Assuring good style for object-oriented programs

Lieberherr, Karl; Holland, Ian M.

doi:10.1109/52.35588

Cited by 166 publications

(74 citation statements)

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“…The framework is naturally compatible with objectoriented simulator development, in which the "least knowledge principle" [19], i.e., modules should hide details from each other, is obeyed. In our framework, if a module that computes a certain kind of quantity is initialized, the sparse pattern of the output gradient vector and the cached target column numbers depend only on the sparse pattern of input gradient vectors and the mathematical model contained in the module and do not include the details of how these input patterns are produced.…”

Section: The Feasibility Of the Backward Ad Frameworkmentioning

confidence: 97%

A backward automatic differentiation framework for reservoir simulation

Zhang

2014

Comput Geosci

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In numerical reservoir simulations, Newton's method is a concise, robust and, perhaps the most commonly used method to solve nonlinear partial differential equations (PDEs). However, as reservoir simulators incorporate more and more physical and chemical phenomena, writing codes that compute gradients for reservoir simulation equations can become quite complicated. This paper presents an automatic differentiation (AD) framework that is specially designed for simplifying coding and simultaneously maintaining computational efficiency. First a parse tree for a mathematical expression is built and evaluated with the backward mode AD, and then the derivatives with respect to the expression's arguments are transformed to derivatives with respect to the PDE's independent variables. The first stage can be realized either by runtime polymorphism to gain higher flexibility or by compile-time polymorphism to gain faster execution speed; the second stage is realized by linear combinations of sparse vectors, which can be accelerated by recording the target column indices. The AD framework has been implemented in an in-house reservoir simulator. Individual tests on some complex mathematical expressions were carried out to compare the speed of the manual implementation, the runtime polymorphic implementation and the compile-time polymorphic implementation of the differentiation. Then the performance of the three was analyzed in complete simulations. These cases

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Section: The Feasibility Of the Backward Ad Frameworkmentioning

confidence: 97%

A backward automatic differentiation framework for reservoir simulation

Zhang

2014

Comput Geosci

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“…Highly coupled systems have long been recognized as hard to comprehend (Lieberherr and Holland 1989;Page-Jones 1980) because their modules cannot be considered in separation from each other.…”

Section: Motivationsmentioning

confidence: 99%

An empirical study on the impact of AspectJ on software evolvability

Przybyłek

2017

Empir Software Eng

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Since its inception in 1996, aspect-oriented programming (AOP) has been believed to reduce the effort required to maintain software systems by replacing cross-cutting code with aspects. However, little convincing empirical evidence exists to support this claim, while several studies suggest that AOP brings new obstacles to maintainability. This paper discusses two controlled experiments conducted to evaluate the impact of AspectJ (the most mature and popular aspect-oriented programming language) versus Java on software evolvability. We consider evolvability as the ease with which a software system can be updated to fulfill new requirements. Since a minor language was compared to the mainstream, the experiments were designed so as to anticipate that the participants were much more experienced in one of the treatments. The first experiment was performed on 35 student subjects who were asked to comprehend either Java or AspectJ implementation of the same system, and perform the corresponding comprehension tasks. Participants of both groups achieved a high rate of correct answers without a statistically significant difference between the groups. Nevertheless, the Java group significantly outperformed the AspectJ group with respect to the average completion time. In the second experiment, 24 student subjects were asked to implement (in a noninvasive way) two extension scenarios to the system that they had already known. Each subject evolved either the Java version using Java or the AspectJ version using AspectJ. We found out that a typical AspectJ programmer needs significantly fewer atomic changes to implement the change scenarios than a typical Java programmer, but we did not observe a significant difference in completion time. The overall result indicates that AspectJ has a different effect on two sub-characteristics of the evolvability: understandability and changeability. While AspectJ decreases the former, it improves one aspect of the latter.Empir Software Eng

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“…Examples include: the open/closed principle [34,32], the Liskov substitution principle [28,31], the acyclic dependencies principle [34,30], Favour composition over inheritance [26], the Law of Demeter [27], You ain't gonna need it (YAGNI) 2 and Tell, don't ask [3]. This lore is supplemented by design patterns and idioms, which provide prototypical solutions to common problems.…”

Section: Design Heuristicsmentioning

confidence: 99%