The Evaluation of an Approach for Automatic Generated Documentation

Abid, Nahla J.; Dragan, Natalia; Collard, Michael L.; Maletic, Jonathan I.

doi:10.1109/icsme.2017.76

Cited by 6 publications

(4 citation statements)

References 29 publications

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“…In addition, their technique could be utilized in clustering systems with similar architecture/design. Moreno et al [110,113] and Abid et al [28]…”

Section: Utilizing Stereotypes For Automatic Documentationmentioning

confidence: 97%

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Automatically Documenting Software Artifacts

2016

2016 IEEE International Conference on Software Maintenance and Evolution (ICSME)

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Software artifacts, such as database schema and unit test cases, constantly change during evolution and maintenance of software systems. Co-evolution of code and DB schemas in Database-Centric Applications (DCAs) often leads to two types of challenging scenarios for developers, where (i) changes to the DB schema need to be incorporated in the source code, and (ii) maintenance of a DCAs code requires understanding of how the features are implemented by relying on DB operations and corresponding schema constraints. On the other hand, the number of unit test cases often grows as new functionality is introduced into the system, and maintaining these unit tests is important to reduce the introduction of regression bugs due to outdated unit tests. Therefore, one critical artifact that developers need to be able to maintain during evolution and maintenance of software systems is up-to-date and complete documentation.

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“…In addition, their technique could be utilized in clustering systems with similar architecture/design. Moreno et al [110,113] and Abid et al [28]…”

Section: Utilizing Stereotypes For Automatic Documentationmentioning

confidence: 97%

“…Linares-Vásquez et al[50,97] relied on commit stereotypes for generating commit messages. Abid et al[28] presented an approach that automatically generates NL documentation summaries for C++ methods based on stereotypes. Overall, none of the existing approaches (but UnitTestScribe) apply stereotype identification for generating unit test case documentation.…”

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confidence: 99%

Automatically Documenting Software Artifacts

2016

2016 IEEE International Conference on Software Maintenance and Evolution (ICSME)

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“…[80][81][82][83] Neural networks, deep learning, machine leaning and its related techniques to solve the synthesis problem. [84][85][86][87][88][89] Template-based technique to express the program space. [90][91][92][93][94][95][96][97][98][99][100][101][102] Paradigms of program synthesis.…”

Section: [49]mentioning

confidence: 99%

“…During the second level of systematic domain analysis on the search space, it was found that templates are widely used across almost all kinds of program synthesis approaches [85,[87][88][89]. Templates are considered to be a common technique that enables developers (users) to provide high-level insights about target programs to a synthesis framework using a generic programming or meta-programming feature (technique) available in some programming languages, such as C++, to create a template of a desired program.…”

Section: Search Space Of the Programmentioning

confidence: 99%

Cognification of Program Synthesis—A Systematic Feature-Oriented Analysis and Future Direction

Subahi

2020

Computers

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Program synthesis is defined as a software development step aims at achieving an automatic process of code generation that is satisfactory given high-level specifications. There are various program synthesis applications built on Machine Learning (ML) and Natural Language Processing (NLP) based approaches. Recently, there have been remarkable advancements in the Artificial Intelligent (AI) domain. The rise in advanced ML techniques has been remarkable. Deep Learning (DL), for instance, is considered an example of a currently attractive research field that has led to advances in the areas of ML and NLP. With this advancement, there is a need to gain greater benefits from these approaches to cognify synthesis processes for next-generation model-driven engineering (MDE) framework. In this work, a systematic domain analysis is conducted to explore the extent to the automatic generation of code can be enabled via the next generation of cognified MDE frameworks that support recent DL and NLP techniques. After identifying critical features that might be considered when distinguishing synthesis systems, it will be possible to introduce a conceptual design for the future involving program synthesis/MDE frameworks. By searching different research database sources, 182 articles related to program synthesis approaches and their applications were identified. After defining research questions, structuring the domain analysis, and applying inclusion and exclusion criteria on the classification scheme, 170 out of 182 articles were considered in a three-phase systematic analysis, guided by some research questions. The analysis is introduced as a key contribution. The results are documented using feature diagrams as a comprehensive feature model of program synthesis showing alternative techniques and architectures. The achieved outcomes serve as motivation for introducing a conceptual architectural design of the next generation of cognified MDE frameworks.

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A Code Summarization Approach for Object Oriented Programs

Mohsin

Hammad

2019

2019 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)

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The Evaluation of an Approach for Automatic Generated Documentation

Cited by 6 publications

References 29 publications

Automatically Documenting Software Artifacts

Automatically Documenting Software Artifacts

Cognification of Program Synthesis—A Systematic Feature-Oriented Analysis and Future Direction

A Code Summarization Approach for Object Oriented Programs

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