2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE)
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9781728122724

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Towards a Software Engineering Process for Developing Data-Driven Applications

2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE) ◽

10.1109/raise.2019.00014 ◽

2019 ◽

Cited By ~ 3

Author(s):

Marc Hesenius ◽

Nils Schwenzfeier ◽

Ole Meyer ◽

Wilhelm Koop ◽

Volker Gruhn

Keyword(s):

Software Engineering ◽

Data Driven ◽

Engineering Process ◽

Software Engineering Process

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RAISE 2019 Additional Reviewers

2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE) ◽

10.1109/raise.2019.00008 ◽

2019 ◽

Download Full-text

The Standard Coder: A Machine Learning Approach to Measuring the Effort Required to Produce Source Code Change

2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE) ◽

10.1109/raise.2019.00009 ◽

2019 ◽

Author(s):

Ian Wright ◽

Albert Ziegler

Keyword(s):

Machine Learning ◽

Source Code ◽

Learning Approach ◽

Code Change ◽

Machine Learning Approach

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2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE) ◽

10.1109/raise.2019.00004 ◽

2019 ◽

Download Full-text

Synthetic Test Data Generation Using Recurrent Neural Networks: A Position Paper

2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE) ◽

10.1109/raise.2019.00012 ◽

2019 ◽

Cited By ~ 1

Author(s):

Razieh Behjati ◽

Erik Arisholm ◽

Margrethe Bedregal ◽

Chao Tan

Keyword(s):

Neural Networks ◽

Test Data ◽

Recurrent Neural Networks ◽

Position Paper ◽

Test Data Generation ◽

Data Generation ◽

Synthetic Test

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ModelKB: Towards Automated Management of the Modeling Lifecycle in Deep Learning

2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE) ◽

10.1109/raise.2019.00013 ◽

2019 ◽

Author(s):

Gharib Gharibi ◽

Vijay Walunj ◽

Sirisha Rella ◽

Yugyung Lee

Keyword(s):

Deep Learning ◽

Automated Management

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Author Index

2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE) ◽

10.1109/raise.2019.00017 ◽

2019 ◽

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Towards Concept Based Software Engineering for Intelligent Agents

2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE) ◽

10.1109/raise.2019.00015 ◽

2019 ◽

Author(s):

Meyer Ole ◽

Gruhn Volker

Keyword(s):

Software Engineering ◽

Intelligent Agents

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Message from the RAISE 2019 Workshop Chairs

2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE) ◽

10.1109/raise.2019.00005 ◽

2019 ◽

Download Full-text

Copyright Page

2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE) ◽

10.1109/raise.2019.00003 ◽

2019 ◽

Download Full-text

2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE)
Latest Publications

TOTAL DOCUMENTS

H-INDEX

Published By IEEE

Towards a Software Engineering Process for Developing Data-Driven Applications

RAISE 2019 Additional Reviewers

The Standard Coder: A Machine Learning Approach to Measuring the Effort Required to Produce Source Code Change

Table of Contents

Synthetic Test Data Generation Using Recurrent Neural Networks: A Position Paper

ModelKB: Towards Automated Management of the Modeling Lifecycle in Deep Learning

Author Index

Towards Concept Based Software Engineering for Intelligent Agents

Message from the RAISE 2019 Workshop Chairs

Copyright Page

Export Citation Format

2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE)Latest Publications

TOTAL DOCUMENTS

H-INDEX

Published By IEEE

Towards a Software Engineering Process for Developing Data-Driven Applications

RAISE 2019 Additional Reviewers

The Standard Coder: A Machine Learning Approach to Measuring the Effort Required to Produce Source Code Change

Table of Contents

Synthetic Test Data Generation Using Recurrent Neural Networks: A Position Paper

ModelKB: Towards Automated Management of the Modeling Lifecycle in Deep Learning

Author Index

Towards Concept Based Software Engineering for Intelligent Agents

Message from the RAISE 2019 Workshop Chairs

Copyright Page

2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE)
Latest Publications