CODEMINE: Building a Software Development Data Analytics Platform at Microsoft

Czerwonka, Jacek; Nagappan, Nachiappan; Schulte, Wolfram; Murphy, Brendan

doi:10.1109/ms.2013.68

Cited by 52 publications

(37 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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

View full text Add to dashboard Cite

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;

show abstract

Section: Discussionmentioning

confidence: 99%

Restmule

Pina

Barmpis

Neubauer

et al. 2018

Proceedings of the 15th International Conference on Mining Software Repositories

View full text Add to dashboard Cite

show abstract

“…The speed of BUMPER allows developers to use it as a way to leverage decades of history scattered over hundreds of software projects in order to find existing solutions to their problems. There exist tools such as Codemine [5] and Boa [6] that enable the mining and reporting of code repositories. These tools, however, will require the download of all the data and process the mining for each installation.…”

Section: Related Work and Conclusionmentioning

confidence: 99%

BUMPER: A Tool for Coping with Natural Language Searches of Millions of Bugs and Fixes

Nayrolles

Hamou-Lhadj

2016

2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering (SANER)

View full text Add to dashboard Cite

In recent years, mining bug report (BR) repositories has perhaps been one of the most active software engineering research fields. There exist many open source bug tracking and version control systems that developers and researchers can use to examine bug reports so as to reason about software quality. The issue is that these repositories use different interfaces and ways to access and represent data, which hinders productivity and reuse. To address this, we introduce BUMPER (BUg Metarepository for dEvelopers and Researchers), a common infrastructure for developers and researchers interested in mining data from many (heterogeneous) repositories. BUMPER is an open source webbased environment that extracts information from a variety of BR repositories and version control systems. It is equipped with a powerful search engine to help users rapidly query the repositories using a single point of access. To demonstrate the effectiveness of BUMPER, we use it to build a large dataset from a variety of repositories. The dataset contains more than one million bug reports and fixes. Both BUMPER and the dataset are publicly available at https://bumper-app.com.

show abstract

“…We gathered source code repository data from CODEMINE [36] our development analytics database and code review data from CodeFlow Analytics [24], an internal data collection system for code reviews across Microsoft. It is common for automated systems to make source code changes (e.g., updating copyright dates in headers) in MS Office.…”

Section: Closed Source: Ms Officementioning

confidence: 99%

Effective assignment and assistance to software developers and reviewers

Zanjani

2016

Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering

View full text Add to dashboard Cite

DEDICATIONTo my parents and my sister. In this dissertation, we first present the automated solutions for Software Change Impact Analysis based on interaction and code review activities of developers. Then we provide explanation for two separate developer expertise models which use the micro-levels of human-to-code and human-to-human interactions from the previous code review and interaction activities of developers. Next, we present a reviewer expertise model based on code review activities of developers and show how this expertise model can be used for Code Reviewer Recommendation. At the end we examine the influential features that characterize the acceptance probability of a submitted patch (implemented code change) by developers. We present a predictive model that classifies whether a patch will be accepted or not as soon as it is submitted for code review in order to assist developers and reviewers in prioritizing and focusing their efforts.A rigorous empirical validation on large open source and commercial systems shows that the solutions based on the presented methodology outperform several existing solutions. The quantitative gains of our solutions across a spectrum of evaluation metrics along with their statistical significance are reported.vi

show abstract

CODEMINE: Building a Software Development Data Analytics Platform at Microsoft

Cited by 52 publications

References 8 publications

Restmule

Restmule

BUMPER: A Tool for Coping with Natural Language Searches of Millions of Bugs and Fixes

Effective assignment and assistance to software developers and reviewers

Contact Info

Product

Resources

About