TopHat

Steenvoorden, Tim; Naus, Nico; Klinik, M.A.A.

doi:10.1145/3354166.3354182

Cited by 5 publications

(3 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally, there are TOP languages with strong academic foundations. TopHat is a fully formally specified TOP language designed to capture the essence of TOP (Steenvoorden et al, 2019). Such a formal specification allows for symbolic execution, hint generation, but also the translation to iTask for actually performing the work (Steenvoorden, 2022).…”

Section: Other Top Languagesmentioning

confidence: 99%

“…Both semantics are not suitable for formal reasoning due to the complexity. Later, Steenvoorden et al (2019) created TopHat, a TOP language with a complete formal specification with similar features to mTask (Steenvoorden et al, 2019). Antonova (2022) compared parts of mTask to the semantics of TopHat semantics and created a preliminary semantics for a subset of mTask.…”

Section: Formal Semanticsmentioning

confidence: 99%

“…For example, if the language has a formal semantics, as Links, Hop and Clean tasks do (Cooper et al, 2007;Plasmeijer et al, 2012;Serrano et al, 2006), it is possible to prove properties of the system, e.g. (Steenvoorden et al, 2019). As another example program analyses can be applied, and section 10.3.3 and (Weisenburger et al, 2020) outline some of the analyses could be, and in some cases have been, used to improve IoT systems.…”

Section: Reflectionsmentioning

confidence: 99%

See 2 more Smart Citations

Orchestrating the Internet of Things with Task-Oriented Programming

Lubbers

2023

View full text Add to dashboard Cite

The development of reliable software for the internet of things (IoT) is difficult because IoT systems are dynamic, interactive, distributed, collaborative, multi-tiered, and multitasking in nature. The complexity is increased further by semantic friction that arises through different hardware and software characteristics between tiers. Many computers that operate in IoT systems are edge devices that interact with the environment using sensors and actuators. Edge devices are often powered by low-cost microcontrollers designed for embedded applications. They have little memory, unhurried processors, and are slow in communication but are also small and energy efficient. Task-oriented programming (TOP) can cope with the challenges of IoT programming. In TOP, the main building blocks are tasks, an abstract representation of work. During execution, the current value of the task is observable, and other tasks can act upon it. Collaboration patterns can be modelled by combining and transforming tasks into compound tasks. Programming edge devices benefits from TOP as well, but running such a system within the limitations of resource-constrained microcontrollers is not straightforward. This dissertation demonstrates how to include edge devices in TOP systems using domain-specific languages (DSLs). With these techniques, all tiers and their interoperation of an IoT system are specified in a single high-level source, language, paradigm, high abstraction level, and type system. First, I present advanced DSL embedding techniques. Then mTask is shown, a TOP DSL for IoT edge devices, embedded in iTask. Tasks are constructed and compiled at run time in order to allow tasks to be tailored to the current work requirements. The task is then sent to the device for interpretation. A device is programmed once with a lightweight domain-specific OS to be used in an mTask system. This OS executes tasks in an energy-efficient way and automates all communications and data sharing. All aspects of the mTask system are shown: example applications, language design, implementation details, integration with iTask, and green computing facilities such as automatic sleeping. Finally, tierless IoT programming is compared to traditional tiered programming. In tierless programming frameworks, the size of the code and the number of required programming languages is reduced significantly. By using a single paradigm and a system-wide type system, tierless programming reduces problems such as semantic friction; maintainability and robustness issues; and interoperation safety.

show abstract

Section: Other Top Languagesmentioning

confidence: 99%

Section: Formal Semanticsmentioning

confidence: 99%

Section: Reflectionsmentioning

confidence: 99%

See 1 more Smart Citation

Orchestrating the Internet of Things with Task-Oriented Programming

Lubbers

2023

View full text Add to dashboard Cite

show abstract

Generating Next Step Hints for Task Oriented Programs Using Symbolic Execution

Naus

Steenvoorden

2020

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

Software that models business workflows is omnipresent in today's society. These systems coordinate collaboration in hospitals, companies, and military institutions. Unfortunately, workflow systems may obfuscate the influence of current user actions on the desired end result. In order to make the right decision, users need to oversee the full process and all information available, both of which are usually buried in the system. We have developed a way to automatically generate next step hints for task oriented programs. Task oriented programming provides programmers with an abstraction over workflow software, while still being expressive enough to describe real world collaboration. By leveraging symbolic execution, we can calculate these hints without modification of the original program. To our knowledge, this is the first time that symbolic execution is used to automatically generate next step hints for end users. We prove the generated hints to be sound and complete, and also demonstrate that the symbolic execution semantics we employ is correct for sequential input. In addition, we have developed a Haskell implementation of our automatic next step hint generation system. By providing next step hints, the chance of human error is reduced, while still allowing end users to intervene if required. The overall performance is raised, since the quality of decisions will improve.

show abstract

Semantic Equivalence of Task-Oriented Programs in TopHat

Klijnsma

Steenvoorden

2022

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Task-oriented programming (top) is a new programming paradigm for specifying multi-user workflows. To reason formally about top programs, a formal language called TopHat has been designed, together with its operational semantics. For proving properties about task-oriented programs, it is desirable to know when two TopHat-programs are semantically equivalent. This paper aims to answer this question. We show that a task can be in either one of five conditions, and for every two tasks in the same condition, we define what it means for them to be semantically equivalent. Using this definition, we study a number of transformation laws for TopHat-programs, which can be used by developers and compilers to optimise top-programs. We show that the "Image missing" operation on types in TopHat is a functor but cannot be a monad. We support our findings with proofs formalised in the dependently typed programming language Idris.

show abstract

TopHat

Cited by 5 publications

References 18 publications

Orchestrating the Internet of Things with Task-Oriented Programming

Orchestrating the Internet of Things with Task-Oriented Programming

Generating Next Step Hints for Task Oriented Programs Using Symbolic Execution

Semantic Equivalence of Task-Oriented Programs in TopHat

Contact Info

Product

Resources

About