ACM Transactions on Software Engineering and Methodology
ACM Transactions on Software Engineering and Methodology
- New York : Association for Computing Machinery, 2022
- [various pagings] : illustrations ; 26 cm.
- ACM Transactions on Software Engineering and Methodology, Volume 31, Issue 3, 2022 .
Includes bibliographical references.
L2S: A Framework for Synthesizing the Most Probable Program under a Specification -- Context- and Fairness-Aware In-Process Crowdworker Recommendation -- ReCDroid+: Automated End-to-End Crash Reproduction from Bug Reports for Android Apps -- Verification of Distributed Systems via Sequential Emulation -- Opinion Mining for Software Development: A Systematic Literature Review -- Stateful Serverless Computing with Crucial -- Applying Bayesian Analysis Guidelines to Empirical Software Engineering Data: The Case of Programming Languages and Code Quality -- On the Faults Found in REST APIs by Automated Test Generation -- Using Personality Detection Tools for Software Engineering Research: How Far Can We Go? -- All in One: Design, Verification, and Implementation of SNOW-optimal Read Atomic Transactions -- Do Developers Really Know How to Use Git Commands? A Large-scale Study Using Stack Overflow -- Industry-Academia Research Collaboration and Knowledge Co-creation: Patterns and Anti-patterns -- Continuous and Proactive Software Architecture Evaluation: An IoT Case -- NPC: Neuron Path Coverage via Characterizing Decision Logic of Deep Neural Networks -- An Empirical Study of the Effectiveness of an Ensemble of Stand-alone Sentiment Detection Tools for Software Engineering Datasets -- Detecting and Augmenting Missing Key Aspects in Vulnerability Descriptions -- Towards Robustness of Deep Program Processing Models-Detection, Estimation, and Enhancement -- Context-Aware Code Change Embedding for Better Patch Correctness Assessment -- XCode: Towards Cross-Language Code Representation with Large-Scale Pre-Training -- An Empirical Study of the Impact of Hyperparameter Tuning and Model Optimization on the Performance Properties of Deep Neural Networks -- Time-travel Investigation: Toward Building a Scalable Attack Detection Framework on Ethereum -- Examining Penetration Tester Behavior in the Collegiate Penetration Testing Competition -- Predictive Models in Software Engineering: Challenges and Opportunities.
[Article Title: L2S: A Framework for Synthesizing the Most Probable Program under a Specification/ Yingfei Xiong and Bo Wang, p. 34:1-34:45] Abstract: In many scenarios, we need to find the most likely program that meets a specification under a local con
1049-331X
INFORMATION TECHNOLOGY
Includes bibliographical references.
L2S: A Framework for Synthesizing the Most Probable Program under a Specification -- Context- and Fairness-Aware In-Process Crowdworker Recommendation -- ReCDroid+: Automated End-to-End Crash Reproduction from Bug Reports for Android Apps -- Verification of Distributed Systems via Sequential Emulation -- Opinion Mining for Software Development: A Systematic Literature Review -- Stateful Serverless Computing with Crucial -- Applying Bayesian Analysis Guidelines to Empirical Software Engineering Data: The Case of Programming Languages and Code Quality -- On the Faults Found in REST APIs by Automated Test Generation -- Using Personality Detection Tools for Software Engineering Research: How Far Can We Go? -- All in One: Design, Verification, and Implementation of SNOW-optimal Read Atomic Transactions -- Do Developers Really Know How to Use Git Commands? A Large-scale Study Using Stack Overflow -- Industry-Academia Research Collaboration and Knowledge Co-creation: Patterns and Anti-patterns -- Continuous and Proactive Software Architecture Evaluation: An IoT Case -- NPC: Neuron Path Coverage via Characterizing Decision Logic of Deep Neural Networks -- An Empirical Study of the Effectiveness of an Ensemble of Stand-alone Sentiment Detection Tools for Software Engineering Datasets -- Detecting and Augmenting Missing Key Aspects in Vulnerability Descriptions -- Towards Robustness of Deep Program Processing Models-Detection, Estimation, and Enhancement -- Context-Aware Code Change Embedding for Better Patch Correctness Assessment -- XCode: Towards Cross-Language Code Representation with Large-Scale Pre-Training -- An Empirical Study of the Impact of Hyperparameter Tuning and Model Optimization on the Performance Properties of Deep Neural Networks -- Time-travel Investigation: Toward Building a Scalable Attack Detection Framework on Ethereum -- Examining Penetration Tester Behavior in the Collegiate Penetration Testing Competition -- Predictive Models in Software Engineering: Challenges and Opportunities.
[Article Title: L2S: A Framework for Synthesizing the Most Probable Program under a Specification/ Yingfei Xiong and Bo Wang, p. 34:1-34:45] Abstract: In many scenarios, we need to find the most likely program that meets a specification under a local con
1049-331X
INFORMATION TECHNOLOGY