Combining Top-Down and Bottom-Up Techniques in Program Derivation

Chaudhari, Dipak; Damani, Om P.

doi:10.1007/978-3-319-27436-2_15

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…Ref. [11] divided the post-assertion into multiple specifications based on the weakest predicate method and then formed a loop invariant for derivation [12] . Refs.…”

Section: Related Workmentioning

confidence: 99%

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Program Construction Method for Sequential Statistics Class Algorithm Based on Bidirectional Scanning Induction

ZUO,

WANG,

LIANG

et al. 2023

Wuhan Univ. J. Nat. Sci.

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The program construction process is based on rigorous mathematical reasoning, which leads to a fully correct algorithmic program via step-by-step refinement of the program specifications. The existing program construction methods' refinement process is partly based on individual subjective speculation and analysis, which lacks a precise guidance method. Meanwhile, efficiency factors have usually been ignored in the construction process, and most of the constructed abstract programs cannot be run directly by machines. In order to solve these problems, a novel program construction method for the sequence statistical class algorithms based on bidirectional scan induction is proposed in this paper. The method takes into account the efficiency factor and thus improves the Morgan's refinement calculus. Furthermore, this paper validates the method's feasibility using an efficiency-sensitive sequential statistics class algorithm as a program construction example. The method proposed in this paper realizes the correctness construction process from program specifications to efficient executable programs.

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“…Ref. [11] divided the post-assertion into multiple specifications based on the weakest predicate method and then formed a loop invariant for derivation [12] . Refs.…”

Section: Related Workmentioning

confidence: 99%

“…Refs. [11,12] are based on the decomposition of post-assertions. However, in the face of more complex program specifications, finding sub-specifications becomes difficult, and the derivation process becomes more complex as the number of sub-specifications increases.…”

Section: Related Workmentioning

confidence: 99%

Program Construction Method for Sequential Statistics Class Algorithm Based on Bidirectional Scanning Induction

ZUO,

WANG,

LIANG

et al. 2023

Wuhan Univ. J. Nat. Sci.

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Assumption propagation through annotated programs

Chaudhari

Damani

2017

Form. Asp. Comput.

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In the correct-by-construction programming methodology, programs are incrementally derived from their formal specifications, by repeatedly applying transformations to partially derived programs. At an intermediate stage in a derivation, users may have to make certain assumptions to proceed further. To ensure that the assumptions hold true at that point in the program, certain other assumptions may need to be introduced upstream as loop invariants or preconditions. Typically these other assumptions are made in an ad hoc fashion and may result in unnecessary rework, or worse, complete exclusion of some of the alternative solutions. In this work, we present rules for propagating assumptions through annotated programs. We show how these rules can be integrated in a top-down derivation methodology to provide a systematic approach for propagating the assumptions, materializing them with executable statements at a place different from the place of introduction, and strengthening of loop invariants with minimal additional proof efforts.

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Combining Top-Down and Bottom-Up Techniques in Program Derivation

Cited by 2 publications

References 9 publications

Program Construction Method for Sequential Statistics Class Algorithm Based on Bidirectional Scanning Induction

Program Construction Method for Sequential Statistics Class Algorithm Based on Bidirectional Scanning Induction

Assumption propagation through annotated programs

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