On coordination tools in the PicOS tuples system

Shimony, Benny; Nikolaidis, Ioanis; Gburzyński, Paweł; Stroulia, Eleni

doi:10.1145/1988051.1988056

Cited by 9 publications

(6 citation statements)

References 23 publications

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“…Evolving b-programs combines the benefits of both approaches: We employ the natural and convenient representation of ASTs, while still maintaining benefits gained from a binary representation, since the paradigm has been implemented in many underlying languages, including Java [16], JavaScript [1], C [17], LSC [18], and more.…”

Section: Representationmentioning

confidence: 99%

From Requirements to Source Code: Evolution of Behavioral Programs

2022

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Automatically generating executable code has a long history of arguably modest success, mostly limited to the generation of small programs of up to 200 lines of code, and genetic improvement of existing code. We present the use of genetic programming (GP) in conjunction with context-oriented behavioral programming (COBP), the latter being a programming paradigm with unique characteristics that facilitate automatic coding. COBP models a program as a set of behavioral threads (b-threads), each aligned to a single behavior or requirement of the system. To evolve behavioral programs we design viable and effective genetic operators, a genetic representation, and evaluation methods. The simplicity of the COBP paradigm, its straightforward syntax, the ability to use verification and formal-method techniques to validate program correctness, and a program comprising small independent chunks all allow us to effectively generate behavioral programs using GP. To demonstrate our approach we evolve complete programs from scratch of a highly competent O player for the game of tic-tac-toe. The evolved programs are well structured, consisting of multiple, explainable modules that specify the different behavioral aspects of the program and are similar to our handcrafted program. To validate the correctness of our individuals, we utilize the mathematical characteristics of COBP to analyze program behavior under all possible execution paths. Our analysis of an evolved program proved that it plays as expected more than 99% of the times.

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Section: Representationmentioning

confidence: 99%

From Requirements to Source Code: Evolution of Behavioral Programs

2022

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“…This allows the run-time to optimize program execution at any given moment. BP principles can also be implemented in a variety of programming languages and domains with possible variations of idioms: Java (Harel et al, 2010)-where BPJ is a BP library for writing behavioral programs using Java and is considered the first BP library, Cþþ (Harel and Katz, 2014)-where BPC is a framework for writing behavioral programs in Cþþ, Erlang (Weiner et al, 2010), C (Shimony et al, 2011), and those are only a few examples.…”

Section: Behavioral Programming For Conversational Agentsmentioning

confidence: 99%

Designing rule-based conversational agents with behavioral programming: a study of human subjects

Rosenfeld

Haimovich

2022

EMJB

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PurposeIn this work, the authors propose to harness the advantages of behavioral programming as a new technique for designing rule-based conversational agents.Design/methodology/approachTo examine the study’s hypotheses, the authors perform a first-of-its-kind user study through which the authors examine how potential designers, both expert designers, computationally-oriented designers, and otherwise, leverage behavioral programming (BP) and dialog graphs for designing conversational agents (CAs). The authors also use two standard CA settings common in the literature: designing a CA representative for a user in an online dating service and a non-character player in a role-playing game (RPG).FindingsThe study’s results indicate that BP can be successfully utilized by computationally-oriented designers, with or without prior knowledge in CA design, and can facilitate the design of better CAs (i.e. more accurate and more robust). However, to capitalize on these potential advantages, designers may be required to devote more time to the design process and are likely to encounter higher temporal demand levels. These results suggest that BP, which was initially proposed and evaluated in the general context of software design, can constitute a valuable alternative to the classic rule-based CA design technique commonly practiced today.Research limitations/implicationsAn important limitation of this study is the relatively small participant pool. While the authors do plan to extend this study in the future, the current coronavirus disease 2019 (COVID-19) situation makes it ever more complex to conduct formal user studies of this kind. It is, however, important to note that despite the low number of participants, many of the results are found to be statistically significant.Practical implicationsThe authors plan to continue this line of work and conduct human studies for additional design techniques in other popular agent-based settings. Specifically, the authors seek to explore how people of different backgrounds should design agents for various tasks such as automated negotiation (e.g. how should a person design a representative agent to negotiate on her behalf?) and social choice (e.g. how should a person design a voting bot to represent her in online voting systems?).Originality/valuePeople are increasingly interacting with conversational agents in various settings and for a variety of reasons, as the market size of those agents keeps on growing every year. Through a first-of-its-kind human study (N = 41), consisting of both expert designers, computationally-oriented designers, and otherwise, the authors demonstrate a few key advantages and limitations of BP in the realm of conversational agents and propose its consideration as an alternative to the classic dialog graph technique.

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“…In addition to Java with the BPJ package 25 (discussed later in more detail) we have implemented them in the functional language Erlang 26,43 and Shimony et al 42 applied them in the PicOS environment using C. Implementations in visual contexts beyond the original Play-Engine include PlayGo 23 and SBT by Kugler et al 34 In behavioral programming, all one must do in order to start developing and experimenting with scenarios that will later constitute the final system, is to determine the common set of events that are relevant to these scenarios. While this still requires contemplation, it is often easier to answer the question "what are the events?"…”

Section: Basic Behavioral Idiomsmentioning

confidence: 99%

Behavioral programming

2012

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sPeLLing oUT The requirements for a software system under development is not an easy task, and translating captured requirements into correct operational software can be even harder. Many technologies (languages, modeling tools, programming paradigms) and methodologies (agile, test-driven, model-driven) were designed, among other things, to help address these challenges. One widely accepted practice is to formalize requirements in the form of use cases and scenarios. Our work extends this approach into using scenarios for actual programming. Specifically, we propose scenario-coding techniques and design approaches for constructing reactive systems 28 incrementally from their expected behaviors. The work on behavioral programming began with scenario-based programming, a way to create executable specifications of reactive systems, introduced through the language of live sequence charts (LSC) and its Play-Engine implementation. 11,21 The initial purpose was to enable testing and refining specifications and prototypes, and it was later extended toward building actual systems. To this end, the underlying behavioral principles have also been implemented in Java via the BPJ package 25 and in additional environments, 26,34,42,43 adding a programming point of view to that of requirement specification. To illustrate the naturalness of constructing systems by composing behaviors , consider how children may be taught, step-by-step, to play strategy games (See Gordon et al. 14). For example , in teaching the game of Tic-Tac-Toe, we first describe rules of the game, such as: EnforceTurns: To play, one player marks a square in a 3 by 3 grid with X, then the other player marks a square with O, then X plays again, and so on; SquareTaken: Once a square is marked, it cannot be marked again; DetectXWin/DetectOWin: When a player places three of his or her marks in a horizontal, vertical, or diagonal line, the player wins; Now we may already start playing. Later, the child may infer, or the teacher may suggest, some tactics: AddThirdO: After placing two Os in a line, the O player should try to mark the third square (to win the game); PreventThirdX: After the X player marks two squares in a line, the O player should try to mark the third square (to foil the attack); and DefaultOMoves: When other tactics are not applicable, player O should prefer the center square, then the cor-key insights Behavioral programming is a novel, language-independent paradigm for programming reactive systems, centered on natural and incremental specification of behavior, and implemented in the visual formalism of live sequence charts (LsC), and in the BPJ Java package. the approach allows coding applications as multi-modal scenarios, each corresponding to an individual requirement, specifying what can, must, or may not happen following certain sequences of events. to facilitate full behavioral modularity via the independent coding of separate facets of behavior, all scenarios run simultaneously, and all are consulted at every decision point during execution...

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On coordination tools in the PicOS tuples system

Cited by 9 publications

References 23 publications

From Requirements to Source Code: Evolution of Behavioral Programs

From Requirements to Source Code: Evolution of Behavioral Programs

Designing rule-based conversational agents with behavioral programming: a study of human subjects

Behavioral programming

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