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A Data-to-Product Multimodal Conceptual Framework to Achieve Automated Software Evolution for Context-rich Intelligent Applications

Songhui Yue

TL;DR

A Selective Sequential Scope Model (3 S) model is developed based on the conceptual framework, and it can be used to categorize existing and future research when it covers different SE phases and multimodal learning tasks.

Abstract

While AI is extensively transforming Software Engineering (SE) fields, SE is still in need of a framework to overall consider all phases to facilitate Automated Software Evolution (ASEv), particularly for intelligent applications that are context-rich, instead of conquering each division independently. Its complexity comes from the intricacy of the intelligent applications, the heterogeneity of the data sources, and the constant changes in the context. This study proposes a conceptual framework for achieving automated software evolution, emphasizing the importance of multimodality learning. A Selective Sequential Scope Model (3S) model is developed based on the conceptual framework, and it can be used to categorize existing and future research when it covers different SE phases and multimodal learning tasks. This research is a preliminary step toward the blueprint of a higher-level ASEv. The proposed conceptual framework can act as a practical guideline for practitioners to prepare themselves for diving into this area. Although the study is about intelligent applications, the framework and analysis methods may be adapted for other types of software as AI brings more intelligence into their life cycles.

A Data-to-Product Multimodal Conceptual Framework to Achieve Automated Software Evolution for Context-rich Intelligent Applications

TL;DR

A Selective Sequential Scope Model (3 S) model is developed based on the conceptual framework, and it can be used to categorize existing and future research when it covers different SE phases and multimodal learning tasks.

Abstract

While AI is extensively transforming Software Engineering (SE) fields, SE is still in need of a framework to overall consider all phases to facilitate Automated Software Evolution (ASEv), particularly for intelligent applications that are context-rich, instead of conquering each division independently. Its complexity comes from the intricacy of the intelligent applications, the heterogeneity of the data sources, and the constant changes in the context. This study proposes a conceptual framework for achieving automated software evolution, emphasizing the importance of multimodality learning. A Selective Sequential Scope Model (3S) model is developed based on the conceptual framework, and it can be used to categorize existing and future research when it covers different SE phases and multimodal learning tasks. This research is a preliminary step toward the blueprint of a higher-level ASEv. The proposed conceptual framework can act as a practical guideline for practitioners to prepare themselves for diving into this area. Although the study is about intelligent applications, the framework and analysis methods may be adapted for other types of software as AI brings more intelligence into their life cycles.
Paper Structure (33 sections, 5 figures)

This paper contains 33 sections, 5 figures.

Table of Contents

  1. Introduction
  2. Backgrounds and Related Work
  3. Automated Software Evolution
  4. Data-to-Product View
  5. White-Box, Black-Box, and Gray-Box Machine Learning Models
  6. Context Dynamism
  7. Multimodality
  8. a Bigger Map and the Key Dimension/Feature Analysis
  9. Context Sources and Data Modalities
  10. Multimodal Learning
  11. Key Features and Products
  12. 3-S Model
  13. Tasks
  14. Software Engineering (SE) Phases
  15. Scope
  16. ...and 18 more sections

Figures (5)

  • Figure 1: Components of the Intelligent System Evolution Research
  • Figure 2: an auto / semi-auto software engineering decision-making process
  • Figure 3: the Architectures of Multimodal Learning through Late Fusion within Software Engineering
  • Figure 4: a Data-to-Product Multimodal Conceptual Framework for ASEv
  • Figure 5: a Selective Sequential Scope Model (SSSM or 3S Model) for Smart (Intelligent) Software Engineering based on the software development life cycle and Multimodal Tasks