Characterizing the Usage, Evolution and Impact of Java Annotations in Practice

Yu, Zhongxing; Bai, Chenggang; Seinturier, Lionel; Monperrus, Martin

doi:10.1109/tse.2019.2910516

Cited by 25 publications

(25 citation statements)

References 44 publications

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“…Our corpus contains 18,122 large and popular Python projects hosted on GitHub. Our project selection process is inspired from Yu et al [142], who studied the usage of Java annotations in practice. We retrieve all non-forked and non-archived Python repositories whose stargazers counts (that indicate popularity of projects [18,19]) are larger than 50 as of December 31, 2018.…”

Section: Top Rated Python Projectsmentioning

confidence: 99%

Understanding Software-2.0

Dilhara

Ketkar

Dig

2021

ACM Trans. Softw. Eng. Methodol.

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Enabled by a rich ecosystem of Machine Learning (ML) libraries, programming using learned models , i.e., Software-2.0 , has gained substantial adoption. However, we do not know what challenges developers encounter when they use ML libraries. With this knowledge gap, researchers miss opportunities to contribute to new research directions, tool builders do not invest resources where automation is most needed, library designers cannot make informed decisions when releasing ML library versions, and developers fail to use common practices when using ML libraries. We present the first large-scale quantitative and qualitative empirical study to shed light on how developers in Software-2.0 use ML libraries, and how this evolution affects their code. Particularly, using static analysis we perform a longitudinal study of 3,340 top-rated open-source projects with 46,110 contributors. To further understand the challenges of ML library evolution, we survey 109 developers who introduce and evolve ML libraries. Using this rich dataset we reveal several novel findings. Among others, we found an increasing trend of using ML libraries: The ratio of new Python projects that use ML libraries increased from 2% in 2013 to 50% in 2018. We identify several usage patterns including the following: (i) 36% of the projects use multiple ML libraries to implement various stages of the ML workflows, (ii) developers update ML libraries more often than the traditional libraries , (iii) strict upgrades are the most popular for ML libraries among other update kinds, (iv) ML library updates often result in cascading library updates, and (v) ML libraries are often downgraded (22.04% of cases). We also observed unique challenges when evolving and maintaining Software-2.0 such as (i) binary incompatibility of trained ML models and (ii) benchmarking ML models. Finally, we present actionable implications of our findings for researchers, tool builders, developers, educators, library vendors, and hardware vendors.

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Section: Top Rated Python Projectsmentioning

confidence: 99%

Understanding Software-2.0

Dilhara

Ketkar

Dig

2021

ACM Trans. Softw. Eng. Methodol.

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“…Several other frameworks for testing and mobile development also adopted the metadatabased approach. The wide adoption of code annotations can be confirmed with recent studies investigating the code of several open-source projects [35]- [37].…”

Section: Reflective and Metadata-based Frameworkmentioning

confidence: 71%

A Model to Enable the Reuse of Metadata-Based Frameworks in Adaptive Object Model Architectures

et al. 2021

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The Adaptive Object Model (AOM) is an architectural style in which domain entity types are represented as instances that can be changed at runtime. It can be used to achieve higher flexibility in domain classes. Due to AOM entities having a distinct structure, they are not compatible with most popular frameworks, especially those that use reflection and code annotations. Objective: To solve such limitations, this work aims to propose a model that enables the reuse of frameworks designed for classic object-oriented domain models in an AOM application. Methods: The proposed model uses dynamically-generated adapters for AOM entities that encapsulate them in a class with the format expected by the frameworks. A reference implementation was developed in the Esfinge AOM RoleMapper framework to evaluate the viability of the proposed model. Initially, to evaluate the solution feasibility, a case study was carried out using the Hibernate framework. Further, an experiment was conducted to assess how the participants perceived the framework functionality reuse through the proposed model. Results: The feasibility study revealed that the solution could be applied in a complex setting for the chosen object-relational mapping frame. It raised some difficulties that can be addressed in future studies. In the experiment, the development time did not present a significant difference compared to the competing approach. Despite the considerable learning curve, most participants considered that the proposed approach has more advantages than the alternative. Conclusion: Based on the evaluations, we can conclude that the proposed model can be successfully employed to use AOM entities with frameworks that were not designed for AOM applications. The possibility of reusing existing frameworks can reduce the effort required to adopt an AOM architecture and, consequently, be a facilitator in implementing more flexible and adaptive approaches.

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“…A recent study performed in Java open source projects [1] identified at least one code annotation in 78% of the classes. Another study demonstrated that code annotations are actively maintained, and most code annotations changes are consistent with other code changes [2]. This evidence suggests that code annotations are a feature that has a non-neglectable impact on software maintenance.…”

Section: Introductionmentioning

confidence: 78%

“…The findings revealed that some annotations were repeated around 100 times in code elements with shared characteristics in the target system. The repetition of annotations is also mentioned in Yu et al [2], but no quantitative evidence was presented.…”

Section: Annotation Assessmentmentioning

confidence: 91%

Towards Visualizing Code Annotations Distribution

Lima¹,

Guerra²,

Meirelles³

2020

Anais Do XI Computer on the Beach - COTB '20

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Java developers make extensive use of code annotations sincetheir introduction in version 5 of the language. They areinserted directly on the source code for custom metadata configuration,similar to C# attributes. The software engineeringcommunity has few works investigating their usage and impacton source code. Being able to visualize characteristics ofcode annotations might aid developers in detecting potentialmisuse, outliers as well as increase the comprehensibility andreadability of the source code. In this paper, we present anapproach to use software metrics to generate a 2D polymetricview targeting the visualization of code annotations in Javaclasses. We developed a prototype tool using the Unity GameEngine. It displays classes and packages as rectangles andannotations as circles. We demonstrated the tool with a smallsample Java program.

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Characterizing the Usage, Evolution and Impact of Java Annotations in Practice

Cited by 25 publications

References 44 publications

Understanding Software-2.0

Understanding Software-2.0

A Model to Enable the Reuse of Metadata-Based Frameworks in Adaptive Object Model Architectures

Towards Visualizing Code Annotations Distribution

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