A study of library migrations in Java

Teyton, Cédric; Falleri, Jean‐Rémy; Palyart, Marc; Blanc, Xavier

doi:10.1002/smr.1660

Cited by 54 publications

(38 citation statements)

References 23 publications

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“…Migration patterns between dependencies that provide comparable functionality were also studied, showing how dependencies are swapped within a system when the used dependency is no longer to be found suitable [9].…”

Section: Introductionmentioning

confidence: 99%

Measuring Dependency Freshness in Software Systems

Cox

Bouwers

Eekelen

et al. 2015

2015 IEEE/ACM 37th IEEE International Conference on Software Engineering

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Abstract-Modern software systems often make use of thirdparty components to speed-up development and reduce maintenance costs. In return, developers need to update to new releases of these dependencies to avoid, for example, security and compatibility risks. In practice, prioritizing these updates is difficult because the use of outdated dependencies is often opaque. In this paper we aim to make this concept more transparent by introducing metrics to quantify the use of recent versions of dependencies, i.e. the system's "dependency freshness".We propose and investigate a system-level metric based on an industry benchmark. We validate the usefulness of the metric using interviews, analyze the variance of the metric through time, and investigate the relationship between outdated dependencies and security vulnerabilities. The results show that the measurements are considered useful, and that systems using outdated dependencies four times as likely to have security issues as opposed to systems that are up-to-date.

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Section: Introductionmentioning

confidence: 99%

Measuring Dependency Freshness in Software Systems

Cox

Bouwers

Eekelen

et al. 2015

2015 IEEE/ACM 37th IEEE International Conference on Software Engineering

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show abstract

“…OUTPUT: newFragment -Fragment has one added, and one removed method that have highest similarity score between method's description. 22: procedure LD( f ragments) to reduce the cardinality of many-to-many fragments, by splitting based on any common one-to-one or one-tomany mappings. Sorting the fragments prior to applying the intersection gives the opportunity to split larger fragments using smaller, yet relevant, fragments instead of performing random intersections between fragments.…”

Section: Algorithm 1 Substitution Algorithm (Sa)mentioning

confidence: 99%

On the Use of Information Retrieval to Automate the Detection of Third-Party Java Library Migration at the Method Level

Alrubaye

Mkaouer

Ouni

2019

2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)

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The migration process between different thirdparty libraries is hard, complex and error-prone. Typically, during a library migration, developers need to find methods in the new library that are most adequate in replacing the old methods of the retired library. This process is subjective and time-consuming as developers need to fully understand the documentation of both libraries' Application Programming Interfaces, and find the right matching between their methods, if it exists. In this context, several studies rely on mining existing library migrations to provide developers with by-example approaches for similar scenarios. In this paper, we introduce a novel mining approach that extracts existing instances of library method replacements that are manually performed by developers for a given library migration to automatically generate migration patterns in the method level. Thereafter, our approach combines the mined method-change patterns with method-related lexical similarity to accurately detect mappings between replacing/replaced methods. We conduct a large scale empirical study to evaluate our approach on a benchmark of 57,447 open-source Java projects leading to 9 popular library migrations. Our qualitative results indicate that our approach significantly increases the accuracy of mining method-level mappings by an average accuracy of 12%, as well as increasing the number of discovered method mappings, in comparison with existing state-of-the-art studies. Finally, we provide the community with an open source mining tool along with a dataset of all mined migrations at the method level.

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“…API evolution and deprecation, which often leads to important collateral evolutions can be influential in project development. Several studies in the literature have investigated such evolution. For example, Dagenais and Robillard have proposed SemDiff, a framework for recommending replacements of non‐trivial changes.…”

Section: Related Workmentioning

confidence: 99%

“…Robbes et al have studied the importance in practice of API deprecation for developers. Teyton et al have built a framework for analyzing software library dependencies to support developers in library migrations based on evolution trends.…”

Section: Related Workmentioning

confidence: 99%

Watch out for this commit! A study of influential software changes

Kim

et al. 2019

J Software Evolu Process

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One single code change can significantly influence a wide range of software systems and their users. For example, (a) adding a new feature can spread defects in several modules, while (b) changing an API method can improve the performance of all client programs. Unfortunately, developers often may not clearly know whether code changes are influential at commit time. This paper investigates influential software changes and proposes an approach to identify them immediately when they are applied. Our goals are to (a) identify existing influential changes (ICs) in software projects, (b) understand their characteristics, and (c) build a classification model of ICs to help developers find and address them early. We first conduct a post‐mortem analysis to discover existing influential changes by using intuitions (eg, changes referred by other changes). Then, we re‐categorize all identified changes through an open‐card sorting process. Subsequently, we conduct a survey with about 100 developers to finalize a taxonomy. Finally, from our ground truth, we extract features, including metrics such as the complexity of changes and file centrality in co‐change graphs to build machine learning classifiers. The experiment results show that our classification model with random samples achieves 86.8% precision, 74% recall, and 80.4% F‐measure, respectively.

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A study of library migrations in Java

Cited by 54 publications

References 23 publications

Measuring Dependency Freshness in Software Systems

Measuring Dependency Freshness in Software Systems

On the Use of Information Retrieval to Automate the Detection of Third-Party Java Library Migration at the Method Level

Watch out for this commit! A study of influential software changes

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