Adressing problems with external validity of repository mining studies through a smart data platform

Trautsch, Fabian; Herbold, Steffen; Makedonski, Philip; Grabowski, Jens

doi:10.1145/2901739.2901753

Cited by 15 publications

(5 citation statements)

References 33 publications

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“…Metricoriented frameworks, such as OSSMETER [1] and RepoGrams [13], focus on collecting data for producing metrics, such as software quality, static source code, and changes. Worklow-oriented frameworks like SmartSHARK [14], CODEMINE [3], and BOA [4], aim to provide a shared environment for data analysis purposes. RestMule can act as a complementary component, which can help with the activity of data collection from remote APIs in such systems.…”

Section: Discussionmentioning

confidence: 99%

Restmule

Pina

Barmpis

Neubauer

et al. 2018

Proceedings of the 15th International Conference on Mining Software Repositories

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Mining data from remote repositories, such as GitHub and StackExchange, involves the execution of requests that can easily reach the limitations imposed by the respective APIs to shield their services from overload and abuse. Therefore, data mining clients are left alone to deal with such protective service policies which usually involves an extensive amount of manual implementation efort. In this work we present RestMule, a framework for handling various service policies, such as limited number of requests within a period of time and multi-page responses, by generating resilient clients that are able to handle request rate limits, network failures, response caching, and paging in a graceful and transparent manner. As a result, RestMule clients generated from OpenAPI speciications (i.e. standardized REST API descriptors), are suitable for intensive data-fetching scenarios. We evaluate our framework by reproducing an existing repository mining use case and comparing the results produced by employing a popular hand-written client and a RestMule client. CCS CONCEPTS• Information systems → RESTful web services; • Software and its engineering → Reusability; Error handling and recovery;

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Section: Discussionmentioning

confidence: 99%

Restmule

Pina

Barmpis

Neubauer

et al. 2018

Proceedings of the 15th International Conference on Mining Software Repositories

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“…The subjects of study are represented by a set of 21 publicly available open source software projects (i.e. the set employed by Trautsch et al [14]).…”

Section: Methodsmentioning

confidence: 99%

Polyglot and Distributed Software Repository Mining with Crossflow

Barmpis

Neubauer

et al. 2020

Proceedings of the 17th International Conference on Mining Software Repositories

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Mining software repositories at a large scale typically requires substantial computational and storage resources. This creates an increasing need for repository mining programs to be executed in a distributed manner, such that remote collaborators can contribute local computational and storage resources. In this paper we present Crossflow, a novel framework for building polyglot distributed repository mining programs. We demonstrate how Crossflow offers delegation of mining jobs to remote workers and can cache their results, how such workers are able to implement advanced behavior like load balancing and rejecting jobs they either cannot perform or would execute sub-optimally, and how workers of the same analysis program can be written in different programing languages like Java and Python, executing only relevant parts of the program described in that language. CCS CONCEPTS• Information systems → Data mining; • Software and its engineering → Concurrent programming structures.

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“…We focus the related work discussion in two areas: compilability [9,10,13,15,16,20] and software quality evolution [1,7,[17][18][19]22] by commit-level.…”

Section: Related Workmentioning

confidence: 99%

“…It mines every commit in the history of software and applies a lightweight static analysis technique on files affected by the commit to check if a code smell is introduced. SmartShark [18,19] is a distributed framework designed to address the problems with external validity of mining software repository studies. It runs static analysis on affected files by every commit.…”

Section: Related Workmentioning

confidence: 99%

A scalable and efficient approach for compiling and analyzing commit history

Behnamghader¹,

Meemeng²,

Fostiropoulos³

et al. 2018

Proceedings of the 12th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement

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Background: Researchers oftentimes measure quality metrics only in the changed files when analyzing software evolution over commithistory. This approach is not suitable for compilation and using program analysis techniques that require byte-code. At the same time, compiling the whole software not only is costly but may also leave us with many uncompilable and unanalyzed revisions. Aims: We intend to demonstrate if analyzing changes in a module results in achieving a high compilation ratio and a better understanding of software quality evolution. Method: We conduct a large-scale multiperspective empirical study on 37838 distinct revisions of the core module of 68 systems across Apache, Google, and Netflix to assess their compilability and identify when the software is uncompilable as a result of a developer's fault. We study the characteristics of uncompilable revisions and analyze compilable ones to understand the impact of developers on software quality. Results: We achieve high compilation ratios: 98.4% for Apache, 99.0% for Google, and 94.3% for Netflix. We identify 303 sequences of uncompile commits and create a model to predict uncompilability based on commit metadata with an F1-score of 0.89 and an AUC of 0.96. We identify statistical differences between the impact of affiliated and external developers of organizations. Conclusions: Focusing on a module results in a more complete and accurate software evolution analysis, reduces the cost and complexity, and facilitates manual inspection. CCS CONCEPTS• Software and its engineering → Software configuration management and version control systems; Maintaining software;

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Adressing problems with external validity of repository mining studies through a smart data platform

Cited by 15 publications

References 33 publications

Restmule

Restmule

Polyglot and Distributed Software Repository Mining with Crossflow

A scalable and efficient approach for compiling and analyzing commit history

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