116 research outputs found
RefDiff: Detecting Refactorings in Version Histories
Refactoring is a well-known technique that is widely adopted by software
engineers to improve the design and enable the evolution of a system. Knowing
which refactoring operations were applied in a code change is a valuable
information to understand software evolution, adapt software components, merge
code changes, and other applications. In this paper, we present RefDiff, an
automated approach that identifies refactorings performed between two code
revisions in a git repository. RefDiff employs a combination of heuristics
based on static analysis and code similarity to detect 13 well-known
refactoring types. In an evaluation using an oracle of 448 known refactoring
operations, distributed across seven Java projects, our approach achieved
precision of 100% and recall of 88%. Moreover, our evaluation suggests that
RefDiff has superior precision and recall than existing state-of-the-art
approaches.Comment: Paper accepted at 14th International Conference on Mining Software
Repositories (MSR), pages 1-11, 201
Refactoring smelly spreadsheet models
Identifying bad design patterns in software is a successful and inspiring research trend. While these patterns do not necessarily correspond to software errors, the fact is that they raise potential problematic issues, often referred to as code smells, and that can for example compromise maintainability or evolution. The identification of code smells in spreadsheets, which can be viewed as software development environments for non-professional programmers, has already been the subject of confluent researches by different groups. While these research groups have focused on detecting smells on concrete spreadsheets, or spreadsheet instances, in this paper we propose a comprehensive set of smells for abstract representations of spreadsheets, or spreadsheet models. We also propose a set of refactorings suggesting how spreadsheet models can become simpler to understand, manipulate and evolve. Finally we present the integration of both smells and refactorings under the MDSheet framework.Part funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia within projects FCOMP-01-0124-FEDER-022701 and Network Sensing for Critical Systems Monitoring (NORTE-01-0124-FEDER-000058), ref. BIM-2013 BestCase RL3.2 UMINHO
30 Years of Software Refactoring Research:A Systematic Literature Review
Due to the growing complexity of software systems, there has been a dramatic
increase and industry demand for tools and techniques on software refactoring
in the last ten years, defined traditionally as a set of program
transformations intended to improve the system design while preserving the
behavior. Refactoring studies are expanded beyond code-level restructuring to
be applied at different levels (architecture, model, requirements, etc.),
adopted in many domains beyond the object-oriented paradigm (cloud computing,
mobile, web, etc.), used in industrial settings and considered objectives
beyond improving the design to include other non-functional requirements (e.g.,
improve performance, security, etc.). Thus, challenges to be addressed by
refactoring work are, nowadays, beyond code transformation to include, but not
limited to, scheduling the opportune time to carry refactoring, recommendations
of specific refactoring activities, detection of refactoring opportunities, and
testing the correctness of applied refactorings. Therefore, the refactoring
research efforts are fragmented over several research communities, various
domains, and objectives. To structure the field and existing research results,
this paper provides a systematic literature review and analyzes the results of
3183 research papers on refactoring covering the last three decades to offer
the most scalable and comprehensive literature review of existing refactoring
research studies. Based on this survey, we created a taxonomy to classify the
existing research, identified research trends, and highlighted gaps in the
literature and avenues for further research.Comment: 23 page
30 Years of Software Refactoring Research: A Systematic Literature Review
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155872/4/30YRefactoring.pd
Towards a catalog of spreadsheet smells
Spreadsheets are considered to be the most widely used programming language in the world, and reports have shown that 90% of real-world spreadsheets contain errors. In this work, we try to identify spreadsheet smells, a concept adapted from software, which consists of a surface indication that usually corresponds to a deeper problem. Our smells have been integrated in a tool, and were computed for a large spreadsheet repository. Finally, the analysis of the results we obtained led to the refinement of our initial catalog
Toward an Effective Automated Tracing Process
Traceability is defined as the ability to establish, record, and maintain dependency relations among various software artifacts in a software system, in both a forwards and backwards direction, throughout the multiple phases of the project’s life cycle. The availability of traceability information has been proven vital to several software engineering activities such as program comprehension, impact analysis, feature location, software reuse, and verification and validation (V&V). The research on automated software traceability has noticeably advanced in the past few years. Various methodologies and tools have been proposed in the literature to provide automatic support for establishing and maintaining traceability information in software systems. This movement is motivated by the increasing attention traceability has been receiving as a critical element of any rigorous software development process. However, despite these major advances, traceability implementation and use is still not pervasive in industry. In particular, traceability tools are still far from achieving performance levels that are adequate for practical applications. Such low levels of accuracy require software engineers working with traceability tools to spend a considerable amount of their time verifying the generated traceability information, a process that is often described as tedious, exhaustive, and error-prone. Motivated by these observations, and building upon a growing body of work in this area, in this dissertation we explore several research directions related to enhancing the performance of automated tracing tools and techniques. In particular, our work addresses several issues related to the various aspects of the IR-based automated tracing process, including trace link retrieval, performance enhancement, and the role of the human in the process. Our main objective is to achieve performance levels, in terms of accuracy, efficiency, and usability, that are adequate for practical applications, and ultimately to accomplish a successful technology transfer from research to industry
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