evolution of database access technologies in java-based software projects

Evolu&onofdatabaseaccesstechnologiesinJava-basedso6wareprojectsLoupMeuriceAnthonyCleveCsabaNagy

UniversityofNamur,Belgium

h?p://informa&que.umons.ac.be/genlog/projects/disse

EOSESE2015—Lille,France,3December2015

TomMensMathieuGoeminneAlexandreDecan

UniversityofMons,Belgium

EOSESE–Lille,France,3December2015

• Context:InteruniversityFNRS-fundedresearchprojectbetweenUniversitédeMonsandUniversitédeNamur

• Focus:Empiricalanalysisofco-evolu&onbetweenprogramcodeanddatabase(schema)indata-intensiveso6waresystems

• Goal:Providebe?ersupportforsuchco-evolu&ontoso6waredevelopersandprojectmanagers

• Thispresenta&on:Studyusageandevolu&onofrela&onaldatabaseaccess(RDBA)technologiesforopensourceJavasystems

Data-IntensiveSo6wareSystemEvolu&on

Focus

3

•  JavaRDBAtechnologies

4

Focus


EOSESE–Lille,France,3December2015 5

The mapping can take many different forms, as illustrated in Figure 2. The first example showsthe use of Hibernate configuration files (i.e., .hbm.xml). The second example illustrates theuse of Java annotations based on JPA, the standard API in Java for ORM and data persistencemanagement. Such a mapping may allow direct operations on objects, attributes and relationshipsinstead of tables and columns. This is commonly referred as the active record pattern.

Some ORM libraries also provide SQL-inspired languages that allow to write SQL-like queriesusing the mappings defined before. The third example in Figure 2 illustrates the Hibernate QueryLanguage (HQL), and the fourth example uses the Java Persistence Query Language (JPQL), aplatform-independent object-oriented query language which is defined as part of the JPA specifi-cation.

Example of using Hibernate configuration files:

1 < h i b e r n a t e �mapping>2 < c l a s s name=" Customer " t a b l e =" AppCustomers ">3 < i d name=" i d " t y p e =" i n t " column=" i d " / >4 < p r o p e r t y name=" name " column=" name " t y p e =" S t r i n g " / >5 < / c l a s s >6 < / h i b e r n a t e �mapping>

Example of using JPA annotations:

1 @Enti ty2 @Table ( name=" AppCustomers " )3 p u b l i c c l a s s Customer {4 @Id5 p r i v a t e i n t i d ;6 S t r i n g name ;7 [ . . . ]8 }

Example of using Hibernate Query Language (HQL):

1 p u b l i c L i s t <Customer > f i n d A l l C u s t o m e r s ( ) {2 S t r i n g h q l = " s e l e c t c from Customer c " ;3 re turn e x e c u t e Q u e r y ( h q l ) ;4 }5 p u b l i c L i s t e x e c u t e Q u e r y ( S t r i n g h q l ) {6 re turn s e s s i o n . c r e a t e Q u e r y ( h q l ) . l i s t ( ) ;7 }8 p u b l i c Customer f i n d C u s t o m e r ( I n t e g e r i d ) {9 re turn ( Customer ) s e s s i o n . g e t ( Customer . c l a s s , i d ) ;

10 }

Example of direct object manipulation using ActiveJDBC:

1 L i s t <Customer > c u s t o m e r s = Customer . where ( " name = ’ John Doe ’ " ) ;2 Customer john = c u s t o m e r s . g e t ( 0 ) ;3 j ohn . setName ( " John Smith " ) ;4 j ohn . s a v e I t ( ) ;

Figure 2: Four examples of Java ORM usage.

6

The mapping can take many different forms, as illustrated in Figure 2. The first example showsthe use of Hibernate configuration files (i.e., .hbm.xml). The second example illustrates theuse of Java annotations based on JPA, the standard API in Java for ORM and data persistencemanagement. Such a mapping may allow direct operations on objects, attributes and relationshipsinstead of tables and columns. This is commonly referred as the active record pattern.

Some ORM libraries also provide SQL-inspired languages that allow to write SQL-like queriesusing the mappings defined before. The third example in Figure 2 illustrates the Hibernate QueryLanguage (HQL), and the fourth example uses the Java Persistence Query Language (JPQL), aplatform-independent object-oriented query language which is defined as part of the JPA specifi-cation.

Example of using Hibernate configuration files:

1 < h i b e r n a t e �mapping>2 < c l a s s name=" Customer " t a b l e =" AppCustomers ">3 < i d name=" i d " t y p e =" i n t " column=" i d " / >4 < p r o p e r t y name=" name " column=" name " t y p e =" S t r i n g " / >5 < / c l a s s >6 < / h i b e r n a t e �mapping>

Example of using JPA annotations:

1 @Enti ty2 @Table ( name=" AppCustomers " )3 p u b l i c c l a s s Customer {4 @Id5 p r i v a t e i n t i d ;6 S t r i n g name ;7 [ . . . ]8 }

Example of using Hibernate Query Language (HQL):

1 p u b l i c L i s t <Customer > f i n d A l l C u s t o m e r s ( ) {2 S t r i n g h q l = " s e l e c t c from Customer c " ;3 re turn e x e c u t e Q u e r y ( h q l ) ;4 }5 p u b l i c L i s t e x e c u t e Q u e r y ( S t r i n g h q l ) {6 re turn s e s s i o n . c r e a t e Q u e r y ( h q l ) . l i s t ( ) ;7 }8 p u b l i c Customer f i n d C u s t o m e r ( I n t e g e r i d ) {9 re turn ( Customer ) s e s s i o n . g e t ( Customer . c l a s s , i d ) ;

10 }

Example of direct object manipulation using ActiveJDBC:

1 L i s t <Customer > c u s t o m e r s = Customer . where ( " name = ’ John Doe ’ " ) ;2 Customer john = c u s t o m e r s . g e t ( 0 ) ;3 j ohn . setName ( " John Smith " ) ;4 j ohn . s a v e I t ( ) ;

Figure 2: Four examples of Java ORM usage.

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Focus



Focus

•  ORMspromisetoreducethe“object-rela&onalimpedancemismatch”

•  Butdotheyreally?•  Whataretherisksandadvantagesofusingapar&culartechnology?

•  HowdoprojectsusingORMevolveover&me?•  Howaremul&pleORMtechnologiesusedtogether?Dotheytendtocomplementorsubs&tuteoneanother?

•  HowarethecodeandDBschemakeptsynchronised?


Coarse-grainedanalysis

•  EmpiricalstudyonopensourceJavaprojects–  13,307s&llac&veJavaprojectsextractedfromGitHubJavaCorpus[Allamanis&Su?on—MSR2013]

–  4,503ofthemusedanRDBAtechnology–  2,818projectsusedJDBC,JPA,SpringorHibernate



•  Evolu&onofRDBAtechnologyusage–  Rela&veshareofeachofthe4consideredtechnologies

•  JDBCremainsmostprominent,butdecreasingsharesince2006•  Sinceitsintroduc&on,shareofJPAcon&nuestoincrease



•  Co-occurrenceofRDBAtechnologies– ManyprojectswithJPA,HibernateorSpringalsousedirectJDBCaccess

–  38%ofallprojectsuseatleast2technologies–  Projectsusingmul&pletechnologiestendtousethemsimultaneously(>80%)

JPASpring JDBC

Hibernate284

167 1239

6086

124

133

139

16

76

61

64143

46

180

Hibernateo8enco-occurswithJPA(77%)andJDBC(61%)



•  IntroducingandremovalofRDBAtechnologies–  Technologiesareintroducedearlyinprojectlife&me–  Technologiesdisappearfasterinsmallthaninlargeprojects

Introduc&on&me Removal&me



•  IntroducingandremovalofRDBAtechnologies– Newtechnosareintroducedmoreo6eninlargeprojects–  JDBCisnotfollowedfrequentlybyothertechnos– Hibernateisfrequentlyfollowedbyanothertechno

“Survivalcurve”

Probabilitythatatechnoremainsthelastlyintroducedone

smallprojects

largeprojects


Fine-grainedanalysis

•  Researchques&ons•  HowdodevelopersdecidetointroducenewRDBAtechnologies?

•  Howandwherearepar&culartechnologiesusedinthesourcecode?

•  Aredatabaseschemaelementsaccessedbydifferenttechnologies?

•  Focuson3par&cularJavaprojects



Distribu&onofaccessedtablesacrosstechnologies

•  HibernatecomplementsJDBC

•  JPAreplacesHibernate&JDBC

•  Tablesaccessedbyseveraltechnologies



•  MajorityoftablesaccessedbyHibernate

•  AfewtablesaccessedviaJDBC

•  SometablesaccessedbybothHibernate&JDBC




•  JPAonlyusedtechnology

•  Highnumberofunaccessedtables




UnIlintroducIonofJPA:majorityoffilesaccessingDBviaHibernate.

A8erintroducIonofJPA:progressivedecreaseof#filesaccessingDBviaHibernateandJDBC

Distribu&onoffilesaccessingthedatabase



Hibernateremainsmaintechnology

JDBCandHibernatetogetherinsomefiles

èbadcodingprac&ces?




Stabiliza&onin2013




•  MajorityofHibernatemappingsreplacedbyJPAmappings.

•  BigpartofDBschemaremainsunmapped.

•  SmallsetoftablescontainbothHibernateandJPAmappings.

Distribu&onofmappedtablesacrosstechnologies



Hibernatemaintechnology

èmajorityoftables

withHibernatemapping




JPAonlyusedtechnology

è majorityoftableswithJPAmapping



•  Coarse-grainedanalysis–  Technologiestendtobeusedincombina&on(especiallyforlargeprojects)–  Sometechnologies(Hibernate)tendtogetreplacedmoreo6en–  JPAcon&nuestoincreaseitsmarketshare–  InspiteofORMpromises,“legacy”technologies(JDBC)remainheavilyused–  Newlyintroducedtechnologiestendto“complement”exis&ngones

•  Fine-grainedanalysis–  Differentprojectswithverydifferentuseoftechnologies–  Sometablescanbeaccessedthroughdifferenttechnologies–  Somesourcecodefileusedmul&pletechnologies–  Sometables/columnsarenotaccessedèmightsuggestthatco-evolu&on

ofschemaandprogramsisnotalwaysatrivialprocess

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Conclusions


•  Broadenthescope–  Non-rela&onaldatabasetechnologies–  Closedsourceprojects–  Non-Javaprojects

•  Studysocialaspects–  Differentteamsfordifferenttechnologies?Differentteamsforcodeversusdatabase?

•  Provideautomatedtoolsupport–  Decisionalsupporttoprojectmanagerstochooseanewtechnoandtodecideif,whenandhowtointroduceit

–  Visualisa&onsupportforthecode/databaseco-evolu&onandthetechnologyco-occurrences

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FutureWork


•  LMeurice,MGoeminne,TMens,CNagy,ADecan,ACleve.AnalyzingtheevoluIonofdatabaseusageindata-intensiveso8waresystems.[Toappearinbookchapter]

•  MGoeminne,TMens.TowardsasurvivalanalysisofdatabaseframeworkusageinJavaprojects.ICSME2015ERAtrack

•  MGoeminne,ADecan,TMens.Co-evolvingcode-relatedanddatabase-relatedchangesinadata-intensiveso8waresystem.CSMR-WCRE2014ERAtrack

•  LMeurice,ACleve.DAHLIA:AvisualanalyzerofdatabaseschemaevoluIon.CSMR-WCRE2014ToolDemo

•  ACleve,MGobert,LMeurice,JMaes,JWeber.UnderstandingdatabaseschemaevoluIon:Acasestudy.ScienceofComputerProgramming(2013)

•  ACleve,TMens,J-LHainaut.Data-intensivesystemevoluIon.IEEEComputer43(8):110-112(2010)

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References