On the knowledge required to understand a program

Clayton, Richard J.; Rugaber, Spencer; Wills, Linda M.

doi:10.1109/wcre.1998.723177

Cited by 17 publications

(12 citation statements)

References 12 publications

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“…According to Clayton there is no real agreement on what it is about a program that needs to be understood (Clayton, 1998). This is not surprising as program comprehension is not an end goal, but rather a necessary step in achieving some other objective.…”

Section: Effects Of Ask Variability In Program Comprehensionmentioning

confidence: 99%

“…He advocates that it is as important to document the problem domain as it is to document programming concepts. Also stress the importance of explicitly documenting domain knowledge to improve comprehension (Clayton et al, 1998). Brooks suggests that different styles of languages require different styles of documentation.…”

Section: Cognitive Models and Tool Implicationsmentioning

confidence: 99%

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Theories, tools and research methods in program comprehension: past, present and future

Storey

2006

Software Qual J

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Program comprehension research can be characterized by both the theories that provide rich explanations about how programmers understand software, as well as the tools that are used to assist in comprehension tasks. In this paper, I review some of the key cognitive theories of program comprehension that have emerged over the past thirty years. Using these theories as a canvas, I then explore how tools that are commonly used today have evolved to support program comprehension. Specifically, I discuss how the theories and tools are related and reflect on the research methods that were used to construct the theories and evaluate the tools. The reviewed theories and tools are distinguished according to human characteristics, program characteristics, and the context for the various comprehension tasks. Finally, I predict how these characteristics will change in the future and speculate on how a number of important research directions could lead to improvements in program comprehension tool development and research methods.

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Section: Effects Of Ask Variability In Program Comprehensionmentioning

confidence: 99%

Section: Cognitive Models and Tool Implicationsmentioning

confidence: 99%

Theories, tools and research methods in program comprehension: past, present and future

Storey

2006

Software Qual J

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“…Bien que ce soit extrêmement important aussi, il est moins connu que près de deux tiers des coûts de la maintenance sont dédiés à la compréhension du code source [Müller et al, 1993]. Ceci n'est pas surprenant puisque pour être capables de réaliser une activité de maintenance quelconque, il est nécessaire de comprendre comment fonctionne le code source et pourquoi il fonctionne de telle façon [Clayton et al, 1998]; cela au moins pour le code qui doit être modifié pour la tâche de maintenance.…”

Section: Résuméunclassified

“…While extremely important as well, it is less commonly known that almost two-thirds of the maintenance cost are devoted to software comprehension or understanding [Müller et al, 1993]. This is not surprising given that before being able to perform any kind of maintenance activity, at least the part of the program that needs to be modified has to be understood in terms of how it works and why it works like that [Clayton et al, 1998]. …”

Section: Introductionmentioning

confidence: 99%

Program understanding using ontologies and dynamic analysis

Belmonte¹,

Dugerdil

2018

Proceedings of the 33rd Annual ACM Symposium on Applied Computing

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“…There's highly valuable work on the program comprehension processes [15] and the knowledge required for understanding programs [3,6]. To a large extent this knowledge is encoded in programs only in the names used for its entities.…”

Section: Related Workmentioning

confidence: 99%

Programs are Knowledge Bases

Ratiu

Deissenboeck

14th IEEE International Conference on Program Comprehension (ICPC'06)

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Gaining an overview of the concepts represented in large programs is very demanding as multiple dimensions of knowledge appear at different abstraction levels throughout the source code. To reduce the overall comprehension effort it is therefore desirable to make the knowledge once gained explicit and shareable. We tackle this problem by establishing a mapping between source code and conceptualizations shared as ontologies. To achieve this we regard programs themselves as knowledge bases built on the programs' identifiers and their relations implied by the programming language. Making these mappings explicit allows sharing knowledge about the concepts represented in programs. We exemplify our approach on Java programming language and the WordNet ontology and we report on our experience with analyzing an open source system. Understanding Large ProgramsProgram comprehension accounts for about 50% of the expenses spent during software maintenance [9] which itself consumes the bulk of the lifecyle costs of successful, long-lived software-systems [13].Most programmers would agree that understanding the high-level coherences of a program (as opposed to understanding localized code fragments like a single method) is one of the most challenging tasks in program comprehension. This is can be best exemplified by a (fictional) experiment: compare understanding an unknown program without any prior information to understanding the program after one of the developers gave you a 10 minute introduction on the program. Certainly the latter task is considerably easier than the former. This raises the question about the nature of the knowledge conveyed to you in the short introduction. As previous research on program comprehension suggests, this is mainly knowledge about the basic concepts represented in the program and their interrelations. In this context concepts don't necessarily have to be concepts of the application domain, e. g. an account number, they can as well be technical concepts like a stack or sorting algorithm or a part thereof. Unfortunately the conceptual information contained in the source code is often of implicit nature as these concepts are scattered over various locations and different abstraction levels within the source code. Thus the task of locating known concepts in the program as well as extracting concepts from the program are equally demanding.We present a new approach for extracting concepts from code by mapping the identifiers and the relations between them to ontologies. As a result, we explicitly link the sources with the semantics contained in ontologies. We demonstrate our approach using on the one hand the relations within Java programs generated by the type and the module systems and on the other hand the WordNet ontology and we exemplify our preliminary experiences with a medium sized open-source Java system. Related WorkThere's highly valuable work on the program comprehension processes [15] and the knowledge required for understanding programs [3,6]. To a large extent this knowledge is enco...

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On the knowledge required to understand a program

Cited by 17 publications

References 12 publications

Theories, tools and research methods in program comprehension: past, present and future

Theories, tools and research methods in program comprehension: past, present and future

Program understanding using ontologies and dynamic analysis

Programs are Knowledge Bases

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