article

Micro patterns in Java code

Authors:

Joseph (Yossi) Gil,

Itay MamanAuthors Info & Claims

ACM SIGPLAN Notices, Volume 40, Issue 10

Pages 97 - 116

https://doi.org/10.1145/1103845.1094819

Published: 12 October 2005 Publication History

Abstract

Micro patterns are similar to design patterns, except that micro patterns are stand at a lower, closer to the implementation, level of abstraction. Micro patterns are also unique in that they are mechanically recognizable, since each such pattern can be expressed as a formal condition on the structure of a class.This paper presents a catalog of 27 micro-patterns defined on Java classes and interfaces. The catalog captures a wide spectrum of common programming practices, including a particular and (intentionally restricted) use of inheritance, immutability, data management and wrapping, restricted creation, and emulation of procedural-, modular-, and even functional- programming paradigms with object oriented constructs. Together, the patterns present a set of prototypes after which a large portion of all Java classes and interfaces are modeled. We provide empirical indication that this portion is as high as 75%.A statistical analysis of occurrences of micro patterns in a large software corpus, spanning some 70,000 Java classes drawn from a rich set of application domains, shows, with high confidence level that the use of these patterns is not random. These results indicate consciousness and discernible design decisions, which are sustained in the software evolution. With high confidence level, we can also show that the use of these patterns is tied to the specification, or the purpose, that the software realizes.The traceability, abundance and the statistical significance of micro pattern occurrence raise the hope of using the classification of software into these patterns for a more founded appreciation of its design and code quality.

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Sultana KAnu VChong T(2020)Using software metrics for predicting vulnerable classes and methods in Java projects: A machine learning approachJournal of Software: Evolution and Process10.1002/smr.2303(e2303)Online publication date: 7-Aug-2020
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Index Terms

Micro patterns in Java code
1. Software and its engineering
  1. Software notations and tools
    1. General programming languages

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Published In

cover image ACM SIGPLAN Notices

ACM SIGPLAN Notices Volume 40, Issue 10

Proceedings of the 20th annual ACM SIGPLAN conference on Object oriented programming systems languages and applications

October 2005

531 pages

ISSN:0362-1340

EISSN:1558-1160

DOI:10.1145/1103845

Issue’s Table of Contents

OOPSLA '05: Proceedings of the 20th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
October 2005
562 pages
ISBN:1595930310
DOI:10.1145/1094811
Conference Chairs:
Ralph Johnson
University of Illinois, Urbana-Champaign, Urbana, IL
,
Elisa Baniassad
Chinese University of Hong Kong
,
Program Chairs:
Richard P. Gabriel
Sun Microsystems Laboratories
,
James Noble
Victoria University of Wellington
,
Brian Marick
Exampler Consulting

Copyright © 2005 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 12 October 2005

Published in SIGPLAN Volume 40, Issue 10

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https://doi.org/10.1007/s11219-022-09606-0
Barbudo RRamírez AServant FRomero J(2021)GEML: A grammar-based evolutionary machine learning approach for design-pattern detectionJournal of Systems and Software10.1016/j.jss.2021.110919175(110919)Online publication date: May-2021
https://doi.org/10.1016/j.jss.2021.110919
Sultana KAnu VChong T(2020)Using software metrics for predicting vulnerable classes and methods in Java projects: A machine learning approachJournal of Software: Evolution and Process10.1002/smr.2303(e2303)Online publication date: 7-Aug-2020
https://doi.org/10.1002/smr.2303
Xiong RLi B(2019)Accurate Design Pattern Detection Based on Idiomatic Implementation Matching in Java Language Context2019 IEEE 26th International Conference on Software Analysis, Evolution and Reengineering (SANER)10.1109/SANER.2019.8668031(163-174)Online publication date: Feb-2019
https://doi.org/10.1109/SANER.2019.8668031
Zhang TYang DLopes CKim MAtlee JBultan TWhittle J(2019)Analyzing and supporting adaptation of online code examplesProceedings of the 41st International Conference on Software Engineering10.1109/ICSE.2019.00046(316-327)Online publication date: 25-May-2019
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Destefanis GQaderi SBowes DPetrić JOrtu MTurhan BTosun AMcIntosh S(2018)A Longitudinal Study of Anti Micro Patterns in 113 versions of TomcatProceedings of the 14th International Conference on Predictive Models and Data Analytics in Software Engineering10.1145/3273934.3273945(90-93)Online publication date: 10-Oct-2018
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Mignon Ade Azevedo da Rocha RMezhuyev VBenedicenti L(2017)An application of composite nano-patterns to compiler selected profiling techniquesProceedings of the 6th International Conference on Software and Computer Applications10.1145/3056662.3056679(186-190)Online publication date: 26-Feb-2017
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Mansoor UKessentini MMaxim BDeb K(2017)Multi-objective code-smells detection using good and bad design examplesSoftware Quality Journal10.1007/s11219-016-9309-725:2(529-552)Online publication date: 1-Jun-2017
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Aktas MKapdan M(2016)Structural Code Clone Detection Methodology Using Software MetricsInternational Journal of Software Engineering and Knowledge Engineering10.1142/S021819401650013326:02(307-332)Online publication date: Mar-2016
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