ACM Transactions on Software Engineering and Methodology

Material type: TextTextSeries: ; ACM Transactions on Software Engineering and Methodology, Volume 31, Issue 3, 2022Publication details: New York : Association for Computing Machinery, 2022Description: [various pagings] : illustrations ; 26 cmISSN:
  • 1049-331X
Subject(s):
Contents:
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.
Summary: [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
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Serials Serials National University - Manila LRC - Main Periodicals Gen. Ed. - CCIT ACM Transactions on Software Engineering and Methodology, Volume 31, Issue 3, 2022 (Browse shelf(Opens below)) c.1 Available PER000000513
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ACM Transactions on Modeling and Computer Simulation, Volume 31, Issue 1, Dec 2021 ACM Transactions on Modeling and Computer Simulation ACM Transactions on Modeling and Computer Simulation, Volume 31, Issue 3, July 2021 ACM Transactions on Modeling and Computer Simulation ACM Transactions on Software Engineering and Methodology, Volume 31, Issue 2, 2022 ACM Transactions on Software Engineering and Methodology ACM Transactions on Software Engineering and Methodology, Volume 31, Issue 3, 2022 ACM Transactions on Software Engineering and Methodology ACM Transactions on Software Engineering and Methodology, Volume 31, Issue 4, 2022 ACM Transactions on Software Engineering and Methodology ACM Transactions on Software Engineering and Methodology, Volume 32, Issue 2, 2023 ACM Transactions on Software Engineering and Methodology MIS Asia, Volume 2, March - April 2010 MIS Asia

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

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