Implementing Partial Persistence in Object-Oriented Languages

Pluquet, Frédéric; Langerman, Stefan; Marot, Antoine; Wuyts, Roel

doi:10.1137/1.9781611972887.4

Cited by 7 publications

(5 citation statements)

References 41 publications

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“…In one project, because of existing interfaces, there were certain requirement specifications that had to be met. This portion of the project is better handled by a traditional RQ3: When scientists produce high-level requirements they rely on developers to prioritize them [29] DI2: Scientific software developers see redesign as a waste of time that risks breaking the "science" of a program [29] DI3: Object Oriented Design helps produce useful software [32][33][34] development method. In order to address the discrepancy, it was effective to utilize a method from Boehm and Turner to blend agile and traditional methodologies in order to minimize the risk in the development process.…”

Section: The Developer Forms a Basic Idea Of What Is Needed And Beginsmentioning

confidence: 99%

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Claims about the use of software engineering practices in science: A systematic literature review

Heaton

Carver

2015

Information and Software Technology

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a b s t r a c tContext: Scientists have become increasingly reliant on software in order to perform research that is too timeintensive, expensive, or dangerous to perform physically. Because the results produced by the software drive important decisions, the software must be correct and developed efficiently. Various software engineering practices have been shown to increase correctness and efficiency in the development of traditional software. It is unclear whether these observations will hold in a scientific context.Objective: This paper evaluates claims from software engineers and scientific software developers about 12 different software engineering practices and their use in developing scientific software. Method:We performed a systematic literature review examining claims about how scientists develop software. Of the 189 papers originally identified, 43 are included in the literature review. These 43 papers contain 33 different claims about 12 software engineering practices. Results:The majority of the claims indicated that software engineering practices are useful for scientific software development. Every claim was supported by evidence (i.e. personal experience, interview/survey, or case study) with slightly over half supported by multiple forms of evidence. For those claims supported by only one type of evidence, interviews/surveys were the most common. The claims that received the most support were: "The effectiveness of the testing practices currently used by scientific software developers is limited" and "Version control software is necessary for research groups with more than one developer." Additionally, many scientific software developers have unconsciously adopted an agile-like development methodology.Conclusion: Use of software engineering practices could increase the correctness of scientific software and the efficiency of its development. While there is still potential for increased use of these practices, scientific software developers have begun to embrace software engineering practices to improve their software. Additionally, software engineering practices still need to be tailored to better fit the needs of scientific software development.

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Section: The Developer Forms a Basic Idea Of What Is Needed And Beginsmentioning

confidence: 99%

“…The other three studies [32][33][34] dealt with projects that sought to provide modular functionality. Each of the authors found that the use of a programming language that allowed them to utilize an Object-Oriented design paradigm was necessary for their project to be successful.…”

Section: Design Issuesmentioning

confidence: 99%

Claims about the use of software engineering practices in science: A systematic literature review

Heaton

Carver

2015

Information and Software Technology

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“…Practically, researchers have developed generic tools, implemented in various object-oriented programming languages, to convert any data structure into a partially or fully persistent one by simply adding one keyword to its source code [13]. In other words, persistence can be obtained easily from a developer's point of view, which further motivates the development of algorithms making use of persistent structures.…”

Section: Applications Of Persistencementioning

confidence: 99%

“…If the data structure is made persistent, one can then retrieve all the information that has been swept through, by going back to previous versions. For instance, this can be used to solve optimally the segment intersection problem [1].Practically, researchers have developed generic tools, implemented in various object-oriented programming languages, to convert any data structure into a partially or fully persistent one by simply adding one keyword to its source code [13]. In other words, persistence can be obtained easily from a developer's point of view, which further motivates the development of algorithms making use of persistent structures.Finally, confluent persistence is useful in many contexts where one wants to backup all versions of some information.…”

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confidence: 99%

Confluent Persistence Revisited

Collette

Iacono

Langerman

2012

Proceedings of the Twenty-Third Annual ACM-SIAM Symposium on Discrete Algorithms

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It is shown how to enhance any data structure in the pointer model to make it confluently persistent, with efficient query and update times and limited space overhead. Updates are performed in O(log n) amortized time, and following a pointer takes O(log c log n) time where c is the in-degree of a node in the data structure. In particular, this proves that confluent persistence can be achieved at a logarithmic cost in the bounded in-degree model used widely in previous work. This is a O(n/ log n)-factor improvement over the previous known transform to make a data structure confluently persistent. IntroductionPersistence. Abstractly, a data structure is some collection of data that supports various operations to be performed upon it. These operations can be partitioned into two groups: query operations, that do not modify the structure, and updates that do modify the structure. Classically, operations are performed on the current state of the structure, and in the case of an update, the current state is changed, and the past state is lost.Persistence is the concept, first formally studied in [7], of allowing the efficient execution of operations not just on the current state, but on past states as well. The past states are referred to as versions of the structure. There are three forms of persistence, which we discuss in increasing order of power and complexity.The simplest kind, partial persistence, is where one can execute query operations on any previous version of the structure, but where updates are only allowed on the current version. This implies that the versions form a list (or timeline), each version being derived from the latest (or most recent) version in the list.In full persistence, update and query operations may be performed on any version of the data structure that ever existed. In the case of an update on a past version, a new version is created, derived from that past version. While in the classic sense, and in partial persistence, time takes on its normal linear structure, in full persistence, time as viewed by the data structure no longer has a Applications of persistence. Persistence is a very useful tool, with applications ranging from algorithm design to code debugging. We list some of these here.From a theoretical point of view, persistence has played a major role in the development of efficient algorithms. For instance, the best algorithms for planar point location [14] and rayshooting [10] use persistence.A widely-used technique in computational geometry consists in performing a sweep with a vertical line through a data set (set of points, set of segments, line arrangement, map, data structure...), and storing in a data structure the set of items intersected by the line. As we sweep, we update the data structure to accurately represent the objects intersected by the sweep line. If the data structure is made persistent, one can then retrieve all the information that has been swept through, by going back to previous versions. For instance, this can be used to solve optimally the segment int...

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“…Compared to an array, whose size is fixed (at compile time or at run-time), the size of a vector can vary and memory management is handled automatically. In the computing literature, this data structure has been discussed under many names, including dynamic array [16,33], dynamic table [11], extendible array [32], extensible array [8], flexible array (term used in Algol 68), growable array [31], resizable array [10], and variable-length array [6,37]. As to the vector class in C++, its full specification together with all associated operations can be found in the C++ standard [9,19].…”

Section: Standard-compliant Vector and Relevant Extensionsmentioning

confidence: 99%

Adaptable component frameworks

Katajainen

Simonsen

2009

Proceedings of the 2009 ACM SIGPLAN Workshop on Generic Programming

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The CPH STL is a special edition of the STL, the containers and algorithms part of the C++ standard library. The specification of the generic components of the STL is given in the C++ standard. Any implementation of the STL, e.g. the one that ships with your standard-compliant C++ compiler, should provide at least one realization for each container that has the specified characteristics with respect to performance and safety. In the CPH STL project, our goal is to provide several alternative realizations for each STL container. For example, for associative containers we can provide almost any kind of balanced search tree. Also, we do provide safe and compact versions of each container. To ease the maintenance of this large collection of implementations, we have developed component frameworks for the STL containers. In this paper, we describe the design and implementation of a component framework for vector, which is undoubtedly the most used container of the C++ standard library. In particular, we specify the details of a vector implementation that is safe with respect to referential integrity and strong exception safety. Additionally, we report the experiences and lessons learnt from the development of component frameworks which we hope to be of benefit to persons engaged in the design and implementation of generic software libraries.

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Implementing Partial Persistence in Object-Oriented Languages

Cited by 7 publications

References 41 publications

Claims about the use of software engineering practices in science: A systematic literature review

Claims about the use of software engineering practices in science: A systematic literature review

Confluent Persistence Revisited

Adaptable component frameworks

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