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Deepa Thiagarajan_Thesis.pdf (680.27 KB)

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EFFICIENT DETECTION OF HANG BUGS IN MOBILE APPLICATIONS

Thiagarajan, Deepa
http://rave.ohiolink.edu/etdc/view?acc_num=osu1480534528352408

Abstract Details

2016, Master of Science, Ohio State University, Electrical and Computer Engineering.
Mobile applications (apps) are growing tremendously in the market. Many apps are useful for our day-to-day activities. In order to survive in the market, these apps must be highly responsive, and free of bugs. For an app to be popular among users, developers must focus on its responsiveness. If the response time of an app is more than the human perceivable delay (100 ms), then the user will feel the app to be slow or unresponsive. This is called the `hang bug’ problem. Developers must ensure that apps are programmed well so as to detect and correct hang bugs. Most of the existing work on hang bugs in mobile apps uses the offline detection technique i.e., detecting bugs before an app is released in the market. Hence, some bugs might exist at runtime when the user interacts with the app. If the offline technique is used, the hang bug problem will remain unknown to the developers until after release, when it will be too late to change. In this thesis, an efficient algorithm has been proposed to detect hang bugs in mobile apps during runtime, as opposed to the offline technique. The algorithm efficiently detects the API/method that is the root cause of the hang bug. There are six algorithms proposed to efficiently detect hang bugs with least delay, memory and CPU utilization. The various cases were tested on real world apps, and results were compared to find the most efficient of the cases for implementation.
Xiaorui Wang, PhD (Advisor)
Joanne DeGroat, PhD (Committee Member)
39 p.
Computer Engineering; Electrical Engineering
Android Applications, Hang Bug, Algorithm, Delay, CPU, Memory Utilization

Recommended Citations

Citations

  • Thiagarajan, D. (2016). EFFICIENT DETECTION OF HANG BUGS IN MOBILE APPLICATIONS [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1480534528352408

    APA Style (7th edition)

  • Thiagarajan, Deepa. EFFICIENT DETECTION OF HANG BUGS IN MOBILE APPLICATIONS. 2016. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1480534528352408.

    MLA Style (8th edition)

  • Thiagarajan, Deepa. "EFFICIENT DETECTION OF HANG BUGS IN MOBILE APPLICATIONS." Master's thesis, Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1480534528352408

    Chicago Manual of Style (17th edition)

osu1480534528352408
546
© 2016, some rights reserved.Creative Commons License EFFICIENT DETECTION OF HANG BUGS IN MOBILE APPLICATIONS by Deepa Thiagarajan is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by The Ohio State University and OhioLINK.