A Survey of Source Code Search: A 3-Dimensional Perspective

(Source) code search is widely concerned by software engineering researchers because it can improve the productivity and quality of software development. Given a functionality requirement usually described in a natural language sentence, a code search system can retrieve code snippets that satisfy the requirement from a large-scale code corpus, e.g., GitHub. To realize effective and efficient code search, many techniques have been proposed successively. These techniques improve code search performance mainly by optimizing three core components, including query understanding component, code understanding component, and query-code matching component. In this paper, we provide a 3-dimensional perspective survey for code search. Specifically, we categorize existing code search studies into query-end optimization techniques, code-end optimization techniques, and match-end optimization techniques according to the specific components they optimize. Considering that each end can be optimized independently and contributes to the code search performance, we treat each end as a dimension. Therefore, this survey is 3-dimensional in nature, and it provides a comprehensive summary of each dimension in detail. To understand the research trends of the three dimensions in existing code search studies, we systematically review 68 relevant literatures. Different from existing code search surveys that only focus on the query end or code end or introduce various aspects shallowly (including codebase, evaluation metrics, modeling technique, etc.), our survey provides a more nuanced analysis and review of the evolution and development of the underlying techniques used in the three ends. Based on a systematic review and summary of existing work, we outline several open challenges and opportunities at the three ends that remain to be addressed in future work.Comment: submitted to ACM Transactions on Software Engineering and Methodolog

Data Management in Microservices: State of the Practice, Challenges, and Research Directions

We are recently witnessing an increased adoption of microservice architectures by the industry for achieving scalability by functional decomposition, fault-tolerance by deployment of small and independent services, and polyglot persistence by the adoption of different database technologies specific to the needs of each service. Despite the accelerating industrial adoption and the extensive research on microservices, there is a lack of thorough investigation on the state of the practice and the major challenges faced by practitioners with regard to data management. To bridge this gap, this paper presents a detailed investigation of data management in microservices. Our exploratory study is based on the following methodology: we conducted a systematic literature review of articles reporting the adoption of microservices in industry, where more than 300 articles were filtered down to 11 representative studies; we analyzed a set of 9 popular open-source microservice-based applications, selected out of more than 20 open-source projects; furthermore, to strengthen our evidence, we conducted an online survey that we then used to cross-validate the findings of the previous steps with the perceptions and experiences of over 120 practitioners and researchers. Through this process, we were able to categorize the state of practice and reveal several principled challenges that cannot be solved by software engineering practices, but rather need system-level support to alleviate the burden of practitioners. Based on the observations we also identified a series of research directions to achieve this goal. Fundamentally, novel database systems and data management tools that support isolation for microservices, which include fault isolation, performance isolation, data ownership, and independent schema evolution across microservices must be built to address the needs of this growing architectural style

Structured Review of the Evidence for Effects of Code Duplication on Software Quality

This report presents the detailed steps and results of a structured review of code clone literature. The aim of the review is to investigate the evidence for the claim that code duplication has a negative effect on code changeability. This report contains only the details of the review for which there is not enough place to include them in the companion paper published at a conference (Hordijk, Ponisio et al. 2009 - Harmfulness of Code Duplication - A Structured Review of the Evidence)

Structured Review of Code Clone Literature

This report presents the results of a structured review of code clone literature. The aim of the review is to assemble a conceptual model of clone-related concepts which helps us to reason about clones. This conceptual model unifies clone concepts from a wide range of literature, so that findings about clones can be compared with each other

A Systematic Review of Tracing Solutions in Software Product Lines

Software Product Lines are large-scale, multi-unit systems that enable massive, customized production. They consist of a base of reusable artifacts and points of variation that provide the system with flexibility, allowing generating customized products. However, maintaining a system with such complexity and flexibility could be error prone and time consuming. Indeed, any modification (addition, deletion or update) at the level of a product or an artifact would impact other elements. It would therefore be interesting to adopt an efficient and organized traceability solution to maintain the Software Product Line. Still, traceability is not systematically implemented. It is usually set up for specific constraints (e.g. certification requirements), but abandoned in other situations. In order to draw a picture of the actual conditions of traceability solutions in Software Product Lines context, we decided to address a literature review. This review as well as its findings is detailed in the present article.Comment: 22 pages, 9 figures, 7 table

Automated analysis of feature models: Quo vadis?

Feature models have been used since the 90's to describe software product lines as a way of reusing common parts in a family of software systems. In 2010, a systematic literature review was published summarizing the advances and settling the basis of the area of Automated Analysis of Feature Models (AAFM). From then on, different studies have applied the AAFM in different domains. In this paper, we provide an overview of the evolution of this field since 2010 by performing a systematic mapping study considering 423 primary sources. We found six different variability facets where the AAFM is being applied that define the tendencies: product configuration and derivation; testing and evolution; reverse engineering; multi-model variability-analysis; variability modelling and variability-intensive systems. We also confirmed that there is a lack of industrial evidence in most of the cases. Finally, we present where and when the papers have been published and who are the authors and institutions that are contributing to the field. We observed that the maturity is proven by the increment in the number of journals published along the years as well as the diversity of conferences and workshops where papers are published. We also suggest some synergies with other areas such as cloud or mobile computing among others that can motivate further research in the future.Ministerio de Economía y Competitividad TIN2015-70560-RJunta de Andalucía TIC-186