46,090 research outputs found

    Systematic reviews in requirements engineering: A tertiary study

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    © 2014 IEEE. There has been an increasing interest in conducting Systematic Literature Reviews (SLR) among Requirements Engineering (RE) researchers in recent years. However, so far there have been no tertiary studies conducted to provide a comprehensive overview of these published SLR in RE. In this paper we present a tertiary study of SLR that focus solely on RE related topics by following the guidelines of Evidence Based Software Engineering. We have conducted both automated search of major online sources and manual search of the RE and SLR related conferences and journals. Our tertiary study has identified 53 distinct systematic reviews published from 2006 to 2014 and reported in 64 publications. We have assessed the resulting SLR for their quality, and coverage of specific RE related topics thus identifying some gaps. We have observed that the quality of SLR in RE has been decreasing over the recent years. There is a strong need to replicate some of these SLR to increase the reliability of their results for future RE research

    Establishing a Search String to Detect Secondary Studies in Software Engineering

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    Search for secondary studies is essential to establish whether the review on the intended topic has already been done, avoiding waste time. In addition, secondary studies are the inputs of a tertiary study. However, one critical step in searching for secondary studies is to elaborate a search string. The main goal of this work is to analyze search strings to establish directions to better detect secondary studies in Software Engineering (SE). We analyzed seven tertiary studies under two perspectives: (1) structure - strings' terms to detect secondary studies; and (2) field: where searching - titles alone or abstracts alone or titles and abstracts together, among others. We also performed a validation of the results found. The suitable search string for finding secondary studies in SE contain the terms "systematic review", "literature review", "systematic mapping", "mapping study", "systematic map", "meta-analysis", "survey" and "literature analysis". Furthermore, we recommend (1) researchers use the title, abstract and keywords search fields in their searches to increase studies recall; (2) researchers choose carefully their paper title, abstract and keyword terms to increase the chance of having such studies found on digital libraries

    Advances and Challenges in Software Refactoring: A Tertiary Systematic Literature Review

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    Software refactoring is one of the most critical aspects of software maintenance. It improves the quality of the software, reduces potential occurrence of bugs and keeps the code easier to maintain, extend and read. The process of refactoring supports and enables the developers to improve the design of software without changing the behavior. However, the automation of this process is complex for developers and software engineers since it is subjective, time and resource consuming. In this context, many literature reviews have analyzed the existing effort made by researchers to facilitate refactoring, as a core software engineering practice. This paper, aims in integrating all the existing research outcomes by performing a tertiary study on all the secondary studies, done in the area of refactoring. Based on our analysis we notice that there are many area of software refactoring that are under studied. As an outcome of this review, several classifications of existing studies were provided to showcase all the studies targeting the automation of refactoring along with explaining what metrics and objectives were used as means to drive refactoring and how it was assessed. This thesis also aims in unveiling areas of future directions for the research community in order to consolidate their efforts in improving the refactoring as a practice

    The contribution that empirical studies performed in industry make to the findings of systematic reviews: A tertiary study

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    Context: Systematic reviews can provide useful knowledge for software engineering practice, by aggregating and synthesising empirical studies related to a specific topic. Objective: We sought to assess how far the findings of systematic reviews addressing practice-oriented topics have been derived from empirical studies that were performed in industry or that used industry data. Method: We drew upon and augmented the data obtained from a tertiary study that performed a systematic review of systematic reviews published in the period up to the end of 2015, seeking to identify those with findings that are relevant for teaching and practice. For the supplementary analysis reported here, we then examined the profiles of the primary studies as reported in each systematic review. Results: We identified 48 systematic reviews as candidates for further analysis. The many differences that arise between systematic reviews, together with the incompleteness of reporting for these, mean that our counts should be treated as indicative rather than definitive. However, even when allowing for problems of classification, the findings from the majority of these systematic reviews were predominantly derived from using primary studies conducted in industry. There was also an emphasis upon the use of case studies, and a number of the systematic reviews also made some use of weaker ‘experience’ or even ‘opinion’ papers. Conclusions: Primary studies from industry play an important role as inputs to systematic reviews. Using more rigorous industry-based primary studies can give greater authority to the findings of the systematic reviews, and should help with the creation of a corpus of sound empirical data to support evidence-informed decisions

    Technical Debt Prioritization: State of the Art. A Systematic Literature Review

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    Background. Software companies need to manage and refactor Technical Debt issues. Therefore, it is necessary to understand if and when refactoring Technical Debt should be prioritized with respect to developing features or fixing bugs. Objective. The goal of this study is to investigate the existing body of knowledge in software engineering to understand what Technical Debt prioritization approaches have been proposed in research and industry. Method. We conducted a Systematic Literature Review among 384 unique papers published until 2018, following a consolidated methodology applied in Software Engineering. We included 38 primary studies. Results. Different approaches have been proposed for Technical Debt prioritization, all having different goals and optimizing on different criteria. The proposed measures capture only a small part of the plethora of factors used to prioritize Technical Debt qualitatively in practice. We report an impact map of such factors. However, there is a lack of empirical and validated set of tools. Conclusion. We observed that technical Debt prioritization research is preliminary and there is no consensus on what are the important factors and how to measure them. Consequently, we cannot consider current research conclusive and in this paper, we outline different directions for necessary future investigations
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