DREMS ML: A wide spectrum architecture design language for distributed computing platforms

Balasubramanian, Daniel; Dubey, Abhishek; Otte, William R.; Levendovszky, Tihamér; Gokhale, Aniruddha; Kumar, Pranav Srinivas; Emfinger, William; Karsai, Gábor

doi:10.1016/j.scico.2015.04.002

Cited by 8 publications

(10 citation statements)

References 9 publications

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“…Herein, the focus is on the specifications of software architectures, the functional/nonfunctional requirements, the analysis of the software architecture specifications for the desired requirements, and the generation of software code from the specifications. The ALs do not unfortunately support all these activities of software development, except Palladio and Drems ML …”

Section: Discussionmentioning

confidence: 99%

“…However, specifying nonfunctional properties would not be so useful unless it was possible to analyze the specified design decisions (eg, system behaviors and interaction) against the property specifications. When the automated analysis was also 14,15 Performance, schedulability, security, dependability, and reliability CBabel 58,59 Via a QoS language 59 Clara 60 Performance ConMoto 61 Any Drems ML 64 Security, schedulability, resource consumption, performance East ADL 32 Safety, performance Palladio 67 Performance TADL 71 Safety, security, availability, and reliability UNAS/SALE 72 Performance, reliability, and scalability considered, only the 9 ALs shown in Table 6 have been observed to support the automated analysis of the design decisions for the nonfunctional requirements.…”

Section: Discussionmentioning

confidence: 99%

“…All the ALs considered in this study offer an architecture‐oriented notation set. However, when some other activities of software design are considered such as functional/nonfunctional requirement specifications, the analysis of software architectures for the requirements, and the translation of architectures into software implementation, just Palladio and Drems‐ML support all these activities together.…”

Section: Summary Of Findingsmentioning

confidence: 99%

“…Note also that textual notation sets let practitioners specify really large and complex systems in a reasonable space. Visual notation sets may essentially be preferred by practitioners who do not have that experience 14,15 Performance, schedulability, and reliability -Annex -Informal notation ABACUS 56 Performance and reliability Informal notation Primitive-C 57 Safety security, performance, portability Informal notation AO-ADL 51 General Aspect-oriented notation AWright 27 General Aspect-oriented CBabel 58,59 General QoS contracts Clara 60 Timeliness Timed Petri nets ConMoto 61 General π-calculus Cosa 62 General Informal notation DADL 63 Performance Informal notation Drems ML 64 Security, schedulability, network resource, performance Object Constraint Language East ADL 32 Safety, performance -Extension packages -Informal notation Modechart 65,66 Performance Real-time logic Palladio 67 Performance Informal graphical notation Prisma 28 General Aspect-oriented notation Aspectual Acme 37 General Aspect-oriented notation RADL 43 Reliability Finite-state machine SADL 68 Schedulability Informal graphical notation SARA 53 Performance Graphical model behavior (GMB) ScudADL 69,70 Resource consumption π-calculus Secure XADL 34 Security XML-based notation TADL 71 Safety, performance, security, availability, and reliability Timed automata UNAS/SALE 72 Performance, reliability, and scalability Informal graphical notation X-MAN 73,74 Reliability Design-by-Contract-based notation MetaH 31 Schedulability, reliability, and security Informal graphical notation Stratus ML 75 Availability, performance Informal graphical notation in architectural modeling and, thus, prefer to express their software architectures by drawing visual diagrams (as is done with the UML language). Visual notation sets can also be preferred if the main intent is effective communication.…”

Section: Textual and Visual Notation Setsmentioning

confidence: 99%

“…C2SADEL, 41 XC2, 42 ArchJava, 152 SOFA, 156,157 Java Zeta, 85 π-ADL, 91 X-ADL, 34 Backbone, 95 Fractal, 46,47 KADL, 39 AspectLeda, 45 FAC, 48 DiaSpec, 102 Palladio, 67 ArchFace, 176 Korrigan, 38 MontiArc, 104,105 ABC/ADL, 173 Dedal, 103 Lisa, 186 FuseJ, 178 AO-ADL, 51 Resolve 131 UniCon, 77 Gestalt, 191 Knit, 193 Koala, 16 Autosar, 179 C X-Man, 73,74 Statemate, 168,169 OCA, 170,171 ADLV 194,195 UNAS/SALE, 72 MetaH, 31 Resolve, 131 Statemate, 168,169 Ada OCA 170,171 ADLV, 194,195 Aesop, 190 Room, 192 Drems ML, 64…”

Section: Architectural Languages Programming Languagementioning

confidence: 99%

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The analysis of architectural languages for the needs of practitioners

Özkaya

2018

Softw Pract Exp

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Summary Architectural languages (ALs) have attracted much attention as the modeling notations for specifying and reasoning about important design decisions. In this study, 124 different existing ALs have been analyzed for a set of requirements that are crucial for practitioners. These requirements are concerned with language definition, language features, and tool support. Some of the important findings obtained from the analysis are as follows: (1) performance is the top popular nonfunctional requirement supported by ALs; (2) no ALs offer both textual and visual notation sets, one of which could be used independently; (3) process algebras are the top preferred formal method by formal ALs; (4) the physical, deployment, and operational viewpoints are rarely supported by ALs; (5) the top preferred extension mechanism of the extensible ALs is XML for syntax extension; (6) Java is the top preferred programming language in generating software code; (7) the exhaustive model checking is the top preferred automated analysis method; (8) the logic‐based formal techniques are so popular in specifying system requirements; (9) among the analysis properties considered, consistency is the top supported property for the automated checking; and (10) most ALs do not provide any discussion platform (eg, forums). Hence, these findings can be used by the new AL developers in addressing the needs of practitioners and bridging the gaps in the field. Practitioners can also use the findings to find out about the existing ALs and compare them to choose the one(s) that suits their needs best.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Summary Of Findingsmentioning

confidence: 99%

Section: Textual and Visual Notation Setsmentioning

confidence: 99%

Section: Architectural Languages Programming Languagementioning

confidence: 99%

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The analysis of architectural languages for the needs of practitioners

Özkaya

2018

Softw Pract Exp

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Cyber security risk assessment for seaports: A case study of a container port

Gunes¹,

Kayisoglu

Bolat

2021

Computers & Security

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Achieving resilience in distributed software systems via self-reconfiguration

Pradhan

Dubey

Levendovszky

et al. 2016

Journal of Systems and Software

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Improvements in mobile networking combined with the ubiquitous availability and adoption of low-cost development boards have enabled the vision of mobile platforms of Cyber-Physical Systems (CPS), such as fractionated spacecraft and UAV swarms. Computation and communication resources, sensors, and actuators that are shared among different applications characterize these systems. The cyber-physical nature of these systems means that physical environments can affect both the resource availability and software applications that depend on resource availability. While many application development and management challenges associated with such systems have been described in existing literature, resilient operation and execution have received less attention. This paper describes our work on improving runtime support for resilience in mobile CPS, with a special focus on our runtime infrastructure that provides autonomous resilience via selfreconfiguration. We also describe the interplay between this runtime infrastructure and our design-time tools, as the later is used to statically determine the resilience properties of the former. Finally, we present a use case study to demonstrate and evaluate our design-time resilience analysis and runtime self-reconfiguration infrastructure.

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DREMS ML: A wide spectrum architecture design language for distributed computing platforms

Cited by 8 publications

References 9 publications

The analysis of architectural languages for the needs of practitioners

The analysis of architectural languages for the needs of practitioners

Cyber security risk assessment for seaports: A case study of a container port

Achieving resilience in distributed software systems via self-reconfiguration

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