NDLI: Improving change recommendation using aggregated association rules

Please wait, while we are loading the content...

Studying the effectiveness of application performance management (APM) tools for detecting performance regressions for web applications: an experience report

Automatic clustering of code changes

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

Raising MSR researchers: an experience report on teaching a graduate seminar course in mining software repositories (MSR)

An empirical study on the practice of maintaining object-relational mapping code in Java systems

Externalization of software behavior by the mining of norms

How software developers use work breakdown relationships in issue repositories

Software ingredients: detection of third-party component reuse in Java software release

The impact of switching to a rapid release cycle on the integration delay of addressed issues: an empirical study of the mozilla firefox project

From query to usable code: an analysis of stack overflow code snippets

Data sets: the circle of life in ruby hosting, 2003-2015

Examining programmer practices for locally handling exceptions

Mining test repositories for automatic detection of UI performance regressions in Android apps

Improving change recommendation using aggregated association rules

Comparing repositories visually with repograms

Interactive exploration of developer interaction traces using a hidden markov model

Inter-app communication in Android: developer challenges

Sentiment analysis in tickets for IT support

Locating bugs without looking back

A look at the dynamics of the JavaScript package ecosystem

Characterization of the Xen project code review process: an experience report

Mining duplicate questions in stack overflow

Mining the modern code review repositories: a dataset of people, process and product

QualBoa: reusability-aware recommendations of source code components

Mining performance regression inducing code changes in evolving software

FEVER: extracting feature-oriented changes from commits

Findings from GitHub: methods, datasets and limitations

Does your configuration code smell?

Mining valence, arousal, and dominance: possibilities for detecting burnout and productivity?

Using dynamic and contextual features to predict issue lifetime in GitHub projects

A large-scale study on repetitiveness, containment, and composability of routines in open-source projects

Domain-specific cross-language relevant question retrieval

MUBench: a benchmark for API-misuse detectors

The dispersion of build maintenance activity across maven lifecycle phases

How android app developers manage power consumption?: an empirical study by mining power management commits

Cold-start software analytics

Feature toggles: practitioner practices and a case study

On mining crowd-based speech documentation

Topic modeling of NASA space system problem reports: research in practice

Recognizing gender of stack overflow users

AndroZoo: collecting millions of Android apps for the research community

The relationship between commit message detail and defect proneness in Java projects on GitHub

GreenOracle: estimating software energy consumption with energy measurement corpora

Logging library migrations: a case study for the apache software foundation projects

Understanding the exception handling strategies of Java libraries: an empirical study

The unreasonable effectiveness of traditional information retrieval in crash report deduplication

A large-scale empirical study on self-admitted technical debt

Grouping android tag synonyms on stack overflow

Multi-extract and multi-level dataset of mozilla issue tracking history

Analysis of exception handling patterns in Java projects: an empirical study

Got technical debt?: surfacing elusive technical debt in issue trackers

How the R community creates and curates knowledge: a comparative study of stack overflow and mailing lists

A dataset of simplified syntax trees for C#

Judging a commit by its cover: correlating commit message entropy with build status on travis-CI

The emotional side of software developers in JIRA

Characterizing energy-aware software projects: are they different?

A deeper look into bug fixes: patterns, replacements, deletions, and additions

How developers use exception handling in Java?

Analyzing developer sentiment in commit logs

Improving change recommendation using aggregated association rules

Content Provider	ACM Digital Library
Author	Binkley, Dave Rolfsnes, Thomas Behjati, Razieh Di Alesio, Stefano Moonen, Leon
Abstract	Past research has proposed association rule mining as a means to uncover the evolutionary coupling from a system's change history. These couplings have various applications, such as improving system decomposition and recommending related changes during development. The strength of the coupling can be characterized using a variety of interestingness measures. Existing recommendation engines typically use only the rule with the highest interestingness value in situations where more than one rule applies. In contrast, we argue that multiple applicable rules indicate increased evidence, and hypothesize that the aggregation of such rules can be exploited to provide more accurate recommendations. To investigate this hypothesis we conduct an empirical study on the change histories of two large industrial systems and four large open source systems. As aggregators we adopt three cumulative gain functions from information retrieval. The experiments evaluate the three using 39 different rule interestingness measures. The results show that aggregation provides a significant impact on most measure's value and, furthermore, leads to a significant improvement in the resulting recommendation.
Starting Page	73
Ending Page	84
Page Count	12
File Format	PDF
ISBN	9781450341868
DOI	10.1145/2901739.2901756
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-05-14
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

Central Library (ISO-9001:2015 Certified)
Indian Institute of Technology Kharagpur
Kharagpur, West Bengal, India | PIN - 721302

See location in the Map
03222 282435
Mail: support@ndl.gov.in

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in