance phase. The proposed release history database is enriched by valuable data that comes from an issue tracking system, code repository, and time entry system. The proposed release history database and the analysis of the data contained there provides metrics which allow maintainers to find risky and time consuming codes, recommending maintenance team and maintenance location and a suggestions for the future of the maintenance. Automation is also provided as a proof of concept through a prototypical tool

Fundamental Approaches to Software Engineering

This open access book constitutes the proceedings of the 25th International Conference on Fundamental Approaches to Software Engineering, FASE 2022, which was held during April 4-5, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 17 regular papers presented in this volume were carefully reviewed and selected from 64 submissions. The proceedings also contain 3 contributions from the Test-Comp Competition. The papers deal with the foundations on which software engineering is built, including topics like software engineering as an engineering discipline, requirements engineering, software architectures, software quality, model-driven development, software processes, software evolution, AI-based software engineering, and the specification, design, and implementation of particular classes of systems, such as (self-)adaptive, collaborative, AI, embedded, distributed, mobile, pervasive, cyber-physical, or service-oriented applications

Fundamental Approaches to Software Engineering

This open access book constitutes the proceedings of the 25th International Conference on Fundamental Approaches to Software Engineering, FASE 2022, which was held during April 4-5, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 17 regular papers presented in this volume were carefully reviewed and selected from 64 submissions. The proceedings also contain 3 contributions from the Test-Comp Competition. The papers deal with the foundations on which software engineering is built, including topics like software engineering as an engineering discipline, requirements engineering, software architectures, software quality, model-driven development, software processes, software evolution, AI-based software engineering, and the specification, design, and implementation of particular classes of systems, such as (self-)adaptive, collaborative, AI, embedded, distributed, mobile, pervasive, cyber-physical, or service-oriented applications

Studying the lives of software bugs

For as long as people have made software, they have made mistakes in that software. Software bugs are widespread, and the maintenance required to fix them has a major impact on the cost of software and how developers' time is spent. Reducing this maintenance time would lower the cost of software and allow for developers to spend more time on new features, improving the software for end-users. Bugs are hugely diverse and have a complex life cycle. This makes them difficult to study, and research is often carried out on synthetic bugs or toy programs. However, a better understanding of the bug life cycle would greatly aid in developing tools to reduce the time spent on maintenance. This thesis will study the life cycle of bugs, and develop such an understanding. Overall, this thesis examines over 3000 real bugs, from real projects, concentrating on three of the most important points in the life cycle: origin, reporting and fix. Firstly, two existing techniques are compared for discovering the origin of a bug. A number of improvements are evaluated, and the most effective approach is found to be combining the techniques. Furthermore, the behaviour of developers is found to have a major impact on the accuracy of the techniques. Secondly, a large number of bugs are analysed to determine what information is provided when users report bugs. For most bugs, much important information is missing, or inaccurate. Most importantly, there appears to be a considerable gap between what users provide and what developers actually want. Finally, an evaluation is carried out on a number of novel alterations to techniques used to determine the location of bug fixes. Compared to existing techniques, these alterations successfully increase the number of bugs which can be usefully localised, aiding developers in removing the bugs.For as long as people have made software, they have made mistakes in that software. Software bugs are widespread, and the maintenance required to fix them has a major impact on the cost of software and how developers' time is spent. Reducing this maintenance time would lower the cost of software and allow for developers to spend more time on new features, improving the software for end-users. Bugs are hugely diverse and have a complex life cycle. This makes them difficult to study, and research is often carried out on synthetic bugs or toy programs. However, a better understanding of the bug life cycle would greatly aid in developing tools to reduce the time spent on maintenance. This thesis will study the life cycle of bugs, and develop such an understanding. Overall, this thesis examines over 3000 real bugs, from real projects, concentrating on three of the most important points in the life cycle: origin, reporting and fix. Firstly, two existing techniques are compared for discovering the origin of a bug. A number of improvements are evaluated, and the most effective approach is found to be combining the techniques. Furthermore, the behaviour of developers is found to have a major impact on the accuracy of the techniques. Secondly, a large number of bugs are analysed to determine what information is provided when users report bugs. For most bugs, much important information is missing, or inaccurate. Most importantly, there appears to be a considerable gap between what users provide and what developers actually want. Finally, an evaluation is carried out on a number of novel alterations to techniques used to determine the location of bug fixes. Compared to existing techniques, these alterations successfully increase the number of bugs which can be usefully localised, aiding developers in removing the bugs

Time evolution and distribution analysis of software bugs from a complex network perspective

Successful software systems are constantly under development. Since they have to be updated when new features are introduced, bug are fixed and the system is kept up to date, they require a continuous maintenance. Among these activities the bug fixing is one of themost relevant, because it is determinant for software quality. Unfortunately, software houses have limited time and developers to address all these issues before the product delivery. For this reason, an efficient allocation of these resources is required to obtain the quality required by the market. The keyword for a correct management of software product process is measure. As De-Marco states “you cannot control what you cannot measure”, and this thesis is mainly devoted to this aspect. This dissertation bears with software measures related to bug proneness and distribution analysis of software bugs. The aim is to describe the bug occurrence phenomena, identify useful metrics related to software bugs proneness and finally to characterize how bug population is distributed and evolve, discussing also the model able to explain this evolution. Studying the relationship between code evolution and bug distribution or bug-proneness, we foresee which software structure will come out. Thus, this research provides information and guidelines tomanagers, helping them to plan, schedule activities and allocate resources, during software development