Algodynamics: Algorithms as systems

Choppella, Venkatesh; Kasturi, Viswanath; Kumar, Mrityunjay

doi:10.1109/fie49875.2021.9637441

Cited by 9 publications

(1 citation statement)

References 36 publications

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“…These modeling approaches derive from systems theory and Mealy [17] and Moore [18] machines (finite-state machines for discrete systems). Choppella et al [19] use transition systems to model interactive algorithms. We want to similarly extend these models and use transition systems as a modeling language for the novice engineers.…”

Section: Related Workmentioning

confidence: 99%

A modeling language for novice engineers to design well at SaaS product companies

Kumar

Choppella

2023

16th Innovations in Software Engineering Conference

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One of the key challenges for a novice engineer in a product company is to comprehend the product sufficiently and quickly. It can take anywhere from six months to several years for them to attain mastery but they need to start delivering results much before. SaaS (Software-as-a-Service) products have sophisticated system architecture which adds to the time and effort of understanding them. On the other hand, time available to new hires for product understanding continues to be short and getting shorter, given the pressure to deliver more in less time.Constructivist theory views learning as a personal process in which the learner constructs new knowledge for themselves. Building and refining a mental model is the key way in which they learn, similar to how the brain operates. This paper presents an approach to improve system comprehension process by using a system model that a) acts as a transitional object to aid and refine the mental model of the learner, and b) captures the current understanding of the dynamics of the software system in a way that can be reasoned with and simulated.We have adapted discrete systems modeling techniques and used a transition system as a lightweight modeling language. Such a model can be used by novice engineers during their product ramp-up phase to build a model of the software system that captures their knowledge of the system and aid their mental model. The paper also presents a learning approach in which the learners create and refine these models iteratively using the available and newly uncovered knowledge about the software system. We hypothesize that by leveraging this modeling language and approach, novice engineers can reduce the time it takes them to achieve desired proficiency level of system comprehension.This paper presents early ideas on this language and approach. Future work will include designing a course to teach this language and approach to final-year students and novice engineers so that this hypothesis can be tested.

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Section: Related Workmentioning

confidence: 99%