Modeling History to Understand Software Evolution with Hismo 2008-03-12

Modeling History to Understand Software Evolution Tudor Gîrba www.tudorgirba.com

Modeling History to Understand Software Evolution Inauguraldissertation der Philosophisch-naturwissenschaftlichen Fakultät der Universität Bern vorgelegt von Tudor Gîrba von Rumänien Leiter der Arbeit: Prof. Dr. Stéphane Ducasse Prof. Dr. Oscar Nierstrasz Institut für Informatik und angewandte Mathematik

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fo rw ar d en gin ee rin g { { { { { { } { { } } actual development } } } { } } }

fo rw g rin ar ee d gin en gin en ee se rin erv g re { { { { { { } { { } } actual development } } } { } } }

{ { } } } { { { } } re v er se en gin ee rin g reverse engineering fo actual development rw ar d en gin ee rin g { { } } { { } }

Most often time is put on the horizontal and a property on the vertical axis. Lehman etal, 2001

Evolution Matrix shows how classes evolve. Time is still on the horizontal axis. Lanza, Ducasse, 2002

Co-change analysis recovers hidden dependencies. Time is the lines. Gall etal, 2003

Evolution information can be mapped on structural information. Eick etal, 2002

Eick etal, 2002 Lehman etal, 2001 ... Lanza, Ducasse, 2002 Gall etal, 2003

Eick etal, 2002 es? niqu tech Lehman etal, 2001 ese ll th da te a om mo we acc can ow H ... Lanza, Ducasse, 2002 Gall etal, 2003

sh ort int er me zzo What is a model?

sh ort int er me zzo A model is a simpliﬁcation of the subject, and its purpose is to answer some particular questions aimed towards the subject. Bezivin, Gerbe, 2001

sh ort int er me zzo what is a meta-model?

sh ort int er me zzo a meta-model is a model that makes statements about what can be expressed in valid models. Seidewitz, 2003

sh ort int er me zzo a good meta-model allows for succinct expression of analyses.

Eick etal, 2002 Lehman etal, 2001 ... Lanza, Ducasse, 2002 Gall etal, 2003

Eick etal, 2002 es? niqu tech Lehman etal, 2001 ese ll th da te a om mo we acc can ow H ... Lanza, Ducasse, 2002 Gall etal, 2003

Evolution Matrix shows class changes. Lanza, Ducasse, 2004 Idle class Pulsar class Supernova class attributes White dwarf class methods Class

Evolution Matrix shows class changes. Lanza, Ducasse, 2004 Idle class entity. st c lass Pulsar da s ﬁr class mo dele to be needs Supernova tio n class Evolu attributes White dwarf class methods Class

Evolution Matrix shows class changes. Lanza, Ducasse, 2004 Idle class Pulsar class Supernova class attributes White dwarf class methods Class

Evolution Matrix shows class changes. Idle class history Pulsar class history Supernova class history ClassHistory White dwarf isPulsar class history isIdle ...

System Version Class Version

System Version Class Class History Version

System System History Version Class Class History Version

System System History Version en tity. st c lass 200 5 ya s ﬁr Gir ba, tor l s his m ode H ismo Class Class History Version

Measuring Yesterday’s Time-based history Weather Detection Strategies 1 2 3 4 5 6 Visualizing the evolution Detecting How developers of hierarchies co-change patterns drive evolution

Measuring history 1

What changed? When did it change? ... 2 4 3 5 7 2 2 3 4 9 2 2 1 2 3 2 2 2 2 2 1 5 3 4 4

Evolution of Number of Methods LENOM(C) = ∑ |NOMi(C)-NOMi-1(C)| 2i-n LENOM(C) = 4 + 2 + 1 + 0 = 7 1 5 3 4 4

Latest Evolution of Number of Methods LENOM(C) = ∑ |NOMi(C)-NOMi-1(C)| 2i-n Earliest Evolution of Number of Methods EENOM(C) = ∑ |NOMi(C)-NOMi-1(C)| 22-i -3 -2 -1 0 LENOM(C) = 42 + 22 + 12 + 02 = 1.5 1 5 3 4 4 EENOM(C) = 4 20 + 2 2-1 + 1 2-2 + 0 2-3 = 5.25

ENOM LENOM EENOM 2 4 3 5 7 7 3.5 3.25 2 2 3 4 9 7 5.75 1.37 2 2 1 2 3 3 1 2 2 2 2 2 2 0 0 0 1 5 3 4 4 7 1.25 5.25

ENOM LENOM EENOM balanced changer 7 3.5 3.25 late changer 7 5.75 1.37 3 1 2 dead stable 0 0 0 early changer 7 1.25 5.25

ENOM LENOM EENOM balanced changer 7 3.5 3.25 late changer 7 tity 5.75 nts. 1.37 en ureme lass eas st c gh m s ﬁr rou 3 y a th 1 2 r H isto rison co mpa deadsstable ena ble 0 0 0 early changer 7 1.25 5.25

History can be measured in many ways. Evolution Number of Methods Stability Number of Lines of Code Historical Max of Cyclomatic Complexity Growth Trend Number of Modules ... ...

Yesterday’s weather 2

The recently changed parts are likely to change in the near future. Common wisdom

The recently changed parts are likely to change in the near future. ally? Common wisdom re re they A

30% 90%

present

past present

past future present

past future prediction hit present

past future YesterdayWeatherHit(present): past:=histories.topLENOM(start, present) future:=histories.topEENOM(present, end) past.intersectWith(future).notEmpty() prediction hit present

Overall Yesterday’s Weather shows the localization of changed in time. Girba etal, 2004 hit hit hit YW = 3 / 8 = 37% hit hit hit hit hit hit hit YW = 7 / 8 = 87%

Time-based Detection Strategies 3

Detection Strategies are metric-based queries to detect design ﬂaws. Lanza, Marinescu 2006 Rule 1 METRIC 1 > Threshold 1 AND Quality problem Rule 2 METRIC 2 < Threshold 2

Example: a God Class centralizes too much intelligence in the system. Class uses directly more than a few attributes of other classes ATFD > FEW Functional complexity of the class is very high AND GodClass WMC ! VERY HIGH Class cohesion is low TCC < ONE THIRD

Example: a God Class centralizes too much intelligence in the system. Class uses directly more than a few attributes of other classes ATFD > FEW tab le? f it is s wh Functional complexity of the at i ut, class is very high B AND GodClass WMC ! VERY HIGH Class cohesion is low TCC < ONE THIRD

History-based Detection Strategies take evolution into account. Ratiu etal, 2004 God Class in the last version isGodClass(last) AND Harmless God Class Stable throughout the history Stability > 90%

History-based Detection Strategies take evolution into account. Ratiu etal, 2004 me. God Class in the last version sa ed the isGodClass(last) eat e tr pace ar an ds AND Harmless God Class e Tim Stable throughout the history Stability > 90%

Visualizing the evolution of hierarchies 4

What happens with inheritance? A A A A A B C B C B C B B D D D E ver .1 ver. 2 ver. 3 ver. 4 ver. 5

History contains too much data. A A A A A A A A A A A A A A A A A A A A B C B C B C B B B C B C B C B B B C B C B C B B B C B C B C B B D D D E D D D E D D D E D D D E ver .1 ver. 2 ver. 3 ver. 4 ver. 5 ver .1 ver. 2 ver. 3 ver. 4 ver. 5 ver .1 ver. 2 ver. 3 ver. 4 ver. 5 ver .1 ver. 2 ver. 3 ver. 4 ver. 5 A A A A A A A A A A A A A A A A A A A A B C B C B C B B B C B C B C B B B C B C B C B B B C B C B C B B D D D E D D D E D D D E D D D E ver .1 ver. 2 ver. 3 ver. 4 ver. 5 ver .1 ver. 2 ver. 3 ver. 4 ver. 5 ver .1 ver. 2 ver. 3 ver. 4 ver. 5 ver .1 ver. 2 ver. 3 ver. 4 ver. 5 A A A A A A A A A A A A A A A A A A A A B C B C B C B B B C B C B C B B B C B C B C B B B C B C B C B B D D D E D D D E D D D E D D D E ver .1 ver. 2 ver. 3 ver. 4 ver. 5 ver .1 ver. 2 ver. 3 ver. 4 ver. 5 ver .1 ver. 2 ver. 3 ver. 4 ver. 5 ver .1 ver. 2 ver. 3 ver. 4 ver. 5 A A A A A A A A A A A A A A A A A A A A B C B C B C B B B C B C B C B B B C B C B C B B B C B C B C B B D D D E D D D E D D D E D D D E ver .1 ver. 2 ver. 3 ver. 4 ver. 5 ver .1 ver. 2 ver. 3 ver. 4 ver. 5 ver .1 ver. 2 ver. 3 ver. 4 ver. 5 ver .1 ver. 2 ver. 3 ver. 4 ver. 5

System System History Version Class Class History Version

System System History Version Inheritance Version Class Class History Version

System System History Version Inheritance Inheritance History Version Class Class History Version

A A A A A B C B C B C B B D D D E ver .1 ver. 2 ver. 3 ver. 4 ver. 5 A is persistent, B is stable, C was removed, E is newborn ...

Hierarchy Evolution View encapsulates time. Girba etal, 2005 A changed methods changed age lines C B Removed Removed D E A is persistent, B is stable, C was removed, E is newborn ...

Hierarchy Evolution View reveals patterns. Girba etal, 2005

Hierarchy Evolution View reveals patterns. Girba etal, 2005 ntity . ss e aph t cla a gr ﬁrs to as ing tory mapp His les e nab

Identifying co-change patterns 5

1 2 3 4 5 6 A A B B E C D E C D Gall etal, ‘98

Co-change patterns are n-ary relationships.

1 2 3 4 5 6 A B C D Version E

1 2 3 4 5 6 A B C D Version E changed

1 2 3 4 5 6 A History changed(i) B C D Version E changed

What is Concept Analysis?

1 2 3 4 5 6 A B C D E

{A, B, C, D, E} 1 2 3 4 5 6 Ø A {A, D, B} {A, E, C, D} {2} {6} B {D, B} {A, D} {A, E, C} C FCA {2, 4} {2, 6} {5, 6} D {D} {A} {C} E {2, 4, 6} {2, 5, 6} {3, 5, 6} Ø {1, 2, 3, 4, 5, 6}

{A, B, C, D, E} 1 2 3 4 5 6 Ø A {A, D, B} {A, E, C, D} {2} {6} B {D, B} {A, D} {A, E, C} C FCA {2, 4} {2, 6} {5, 6} D {D} {A} {C} E {2, 4, 6} {2, 5, 6} {3, 5, 6} Ø {1, 2, 3, 4, 5, 6} Girba etal, 2007

Parallel Inheritance add simultaneously children to several classes Shotgun Surgery change several classes simultaneously, but do not add methods

{A, B, C, D, E} 1 2 3 4 5 6 Ø A {A, D, B} {A, E, C, D} {2} {6} B {D, B} {A, D} {A, E, C} C FCA {2, 4} {2, 6} {5, 6} D {D} {A} {C} E {2, 4, 6} {2, 5, 6} {3, 5, 6} Ø {1, 2, 3, 4, 5, 6}

{A, B, C, D, E} 1 2 3 4 5 6 Ø A {A, D, B} {A, E, C, D} {2} {6} tity B s en A. st clas {D, B} FC ﬁrFCA g to{2, 4} {A, D} {A, E, C} y as appin C {2, 6} {5, 6} stor s m Hi ble D ena {D} {A} {C} E {2, 4, 6} {2, 5, 6} {3, 5, 6} Ø {1, 2, 3, 4, 5, 6}

How developers drive software evolution 6

CVS shows activity.

Who is responsible for this?

Alphabetical order is no order.

The Hausdorf metric can be used to compute the similarity between commits. A d(A, B) = ∑ min2{ | a - b | b in B } a in A B

Alphabetical order is no order.

Ownership Map reveals development patterns. Girba etal, 2006

Ownership Map reveals development patterns. Girba etal, 2006 tity anges. s en c ch clas listi rst ho as ﬁ out tory ing ab His son les rea enab

Measuring Yesterday’s Time-based history Weather Detection Strategies 1 2 3 4 5 6 Visualizing the evolution Detecting How developers of hierarchies co-change patterns drive evolution

System System History Version Inheritance Inheritance History Version Class Class History Version

History Version History Version History Version

History Version en tity. st c lass 200 5 as ﬁr Gir ba, his tory History Version mo dels Hi smo History Version

Modeling History to Understand Software Evolution Inauguraldissertation der Philosophisch-naturwissenschaftlichen Fakultät der Universität Bern vorgelegt von Tudor Gîrba von Rumänien Leiter der Arbeit: Prof. Dr. Stéphane Ducasse Prof. Dr. Oscar Nierstrasz Institut für Informatik und angewandte Mathematik www.tudorgirba.com

Tudor Gîrba www.tudorgirba.com creativecommons.org/licenses/by/3.0/

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Modeling History to Understand Software Evolution with Hismo 2008-03-12

by Tudor Girba on Mar 16, 2008

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