Domain-Specific Languages in Practice: with JetBrains MPS PDF
Preview Domain-Specific Languages in Practice: with JetBrains MPS
Antonio Bucchiarone Antonio Cicchetti · Federico Ciccozzi Alfonso Pierantonio Editors Domain-Specific Languages in Practice with JetBrains MPS Domain-Specific Languages in Practice Antonio Bucchiarone • Antonio Cicchetti • Federico Ciccozzi • Alfonso Pierantonio Editors Domain-Specific Languages in Practice with JetBrains MPS Editors AntonioBucchiarone AntonioCicchetti FondazioneBrunoKessler(FBK)-MoDiS SchoolofInnovation,Designand Trento,Italy Engineering(IDT) MälardalenUniversity Västerås,Sweden FedericoCiccozzi AlfonsoPierantonio SchoolofInnovation,Designand UniversityofL’Aquila Engineering(IDT) L’Aquila,Italy MälardalenUniversity Västerås,Sweden ISBN978-3-030-73757-3 ISBN978-3-030-73758-0 (eBook) https://doi.org/10.1007/978-3-030-73758-0 ©TheEditor(s)(ifapplicable)andTheAuthor(s),underexclusivelicensetoSpringerNatureSwitzerland AG2021 Thisworkissubjecttocopyright.AllrightsaresolelyandexclusivelylicensedbythePublisher,whether thewhole orpart ofthematerial isconcerned, specifically therights oftranslation, reprinting, reuse ofillustrations, recitation, broadcasting, reproductiononmicrofilmsorinanyotherphysicalway,and transmissionorinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilar ordissimilarmethodologynowknownorhereafterdeveloped. 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Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland Preface ThefundamentalvisionproposedbyModel-DrivenEngineering(MDE)iscoping with the complexity of reality by means of abstraction: The relevant aspects for a certain application domain are described with models, which by definition are simplifiedrepresentationsofasystemintherealworld[1].Inparticular,modelsare abstractionsof real problemsand are defined using a set of well-definedconcepts and their relationships, typically formalized in a modeling language definition. Domain-SpecificLanguages(DSLs)havebeenintroducedwiththeaimofmeeting the needs of particular application domains, industry, or business challenges, which would be less efficiently addressed by using mainstream general-purpose languages. In fact, DSLs are languages specifically defined to express problems and/orsolutionsbyusingtermsappropriateforthespecificapplicationdomainand hencefamiliartodomainexperts[2]. Language workbenches are tools with which DSLs can be designed, imple- mented, tested, and in some cases used. In this respect, they play a critical role for DSL development. A workbench should allow for a relatively easy language specification while still providing language engineers with powerful editing and automation features. Domain-specific concepts and their relationships should be specifiedtogetherwithcorrespondingsemanticsandnotations,whiletheworkbench is expected to offer generative mechanisms or interpreters deriving the necessary programming environment, notably editors, palettes, auto-completion and valida- tionfeatures,persistenceandversioning,andsoforth[3].Needlesstosay,additional capabilitiesforsupportinglanguageextension,refinement,andmaintenanceareof paramountrelevanceforthesuccessofindustry-strengthDSLstoo. MPS, short for Meta Programming System, is an open source language workbenchdevelopedby JetBrains overthe last 15 years. It is used to implement languagesforreal-worlduse.Itsdistinguishingfeatureisprojectionalediting,which supportsalmostunlimited languageextensionand compositionpossibilities [4]as wellasaflexiblemixofawiderangeoftextual,tabular,mathematical,andgraphical notations[5]. Thisbookisdesignedasanaccessiblemeanstointroducethereaderstoand/or deepentheirexistingknowledgeofMPS. v vi Preface The book begins with an overview of the domain of language workbenches, which provides perspectives and motivations underpinning the creation of MPS. Moreover, technical details of the language underneath MPS together with the definitionofthetool’smainfeaturesarediscussedinchapter“JetBrainsMPS:Why ModernLanguageWorkbenchesMatter”. Followingthis Introduction,the volume isorganizedintothreeparts,eachdedicatedtoaspecificaspectofthetopic. MPS inIndustrialApplications Chapters “Use MPS to Unleash the Creativity of Domain Experts: Language Engineering Is a Key Enabler for Bringing Innovation in Industry”, “JetBrains MPS as Core DSL Technology for Developing Professional Digital Printers”, “A Domain-Specific Language for Payroll Calculations: An Experience Report from DATEV”, “FASTEN: An Extensible Platform to Experiment with Rigorous Modeling of Safety-Critical Systems” and “Migrating Insurance Calculation Rule DescriptionsfromWordtoMPS”presenttheuseofMPSinindustrialapplications. Theycoverthe challengesandinadequaciesof general-purposelanguagesused in companies,as opposedto the reasonswhy DSLs are essential, together with their benefitsandefficiency;moreover,theysummarizelessonslearntbyusingMPS. Chapter “Use MPS to Unleash the Creativity of Domain Experts: Language Engineering Is a Key Enabler for Bringing Innovation in Industry” introduces the experiences gained by utilizing MPS in smart factory, finance, and medical domains.ThechapterdescribeshowappropriateDSLscouldbedefinedbymeans ofMPStogetherwiththeireffectivenessinallowingexpertstoexploreandenhance their domain-specific knowledge. Moreover,the chapter places MPS in a broader perspective of core DSL engineering by discussing language adoption and the most frequentlyused features. Chapter “JetBrains MPS as Core DSL Technology for Developing Professional Digital Printers” reports on how the adoption of MPS canlead to efficientand continuousinnovationwith sustainable quality.The innovation is brought by means of new DSLs supporting feature management and tool chaining for an industrial production application. Once a new DSL is introduced in the industrial ecosystem, its functionality and suitability are tested andevaluated.Chapter“ADomain-SpecificLanguageforPayrollCalculations:An Experience Report from DATEV” reviews the developmentprocess of a DSL for payrollcalculationsbymeansofMPS.Interestingly,theintroductionoftheDSLis based on the demonstrated higher efficiency of using a DSL to deal with domain complexitydriversincomparisontoageneral-purposelanguage.Theimplemented DSL has reached an advanced maturity level and includes relevant features such as versioning, re-use, and testing. Chapter “FASTEN: An Extensible Platform to Experiment with Rigorous Modeling of Safety-Critical Systems” introduces an open source research environment for model-based specification and design of safety-criticalapplicationsanddescribesitscharacteristicsasacollectionofDSLs. The chapter surveys the DSLs, and their development and utilization, and then Preface vii proposes a discussion of the lessons learnt by implementing them focusing on the features of MPS that enabled that. Another industrial application is reported in chapter “Migrating Insurance Calculation Rule Descriptions from Word to MPS”, where existing C code plus natural language specifications in Word were reverse-engineeredtowardaDSLunderadoptionintheassurancedomain.Indeed, the underlying goal is to perform a structural cleanup and splitting into small independentunitsoftheexistingroutines.Theincrementaladoptionprocessofthe DSL is discussed together with a demonstrationof its effective results, especially withrespecttoversioningandmemoryhandling. MPS inResearch Projects MPS implementations in research projects are discussed in chapters “Projecting TextualLanguages”,“EngineeringGamefulApplicationswithMPS”,and“Learn- ing Data Analysis with MetaR”: these projects cover the benefits of text-based languages, the design and developmentof gamification applications, and research fields with generally low expertise in language engineering. One of the strengths of MPS, the provision of a mixture of different notations, is discussed in chapter “ProjectingTextualLanguages”.In particular,thechapterpresentsan approachto automaticallymapgrammar-basedlanguagedefinitionstowardcorrespondingDSLs specified by MPS. Another research effort based on MPS features is presented in chapter “Engineering Gameful Applications with MPS”, which illustrates the creation of a gamification design framework as a collection of DSLs. Each DSL addresses specific concerns of a gamification application design and deployment, whiletheMPSlanguageworkbenchprovidesconsistencybyconstructionthrough language extension mechanisms. Chapter “Learning Data Analysis with MetaR” introducesa case study related to a tool designedto facilitate the use of DSLs by researcherswithnontechnicalbackground.Inotherwords,aDSLcreatedbymeans of MPS acts as a meta-toolto enhance the user-friendlinessof the base tool. Yet, thanks to the features embedded in MPS, the tool includes language composition for expert users, such that the meta-tool can be further extended and tailored to specificneeds. TeachingandLearning with MPS Chapters“TeachingMPS:ExperiencesfromIndustryandAcademia”and“Teaching LanguageEngineeringUsing MPS” present experienceson teaching and learning with MPS. Chapter “Teaching MPS: Experiences from Industry and Academia” focuses on teaching both industrial professionals and academic students. In par- ticular, the chapter discusses the organizationof academic courses on MPS: first, thebasicsoftext-basedlanguageworkbenchesareprovided,andthenthetechnical viii Preface details of MPS are presented. In this way, students can capture the distinctive characteristics of MPS. Instead, chapter “Teaching Language Engineering Using MPS” introduces the principles involved in DSL design and development in conjunctionwith compiler theory,and then shows how MPS can be exploited for thepracticalimplementationofthoseprinciples. To summarize, this book covers several topics related to DSL engineering in generalandhowtheycanbehandledbymeansoftheJetBrainsMPS.Thenumber and diversity of the presented use-case demonstrate the strength and malleability of the DSLs defined using MPS. The selected contributions, which represent the currentstateoftheartandpracticeinusingJetBrainsMPStoimplementlanguages forreal-worldapplications,areexpectedtobeofgreatinterestfortheModel-Driven andSoftwareLanguagesEngineeringcommunities. Perspectives The insights brought by the book indicate that MDE’s state of the art and practicedisplaythegrowingsuccessoflanguageworkbenchessupportingvarious, sometimes blended [6], notations (Rascal [7], xText [8], and MPS, to mention a few). Seamless blended notations can bring several benefits, among them flexible separationofconcerns,multiviewmodelingbasedonmultiplenotations,convenient text-based editing operations (inside and outside the modeling environment), and eventuallyfaster modelingactivities [9]. In this respect, specifyingmodelsas text may providegreatadvantagesvia the leverage of text manipulationtools, such as text-based diff/merge, while leaving open the possibility of rendering portions of modelsin a diagrammaticform(interestingly,the upcomingSysML v2[10]takes thisdirectionbyprovidingatextualsyntax). One of the reasonsforthe success oftext-basedlanguageworkbenchesistheir pragmaticapproach:the simple definition of a (E)BNF grammar,i.e., the abstract syntax, is usually enough to create the first prototype of a DSL, while concrete syntaxescanbe incrementallyrefined.Thisisthe case forMPS, whichallowsthe quickcreationoffullyfledgedtext-basedDSLswithlimitedeffort,bydefiningaset of concepts, their properties, and relationships. Moreover, its projectional editing conveysastructuredapproachtothecreation,visualization,andeditingofmodels. Anopenissue,commontomostlanguageworkbenches,istheeffortrequiredfor largecustomizations,includingtheirmaintenanceincaseoflanguageevolution.In thisrespect,MPSprovidesthepossibilitytoalleviatemaintenanceissuesthrougha powerfullanguageextensionmechanism.Indeed,severalchaptersinthebookrefer to these mechanisms as one of the most relevant features of MPS. Moreover, the movement toward web- and cloud-based solutions has affected the way language workbenches are designed and evolved; this applies to MPS too, for which fully fledgedweb-basedsolutions(e.g.,ModelixDSL1)areunderdevelopment. 1https://modelix.github.io/ Preface ix Acknowledgments The editors would like to express their deepest gratitude to all the authors who havesubmittedtheirvaluablecontributionsandhaveprovidedtheirhighlyqualified expertise in reviewing the chapters included in this book. Moreover, they would like to thank RobertWalter—Senior Software DeveloperatUnity Technologies— andFedericoTomassetti—SoftwareLanguageEngineeringexpertandCo-founder atStrumenta—fortheirprofessionalsupportinreviewingsomeofthechapters.The editorswouldalsoliketothanktheSpringerstafffortheircontinuoussupportand dedication.In particular,the tireless supportfrom Ralf Gerstner,ExecutiveEditor forComputerScienceatSpringer,hasbeengreatlyappreciated. Trento,Italy AntonioBucchiarone Västerås,Sweden AntonioCicchetti Västerås,Sweden FedericoCiccozzi L’Aquila,Italy AlfonsoPierantonio References 1. Schmidt, D.C.: Guest Editor’sIntroduction:Model-drivenengineering.Com- puter,39(2),25–31(2006).https://doi.org/10.1109/MC.2006.58 2. vanDeursen,A.,Klint,P.,Visser,J.:Domain-specificlanguages:anannotated bibliography.SIGPLANNot.35(6),26–36. https://doi.org/10.1145/352029.352035 3. Voelter,M.,Benz,S.,Dietrich,C.,Engelmann,B.,Helander,M.,Kats,L.C.L., Visser, E., Wachsmuth, G.: DSL engineering – designing, implementing and using domain-specific languages, pp. 1–558. dslbook.org, ISBN 978-1-4812- 1858-0(2013) 4. Voelter, M.: Language and IDE modularization and composition with MPS. In:GenerativeandtransformationaltechniquesinsoftwareengineeringIV,pp 383–430.Springer(2013) 5. Voelter, M., Lisson, S.: Supporting diverse notations in MPS’ projectional editor.GEMOC@MoDELS2014,pp.7–16 6. Ciccozzi,F.,Tichy,M.,Vangheluwe,H.,Weyns,D.:Blendedmodelling-what, why and how. In: 2019 ACM/IEEE 22nd InternationalConference on Model Driven Engineering Languages and Systems Companion (MODELS-C), pp. 425–430.IEEE(2019) 7. Klint,P.,vanderStorm,T.,Vinju,J.J.:RASCAL:Adomainspecificlanguage for source code analysis and manipulation. In: SCAM, pp. 168–177. IEEE (2009) 8. Eysholdt, M., Behrens, H.: Xtext: Implement your language faster than the quickanddirtyway.In:SPLASHCompanion,pp.307–309.ACM(2010) x Preface 9. Addazi, L., Ciccozzi, F. (2021). Blended graphical and textual modelling for UML profiles: a proof-of-concept implementation and experiment. J. Syst. Softw.110912 10. ObjectManagementGroup.https://www.omgsysml.org/
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