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AutoTap: Synthesizing and Repairing Trigger-Action Programs Using LTL Properties.

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Title: AutoTap: Synthesizing and Repairing Trigger-Action Programs Using LTL Properties.
Authors: Lefan Zhang1 lefanz@uchicago.edu, Weijia He1 hewj@uchicago.edu, Martinez, Jesse1 jessjmart@uchicago.edu, Brackenbury, Noah1 brackenburyn@uchicago.edu, Shan Lu1 shanlu@uchicago.edu, Ur, Blase1 blase@uchicago.edu
Source: ICSE: International Conference on Software Engineering. 5/25/2019, p281-291. 11p.
Subjects: End-user computing software, Computer software testing, Computer science, Artificial intelligence, Software engineering
Abstract: End-user programming, particularly trigger-action programming (TAP), is a popular method of letting users express their intent for how smart devices and cloud services interact. Unfortunately, sometimes it can be challenging for users to correctly express their desires through TAP. This paper presents AutoTap, a system that lets novice users easily specify desired properties for devices and services. AutoTap translates these properties to linear temporal logic (LTL) and both automatically synthesizes property-satisfying TAP rules from scratch and repairs existing TAP rules. We designed AutoTap based on a user study about properties users wish to express. Through a second user study, we show that novice users made significantly fewer mistakes when expressing desired behaviors using AutoTap than using TAP rules. Our experiments show that AutoTap is a simple and effective option for expressive end-user programming. [ABSTRACT FROM AUTHOR]
Copyright of ICSE: International Conference on Software Engineering is the property of Association for Computing Machinery and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: AutoTap: Synthesizing and Repairing Trigger-Action Programs Using LTL Properties.
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  Data: <searchLink fieldCode="AR" term="%22Lefan+Zhang%22">Lefan Zhang</searchLink><relatesTo>1</relatesTo><i> lefanz@uchicago.edu</i><br /><searchLink fieldCode="AR" term="%22Weijia+He%22">Weijia He</searchLink><relatesTo>1</relatesTo><i> hewj@uchicago.edu</i><br /><searchLink fieldCode="AR" term="%22Martinez%2C+Jesse%22">Martinez, Jesse</searchLink><relatesTo>1</relatesTo><i> jessjmart@uchicago.edu</i><br /><searchLink fieldCode="AR" term="%22Brackenbury%2C+Noah%22">Brackenbury, Noah</searchLink><relatesTo>1</relatesTo><i> brackenburyn@uchicago.edu</i><br /><searchLink fieldCode="AR" term="%22Shan+Lu%22">Shan Lu</searchLink><relatesTo>1</relatesTo><i> shanlu@uchicago.edu</i><br /><searchLink fieldCode="AR" term="%22Ur%2C+Blase%22">Ur, Blase</searchLink><relatesTo>1</relatesTo><i> blase@uchicago.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22ICSE%3A+International+Conference+on+Software+Engineering%22">ICSE: International Conference on Software Engineering</searchLink>. 5/25/2019, p281-291. 11p.
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  Data: <searchLink fieldCode="DE" term="%22End-user+computing+software%22">End-user computing software</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software+testing%22">Computer software testing</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+science%22">Computer science</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Software+engineering%22">Software engineering</searchLink>
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  Data: End-user programming, particularly trigger-action programming (TAP), is a popular method of letting users express their intent for how smart devices and cloud services interact. Unfortunately, sometimes it can be challenging for users to correctly express their desires through TAP. This paper presents AutoTap, a system that lets novice users easily specify desired properties for devices and services. AutoTap translates these properties to linear temporal logic (LTL) and both automatically synthesizes property-satisfying TAP rules from scratch and repairs existing TAP rules. We designed AutoTap based on a user study about properties users wish to express. Through a second user study, we show that novice users made significantly fewer mistakes when expressing desired behaviors using AutoTap than using TAP rules. Our experiments show that AutoTap is a simple and effective option for expressive end-user programming. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of ICSE: International Conference on Software Engineering is the property of Association for Computing Machinery and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1109/ICSE.2019.00043
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        Text: English
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              Text: 5/25/2019
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