A dynamic memory of software designs

1994 ◽  
Vol 8 (2) ◽  
pp. 163-176 ◽  
Author(s):  
Scott Henderson ◽  
Sidney C. Bailin
Keyword(s):  
Artificial Intelligence ◽  
Software Engineering ◽  
Software Reuse ◽  
Concept Formation ◽  
Experimental System ◽  
Dynamic Memory ◽  
Software Artifacts ◽  
Retrieval Efficiency ◽  
Conceptual Hierarchy ◽  
Support Software

AbstractThis paper describes an application of artificial intelligence to support software reuse. We begin by discussing the characteristics of software engineering that establish dynamic reorganization as a requirement for a repository of software artifacts. We then present an experimental system that uses incremental concept formation as the basis for dynamic reorganization, and the conceptual hierarchy that was generated by the system for a set of 67 artifacts. The hierarchy is compared to a hierarchy produced manually by independent investigators, and the automatic hierarchy is evaluated in terms of retrieval efficiency and retrieval reliability. The paper ends with a discussion of three projects that share similar objectives with our work.

APPLYING CONCEPT FORMATION METHODS TO SOFTWARE REUSE

1995 ◽  
Vol 05 (01) ◽  
pp. 119-142 ◽  
Author(s):  
ROBERT GODIN ◽  
GUY MINEAU ◽  
ROKIA MISSAOUI ◽  
MARC ST-GERMAIN ◽  
NAJIB FARAJ
Keyword(s):  
Software Engineering ◽  
Software Reuse ◽  
Concept Formation ◽  
Software Systems ◽  
Research Project ◽  
Engineering Research ◽  
Concept Hierarchy ◽  
Software Engineering Research

This paper describes an approach to software reuse that involves generating and retrieving abstractions from existing software systems using concept formation methods. The potential of the approach is illustrated through two important activities of the reuse process. First, the concept hierarchy generated by the concept formation methods is used for organizing and retrieving the artifacts inside a repository. Second, the generated concepts are used in identifying new abstractions that may be converted into new, more generic artifacts with better reuse potential. These experiments are part of a major software engineering research project involving many business and academic partners.

Data Mining Techniques for Software Quality Prediction

2014 ◽  
pp. 401-428
Author(s):  
Bharavi Mishra ◽  
K. K. Shukla
Keyword(s):  
Data Mining ◽  
Project Management ◽  
Software Engineering ◽  
Software Development ◽  
Vital Role ◽  
Software Systems ◽  
Software Artifacts ◽  
Formidable Challenge ◽  
Management Processes ◽  
Support Software

In the present time, software plays a vital role in business, governance, and society in general, so a continuous improvement of software productivity and quality such as reliability, robustness, etc. is an important goal of software engineering. During software development, a large amount of data is produced, such as software attribute repositories and program execution trace, which may help in future development and project management activities. Effective software development needs quantification, measurement, and modelling of previous software artefacts. The development of large and complex software systems is a formidable challenge which requires some additional activities to support software development and project management processes. In this scenario, data mining can provide a helpful hand in the software development process. This chapter discusses the application of data mining in software engineering and includes static and dynamic defect detection, clone detection, maintenance, etc. It provides a way to understand the software artifacts and processes to assist in software engineering tasks.

The Aspects of Artificial Intelligence in Software Engineering

2020 ◽  
Vol 17 (9) ◽  
pp. 4635-4642
Author(s):  
Mudita ◽  
Deepali Gupta
Keyword(s):  
Artificial Intelligence ◽  
Software Engineering ◽  
Software Development ◽  
Emerging Technologies ◽  
Software Systems ◽  
Application Development ◽  
Desktop Application ◽  
Development Life Cycle ◽  
Support Software

Software Engineering is the fundamental methodology used in the process of developing the software. Software Development Life Cycle (SDLC) is the backbone of software engineering. SDLC is emerging in several forms to support software development at different phases. SDLC plays as a role of guide for engineers that are involved from traditional desktop application development to much trending development. The new emerging technologies accelerate the process of software engineering, resulting in saving time and resources and enhance the quality of software systems. This paper focuses on technologies used to accelerate the process of software engineering in solving problems associated with its phases. The first section of this paper contains an introduction to Software Engineering (SE) and Artificial Intelligence (AI). The next section describes the aspects of emerging technologies in software engineering. After this, the role of AI in SE is discussed followed by a conclusion in the last section.

Data Mining Techniques for Software Quality Prediction

2013 ◽  
pp. 112-139
Author(s):  
Bharavi Mishra ◽  
K. K. Shukla
Keyword(s):  
Data Mining ◽  
Project Management ◽  
Software Engineering ◽  
Software Development ◽  
Vital Role ◽  
Software Systems ◽  
Software Artifacts ◽  
Formidable Challenge ◽  
Management Processes ◽  
Support Software

In the present time, software plays a vital role in business, governance, and society in general, so a continuous improvement of software productivity and quality such as reliability, robustness, etc. is an important goal of software engineering. During software development, a large amount of data is produced, such as software attribute repositories and program execution trace, which may help in future development and project management activities. Effective software development needs quantification, measurement, and modelling of previous software artefacts. The development of large and complex software systems is a formidable challenge which requires some additional activities to support software development and project management processes. In this scenario, data mining can provide a helpful hand in the software development process. This chapter discusses the application of data mining in software engineering and includes static and dynamic defect detection, clone detection, maintenance, etc. It provides a way to understand the software artifacts and processes to assist in software engineering tasks.

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