Automated refactoring to the Null Object design pattern

ContextNull-checking conditionals are a straightforward solution against null dereferences. However, their frequent repetition is considered a sign of poor program design, since they introduce source code duplication and complexity that impacts code comprehension and maintenance. The Null Object design pattern enables the replacement of null-checking conditionals with polymorphic method invocations that are bound, at runtime, to either a real object or a Null Object.ObjectiveThis work proposes a novel method for automated refactoring to Null Object that eliminates null-checking conditionals associated with optional class fields, i.e., fields that are not initialized in all class instantiations and, thus, their usage needs to be guarded in order to avoid null dereferences.MethodWe introduce an algorithm for automated discovery of refactoring opportunities to Null Object. Moreover, we specify the source code transformation procedure and an extensive set of refactoring preconditions for safely refactoring an optional field and its associated null-checking conditionals to the Null Object design pattern. The method is implemented as an Eclipse plug-in and is evaluated on a set of open source Java projects.ResultsSeveral refactoring candidates are discovered in the projects used in the evaluation and their refactoring lead to improvement of the cyclomatic complexity of the affected classes. The successful execution of the projects’ test suites, on their refactored versions, provides empirical evidence on the soundness of the proposed source code transformation. Runtime performance results highlight the potential for applying our method to a wide range of project sizes.ConclusionOur method automates the elimination of null-checking conditionals through refactoring to the Null Object design pattern. It contributes to improvement of the cyclomatic complexity of classes with optional fields. The runtime processing overhead of applying our method is limited and allows its integration to the programmer’s routine code analysis activities.     

How changes affect software entropy: an empirical study

Context Software systems continuously change for various reasons, such as adding new features, fixing bugs, or refactoring. Changes may either increase the source code complexity and disorganization, or help to reducing it. Aim This paper empirically investigates the relationship of source code complexity and disorganization—measured using source code change entropy—with four factors, namely the presence of refactoring activities, the number of developers working on a source code file, the participation of classes in design patterns, and the different kinds of changes occurring on the system, classified in terms of their topics extracted from commit notes. Method We carried out an exploratory study on an interval of the life-time span of four open source systems, namely ArgoUML, Eclipse-JDT, Mozilla, and Samba, with the aim of analyzing the relationship between the source code change entropy and four factors: refactoring activities, number of contributors for a file, participation of classes in design patterns, and change topics. Results The study shows that (i) the change entropy decreases after refactoring, (ii) files changed by a higher number of developers tend to exhibit a higher change entropy than others, (iii) classes participating in certain design patterns exhibit a higher change entropy than others, and (iv) changes related to different topics exhibit different change entropy, for example bug fixings exhibit a limited change entropy while changes introducing new features exhibit a high change entropy. Conclusions Results provided in this paper indicate that the nature of changes (in particular changes related to refactorings), the software design, and the number of active developers are factors related to change entropy. Our findings contribute to understand the software aging phenomenon and are preliminary to identifying better ways to contrast it.     

Increasing clone maintenance support by unifying clone detection and refactoring activities

ContextClone detection tools provide an automated mechanism to discover clones in source code. On the other side, refactoring capabilities within integrated development environments provide the necessary functionality to assist programmers in refactoring. However, we have observed a gap between the processes of clone detection and refactoring.ObjectiveIn this paper, we describe our work on unifying the code clone maintenance process by bridging the gap between clone detection and refactoring.MethodThrough an Eclipse plug-in called CeDAR (Clone Detection, Analysis, and Refactoring), we forward clone detection results to the refactoring engine in Eclipse. In this case, the refactoring engine is supplied with information about the detected clones to which it can then determine those clones that can be refactored. We describe the extensions to Eclipse’s refactoring engine to allow clones with additional similarity properties to be refactored.ResultsOur evaluation of open source artifacts shows that this process yields considerable increases in the instances of clone groups that may be suggested to the programmer for refactoring within Eclipse.ConclusionBy unifying the processes of clone detection and refactoring, in addition to providing extensions to the refactoring engine of an IDE, the strengths of both processes (i.e., more significant detection capabilities and an established framework for refactoring) can be garnered.     

Automated refactoring to the Strategy design pattern

ContextThe automated identification of code fragments characterized by common design flaws (or “code smells”) that can be handled through refactoring, fosters refactoring activities, especially in large code bases where multiple developers are engaged without a detailed view on the whole system. Automated refactoring to design patterns enables significant contributions to design quality even from developers with little experience on the use of the required patterns.ObjectiveThis work targets the automated identification of refactoring opportunities to the Strategy design pattern and the elimination through polymorphism of respective “code smells” that are related to extensive use of complex conditional statements.MethodAn algorithm is introduced for the automated identification of refactoring opportunities to the Strategy design pattern. Suggested refactorings comprise conditional statements that are characterized by analogies to the Strategy design pattern, in terms of the purpose and selection mode of strategies. Moreover, this work specifies the procedure for refactoring to Strategy the identified conditional statements. For special cases of these statements, a technique is proposed for total replacement of conditional logic with method calls of appropriate concrete Strategy instances. The identification algorithm and the refactoring procedure are implemented and integrated in the JDeodorant Eclipse plug-in. The method is evaluated on a set of Java projects, in terms of quality of the suggested refactorings and run-time efficiency. The relevance of the identified refactoring opportunities is verified by expert software engineers.ResultsThe identification algorithm recalled, from the projects used during evaluation, many of the refactoring candidates that were identified by the expert software engineers. Its execution time on projects of varying size confirmed the run-time efficiency of this method.ConclusionThe proposed method for automated refactoring to Strategy contributes to simplification of conditional statements. Moreover, it enhances system extensibility through the Strategy design pattern.     

Identification of refactoring opportunities introducing polymorphism

Polymorphism is one of the most important features offered by object-oriented programming languages, since it allows to extend/modify the behavior of a class without altering its source code, in accordance to the Open/Closed Principle. However, there is a lack of methods and tools for the identification of places in the code of an existing system that could benefit from the employment of polymorphism. In this paper we propose a technique that extracts refactoring suggestions introducing polymorphism. The approach ensures the behavior preservation of the code and the applicability of the refactoring suggestions based on the examination of a set of preconditions.     

Global analysis and transformations in preprocessed languages

Tool support for refactoring code written in mainstream languages such as C and C++ is currently lacking due to the complexity introduced by the mandatory preprocessing phase that forms part of the C/C++ compilation cycle. The definition and use of macros complicates the notions of scope and of identifier boundaries. The concept of token equivalence classes can be used to bridge the gap between the language proper semantic analysis and the non-preprocessed source code. The CScout toolchest uses the developed theory to analyze large interdependent program families. A Web-based interactive front end allows the precise realization of rename and remove refactorings on the original C source code. In addition, CScout can convert programs into a portable obfuscated format or store a complete and accurate representation of the code and its identifiers in a relational database.     

Identification of extract method refactoring opportunities for the decomposition of methods

The extraction of a code fragment into a separate method is one of the most widely performed refactoring activities, since it allows the decomposition of large and complex methods and can be used in combination with other code transformations for fixing a variety of design problems. Despite the significance of Extract Method refactoring towards code quality improvement, there is limited support for the identification of code fragments with distinct functionality that could be extracted into new methods. The goal of our approach is to automatically identify Extract Method refactoring opportunities which are related with the complete computation of a given variable (complete computation slice) and the statements affecting the state of a given object (object state slice). Moreover, a set of rules regarding the preservation of existing dependences is proposed that exclude refactoring opportunities corresponding to slices whose extraction could possibly cause a change in program behavior. The proposed approach has been evaluated regarding its ability to capture slices of code implementing a distinct functionality, its ability to resolve existing design flaws, its impact on the cohesion of the decomposed and extracted methods, and its ability to preserve program behavior. Moreover, precision and recall have been computed employing the refactoring opportunities found by independent evaluators in software that they developed as a golden set.     

Performance comparison of query-based techniques for anti-pattern detection

ContextProgram queries play an important role in several software evolution tasks like program comprehension, impact analysis, or the automated identification of anti-patterns for complex refactoring operations. A central artifact of these tasks is the reverse engineered program model built up from the source code (usually an Abstract Semantic Graph, ASG), which is traditionally post-processed by dedicated, hand-coded queries.ObjectiveOur paper investigates the costs and benefits of using the popular industrial Eclipse Modeling Framework (EMF) as an underlying representation of program models processed by four different general-purpose model query techniques based on native Java code, OCL evaluation and (incremental) graph pattern matching.MethodWe provide in-depth comparison of these techniques on the source code of 28 Java projects using anti-pattern queries taken from refactoring operations in different usage profiles.ResultsOur results show that general purpose model queries can outperform hand-coded queries by 2–3 orders of magnitude, with the trade-off of an increased in memory consumption and model load time of up to an order of magnitude.ConclusionThe measurement results of usage profiles can be used as guidelines for selecting the appropriate query technologies in concrete scenarios.     

Supporting requirements to code traceability through refactoring

In this paper, we hypothesize that the distorted traceability tracks of a software system can be systematically re-established through refactoring, a set of behavior-preserving transformations for keeping the system quality under control during evolution. To test our hypothesis, we conduct an experimental analysis using three requirements-to-code datasets from various application domains. Our objective is to assess the impact of various refactoring methods on the performance of automated tracing tools based on information retrieval. Results show that renaming inconsistently named code identifiers, using Rename Identifier refactoring, often leads to improvements in traceability. In contrast, removing code clones, using eXtract Method (XM) refactoring, is found to be detrimental. In addition, results show that moving misplaced code fragments, using Move Method refactoring, has no significant impact on trace link retrieval. We further evaluate Rename Identifier refactoring by comparing its performance with other strategies often used to overcome the vocabulary mismatch problem in software artifacts. In addition, we propose and evaluate various techniques to mitigate the negative impact of XM refactoring. An effective traceability sign analysis is also conducted to quantify the effect of these refactoring methods on the vocabulary structure of software systems.     

Cost-Directed Refactoring for Parallel Erlang Programs

This paper presents a new programming methodology for introducing and tuning parallelism in Erlang programs, using source-level code refactoring from sequential source programs to parallel programs written using our skeleton library, Skel. High-level cost models allow us to predict with reasonable accuracy the parallel performance of the refactored program, enabling programmers to make informed decisions about which refactorings to apply. Using our approach, we demonstrate easily obtainable, significant and scalable speedups of up to 21 on a 24-core machine over the sequential code.     

代码缺陷与代码味道的自动探测与优化研究

为了实现代码缺陷与代码味道的自动探测与优化, 提升优化与重构的效率, 设计并开发了一套名为SCORT的源代码优化与重构工具。SCORT将源代码解析为抽象语法树, 再探测其中存在的代码缺陷和代码味道, 最后对缺陷和味道进行自动优化和重构。在SCORT中已经实现了对15种常见代码缺陷和六种常见代码味道的检测以及自动优化与重构, 提供了多种代码味道的自动重构算法, 且具有良好的可扩展性。通过对三个待测项目的探测和优化实验结果表明, 对于常见代码缺陷的探测和优化, SCORT的精确率、召回率和准确率均可达100%; 对于部分常见的代码味道, SCORT尚需进一步完善。SCORT有助于开发人员提高代码质量, 减少源代码中存在的缺陷和味道。     

代码变更中抽取类重构模式的识别

在现代软件开发和维护中,重构是提高软件可维护性和软件质量的常用手段.而大量重构模式掺杂在日常的bug修复、功能增加等代码变更中,使得变更理解变得非常复杂.识别重构模式可以将重构与其它类型的代码变更隔离,利于变更理解.目前在识别重构模式的相关研究中,并没有结合变更类型和相似性比较的识别重构模式的方法及工具.为此,提出了一种基于细粒度变更类型和文本相似性比较识别重构模式的方法.将该方法应用于抽取类重构模式,并在4个开源项目中进行了实验,其平均准确率在82.6%左右.     

Identifying refactoring opportunities in object-oriented code: A systematic literature review

ContextIdentifying refactoring opportunities in object-oriented code is an important stage that precedes the actual refactoring process. Several techniques have been proposed in the literature to identify opportunities for various refactoring activities.ObjectiveThis paper provides a systematic literature review of existing studies identifying opportunities for code refactoring activities.MethodWe performed an automatic search of the relevant digital libraries for potentially relevant studies published through the end of 2013, performed pilot and author-based searches, and selected 47 primary studies (PSs) based on inclusion and exclusion criteria. The PSs were analyzed based on a number of criteria, including the refactoring activities, the approaches to refactoring opportunity identification, the empirical evaluation approaches, and the data sets used.ResultsThe results indicate that research in the area of identifying refactoring opportunities is highly active. Most of the studies have been performed by academic researchers using nonindustrial data sets. Extract Class and Move Method were found to be the most frequently considered refactoring activities. The results show that researchers use six primary existing approaches to identify refactoring opportunities and six approaches to empirically evaluate the identification techniques. Most of the systems used in the evaluation process were open-source, which helps to make the studies repeatable. However, a relatively high percentage of the data sets used in the empirical evaluations were small, which limits the generality of the results.ConclusionsIt would be beneficial to perform further studies that consider more refactoring activities, involve researchers from industry, and use large-scale and industrial-based systems.     

On the capability of static code analysis to detect security vulnerabilities

Context: Static analysis of source code is a scalable method for discovery of software faults and security vulnerabilities. Techniques for static code analysis have matured in the last decade and many tools have been developed to support automatic detection.Objective: This research work is focused on empirical evaluation of the ability of static code analysis tools to detect security vulnerabilities with an objective to better understand their strengths and shortcomings.Method: We conducted an experiment which consisted of using the benchmarking test suite Juliet to evaluate three widely used commercial tools for static code analysis. Using design of experiments approach to conduct the analysis and evaluation and including statistical testing of the results are unique characteristics of this work. In addition to the controlled experiment, the empirical evaluation included case studies based on three open source programs.Results: Our experiment showed that 27% of C/C++ vulnerabilities and 11% of Java vulnerabilities were missed by all three tools. Some vulnerabilities were detected by only one or combination of two tools; 41% of C/C++ and 21% of Java vulnerabilities were detected by all three tools. More importantly, static code analysis tools did not show statistically significant difference in their ability to detect security vulnerabilities for both C/C++ and Java. Interestingly, all tools had median and mean of the per CWE recall values and overall recall across all CWEs close to or below 50%, which indicates comparable or worse performance than random guessing. While for C/C++ vulnerabilities one of the tools had better performance in terms of probability of false alarm than the other two tools, there was no statistically significant difference among tools’ probability of false alarm for Java test cases.Conclusions: Despite recent advances in methods for static code analysis, the state-of-the-art tools are not very effective in detecting security vulnerabilities.     

Identification of generalization refactoring opportunities

Generalization refactoring helps relate classes and share functions, including both interfaces and implementation, by inheritance. To apply generalization refactoring, developers should first identify potential generalization refactoring opportunities, i.e., software entities that might benefit from generalization refactoring. For non-trivial software systems, manual identification of these opportunities is challenging and time-consuming. However, to the best of our knowledge, no existing tools have been specifically designed for this task. As a result, people have to identify these opportunities manually or with the help of tools designed for other purposes, e.g., clone detectors. To this end, we propose a tool GenReferee (Generalization Referee) to identify potential refactoring opportunities according to conceptual relationship, implementation similarity, structural correspondence, and inheritance hierarchies. It was first calibrated on two non-trivial open source applications, and then evaluated on another three. Evaluation results suggest that the proposed approach is effective and efficient.     

Recovering test-to-code traceability using slicing and textual analysis

Test suites are a valuable source of up-to-date documentation as developers continuously modify them to reflect changes in the production code and preserve an effective regression suite. While maintaining traceability links between unit test and the classes under test can be useful to selectively retest code after a change, the value of having traceability links goes far beyond this potential savings. One key use is to help developers better comprehend the dependencies between tests and classes and help maintain consistency during refactoring. Despite its importance, test-to-code traceability is not common in software development and, when needed, traceability information has to be recovered during software development and evolution. We propose an advanced approach, named SCOTCH+ (Source code and COncept based Test to Code traceability Hunter), to support the developer during the identification of links between unit tests and tested classes. Given a test class, represented by a JUnit class, the approach first exploits dynamic slicing to identify a set of candidate tested classes. Then, external and internal textual information associated with the classes retrieved by slicing is analyzed to refine this set of classes and identify the final set of candidate tested classes. The external information is derived from the analysis of the class name, while internal information is derived from identifiers and comments. The approach is evaluated on five software systems. The results indicate that the accuracy of the proposed approach far exceeds the leading techniques found in the literature.     

A robust multi-objective approach to balance severity and importance of refactoring opportunities

Refactoring large systems involves several sources of uncertainty related to the severity levels of code smells to be corrected and the importance of the classes in which the smells are located. Both severity and importance of identified refactoring opportunities (e.g. code smells) are difficult to estimate. In fact, due to the dynamic nature of software development, these values cannot be accurately determined in practice, leading to refactoring sequences that lack robustness. In addition, some code fragments can contain severe quality issues but they are not playing an important role in the system. To address this problem, we introduced a multi-objective robust model, based on NSGA-II, for the software refactoring problem that tries to find the best trade-off between three objectives to maximize: quality improvements, severity and importance of refactoring opportunities to be fixed. We evaluated our approach using 8 open source systems and one industrial project, and demonstrated that it is significantly better than state-of-the-art refactoring approaches in terms of robustness in all the experiments based on a variety of real-world scenarios. Our suggested refactoring solutions were found to be comparable in terms of quality to those suggested by existing approaches, better prioritization of refactoring opportunities and to carry an acceptable robustness price.     

Rank-based refactoring decision support: two studies

Refactoring can result in code with improved maintainability and is considered a preventive maintenance activity. Managers of large projects need ways to decide where to apply scarce resources when performing refactoring. There is a lack of tools for supporting such decisions. We introduce a rank-based software measure-driven refactoring decision support approach to assist managers. The approach uses various static measures to develop a weighted rank, ranking classes or packages that need refactoring. We undertook two case studies to examine the effectiveness of the approach. Specifically, we wanted to see if the decision support tool yielded results similar to those of human analysts/managers and in less time so that it can be used to augment human decision making. In the first study, we found that our approach identified classes as needing refactoring that were also identified by humans. In the second study, a hierarchical approach was used to identify packages that had actually been refactored in 15 releases of the open source project Tomcat. We examined the overlap between the tool’s findings and the actual refactoring activities. The tool reached 100/86.7% recall on the package/class level. Though these studies were limited in size and scope, it appears that this approach is worthy of further examination.     

On Paper

This paper tries to devise an algorithm for analyzing initializers for C arrays and structures. The CScout refactoring browser is used to look for possible differences between closed and open source code. Unlike the other code bases, Sun's code didn't appear to use any exotic compiler extensions, so CScout uncomplainingly devoured one file after the next. Then, after approximately six hours of processing and 80 percent along the way, it reported a syntax error. Most errors encountered when processing C code with CScout are easy to handle. A macro definition is added to simulate a compiler built-in-function.     

Evolving Object-Oriented Designs with Refactorings

Refactorings are behavior-preserving program transformations that automate design evolution in object-oriented applications. Three kinds of design evolution are: schema transformations, design pattern microarchitectures, and the hot-spot-driven-approach. This research shows that all three are automatable with refactorings. A comprehensive list of refactorings for design evolution is provided and an analysis of supported schema transformations, design patterns, and hot-spot meta patterns is presented. Further, we evaluate whether refactoring technology can be transferred to the mainstream by restructuring non-trivial C++ applications. The applications that we examine were evolved manually by software engineers. We show that an equivalent evolution could be reproduced significantly faster and cheaper by applying a handful of general-purpose refactorings. In one application, over 14K lines of code were transformed automatically that otherwise would have been coded by hand. Our experiments identify benefits, limitations, and topics of further research related to the transfer of refactoring technology to a production environment.