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11/02/2022
Synthesizing Programs with Continuous Optimization
Automatic software generation based on some specification is known as pr...
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04/14/2022
MP-CodeCheck: Evolving Logical Expression Code Anomaly Learning with Iterative Self-Supervision
Machine programming (MP) is concerned with automating software developme...
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12/06/2021
Simulation Intelligence: Towards a New Generation of Scientific Methods
The original "Seven Motifs" set forth a roadmap of essential methods for...
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04/26/2021
Toward Code Generation: A Survey and Lessons from Semantic Parsing
With the growth of natural language processing techniques and demand for...
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11/06/2020
ControlFlag: A Self-supervised Idiosyncratic Pattern Detection System for Software Control Structures
Software debugging has been shown to utilize upwards of 50 time. Machine...
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10/12/2020
Class-Weighted Evaluation Metrics for Imbalanced Data Classification
Class distribution skews in imbalanced datasets may lead to models with ...
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06/05/2020
MISIM: An End-to-End Neural Code Similarity System
Code similarity systems are integral to a range of applications from cod...
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04/28/2020
Learned Garbage Collection
Several programming languages use garbage collectors (GCs) to automatica...
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04/02/2020
Software Language Comprehension using a Program-Derived Semantic Graph
Traditional code transformation structures, such as an abstract syntax t...
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03/24/2020
Context-Aware Parse Trees
The simplified parse tree (SPT) presented in Aroma, a state-of-the-art c...
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10/31/2019
An Abstraction-Based Framework for Neural Network Verification
Deep neural networks are increasingly being used as controllers for safe...
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08/22/2019
Learning Fitness Functions for Genetic Algorithms
A genetic algorithm (GA) attempts to solve a problem using a pool of pot...
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08/22/2019
NetSyn: Neural Evolutionary Technique to Synthesize Programs
Program synthesis using inputs and outputs is a fundamental problem in c...
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03/29/2019
SysML: The New Frontier of Machine Learning Systems
Machine learning (ML) techniques are enjoying rapidly increasing adoptio...
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03/20/2018
The Three Pillars of Machine Programming
In this position paper, we describe our vision of the future of machine ...
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03/20/2018
The Three Pillars of Machine-Based Programming
In this position paper, we describe our vision of the future of machine-...
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03/08/2018
A New Model for Evaluating Range-Based Anomaly Detection Algorithms
Classical anomaly detection (AD) is principally concerned with point-bas...
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01/18/2018
Toward Scalable Verification for Safety-Critical Deep Networks
The increasing use of deep neural networks for safety-critical applicati...
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01/09/2018
Precision and Recall for Range-Based Anomaly Detection
Classical anomaly detection is principally concerned with point-based an...
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01/09/2018
Greenhouse: A Zero-Positive Machine Learning System for Time-Series Anomaly Detection
This short paper describes our ongoing research on Greenhouse - a zero-p...
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01/09/2018
Paranom: A Parallel Anomaly Dataset Generator
In this paper, we present Paranom, a parallel anomaly dataset generator....
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09/21/2017
AutoPerf: A Generalized Zero-Positive Learning System to Detect Software Performance Anomalies
In this paper, we present AutoPerf, a generalized software performance a...
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09/17/2017