Tonic: An Infrastructure to Graphically Represent the Definition and Behaviour of Tasks

Proceedings of the 21st International Symposium on Principles and Practice of Declarative Programming

Klinik

2019

Software that models how people work is omnipresent in today's society. Current languages and frameworks often focus on usability by non-programmers, sacrificing flexibility and high level abstraction. Task-oriented programming (TOP) is a programming paradigm that aims to provide the desired level of abstraction while still being expressive enough to describe real world collaboration. It prescribes a declarative programming style to specify multi-user workflows. Workflows can be higher-order. They communicate through typed values on a local and global level. Such specifications can be turned into interactive applications for different platforms, supporting collaboration during execution. TOP has been around for more than a decade, in the forms of iTasks and mTasks, which are tailored for real-world usability. So far, it has not been given a formalisation which is suitable for formal reasoning.In this paper we give a description of the TOP paradigm and then decompose its rich features into elementary language elements, which makes them suitable for formal treatment. We use the simply typed lambda-calculus, extended with pairs and references, as a base language. On top of this language, we develop TopHat, a language for modular interactive workflows. We describe TopHat by means of a layered semantics. These layers consist of multiple big-step evaluations on expressions, and two labelled transition systems, handling user inputs.With TopHat we prepare a way to formally reason about TOP languages and programs. This approach allows for comparison with other work in the field. We have implemented the semantic rules of TopHat in Haskell, and the task layer on top of the iTasks framework. This shows that our approach is feasible, and lets us demonstrate the concepts by means of illustrative case studies. TOP has been applied in projects with the Dutch coast guard, tax office, and navy. Our work matters because formal program verification is important for mission-critical software, especially for systems with concurrency.

Section: Discussionmentioning

confidence: 99%

TopHat

Steenvoorden

Proceedings of the 21st International Symposium on Principles and Practice of Declarative Programming

Klinik

2019

“…Stutterheim et al [22] have developed Tonic, a task visualiser for iTasks with limited path prediction capabilities. The main goal is not to provide hints to end users, but the system is able to handle the complete task language, and visualise the effects of user input on the progression of tasks.…”

Section: Related Workmentioning

confidence: 99%

Generating Next Step Hints for Task Oriented Programs Using Symbolic Execution

Lecture Notes in Computer Science

Steenvoorden

2020

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.

“…Other approaches apply workflow mining to evaluate implementations [1]. Stutterheim et al [33] present a system for generating visualisations from the source code of workflow systems implemented in the iTasks workflow framework. Their system Tonic also features dynamic inspection and limited path prediction.…”

Section: Workflow Analysismentioning

confidence: 99%

End-user feedback in multi-user workflow systems

Proceedings of the 32nd Symposium on Implementation and Application of Functional Languages

Jeuring

2020

Workflow systems are more and more common due to the automation of business processes. The automation of business processes enables organizations to simplify their processes, improve services and contain costs. A problem with using workflow systems is that processes once known by heart, are now hidden from the user. This, combined with time pressure, lack of experience and an abundance of options, makes it harder for a user to make the right choices. To aid users of these systems, we have developed a multi-user rule-based problem-solving framework that can be instantiated for many workflow systems. It provides hints to the end user on how to achieve her goals and makes life for the programmer easier, as she only needs to instantiate the framework instead of programming an ad-hoc solution. Our approach consists of two parts. First, we present a domain-specific language (DSL) that offers commonly used constructs for combining components of different rule-based problems. Second, we use generic search algorithms to solve various kinds of problems. We show a practical implementation with an example workflow system. We show that this system fulfills several desirable properties. CCS CONCEPTS• Theory of computation → Formal languages and automata theory.