Workshop DeMobile 2013 – Author Index |
Contents -
Abstracts -
Authors
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Abreu, Rui |
![]() Pedro Machado, José Campos, and Rui Abreu (University of Porto, Portugal) Automated diagnosis of errors and/or failures detected during software testing can greatly improve the efficiency of the debugging process, and thus help to make applications more reliable. In this paper, we propose an approach, dubbed MZoltar, offering dynamic analysis (namely, spectrum-based fault localization) of mobile apps that produces a diagnostic report to help identifying potential defects quickly. The approach also offers a graphical representation of the diagnostic report, making it easier to understand. Our experimental results show that the approach requires low runtime overhead (5.75% on average), while the tester needs to inspect 5 components (statements in this paper) on average to find the fault. ![]() ![]() |
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Bnayahu, Jonathan |
![]() Eli Packer, Tali Yatzkar-Haham, Alexander Kofman, and Jonathan Bnayahu (IBM, Israel) In recent years we have been witness to rapidly growing adoption and spread of smart mobile devices, not only for personal use but also by enterprises. An important feature provided by majority of these devices is location awareness – ability to detect the device’s location on Earth and use it in applications. For enterprises, there is tremendous value in ability to leverage location context in business logic. However, implementing location awareness in enterprise environments introduces new challenges, both technical and organizational. In this paper we present and discuss main technical challenges associated with building location aware enterprise software systems. ![]() |
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Campos, José |
![]() Pedro Machado, José Campos, and Rui Abreu (University of Porto, Portugal) Automated diagnosis of errors and/or failures detected during software testing can greatly improve the efficiency of the debugging process, and thus help to make applications more reliable. In this paper, we propose an approach, dubbed MZoltar, offering dynamic analysis (namely, spectrum-based fault localization) of mobile apps that produces a diagnostic report to help identifying potential defects quickly. The approach also offers a graphical representation of the diagnostic report, making it easier to understand. Our experimental results show that the approach requires low runtime overhead (5.75% on average), while the tester needs to inspect 5 components (statements in this paper) on average to find the fault. ![]() ![]() |
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Kofman, Alexander |
![]() Eli Packer, Tali Yatzkar-Haham, Alexander Kofman, and Jonathan Bnayahu (IBM, Israel) In recent years we have been witness to rapidly growing adoption and spread of smart mobile devices, not only for personal use but also by enterprises. An important feature provided by majority of these devices is location awareness – ability to detect the device’s location on Earth and use it in applications. For enterprises, there is tremendous value in ability to leverage location context in business logic. However, implementing location awareness in enterprise environments introduces new challenges, both technical and organizational. In this paper we present and discuss main technical challenges associated with building location aware enterprise software systems. ![]() |
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Machado, Pedro |
![]() Pedro Machado, José Campos, and Rui Abreu (University of Porto, Portugal) Automated diagnosis of errors and/or failures detected during software testing can greatly improve the efficiency of the debugging process, and thus help to make applications more reliable. In this paper, we propose an approach, dubbed MZoltar, offering dynamic analysis (namely, spectrum-based fault localization) of mobile apps that produces a diagnostic report to help identifying potential defects quickly. The approach also offers a graphical representation of the diagnostic report, making it easier to understand. Our experimental results show that the approach requires low runtime overhead (5.75% on average), while the tester needs to inspect 5 components (statements in this paper) on average to find the fault. ![]() ![]() |
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Moshnyaga, Vasily G. |
![]() Vasily G. Moshnyaga (Fukuoka University, Japan) Energy assessment is important to reduce environmental impact of modern IT. This paper analyzes the total energy consumption associated with production, delivery and use of application software for mobile devices and assesses its contribution to green-house gas emissions. The results reveal that as application size grows, the energy consumed at the production stage becomes a dominant factor of the total lifecycle energy. However, as the application becomes largely used, most of the lifecycle energy is consumed at the use stage due to updates. The paper investigates dependency of lifecycle energy on the application size, the number of application copies in use as well as the size of update and shows the trend. A lifecycle energy assessment of Mail K9 application is presented as a case study. ![]() |
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Packer, Eli |
![]() Eli Packer, Tali Yatzkar-Haham, Alexander Kofman, and Jonathan Bnayahu (IBM, Israel) In recent years we have been witness to rapidly growing adoption and spread of smart mobile devices, not only for personal use but also by enterprises. An important feature provided by majority of these devices is location awareness – ability to detect the device’s location on Earth and use it in applications. For enterprises, there is tremendous value in ability to leverage location context in business logic. However, implementing location awareness in enterprise environments introduces new challenges, both technical and organizational. In this paper we present and discuss main technical challenges associated with building location aware enterprise software systems. ![]() |
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Sagar, Shikhar |
![]() Jack Zhang, Shikhar Sagar, and Emad Shihab (Rochester Institute of Technology, USA) As mobile apps continue to grow in popularity, it is important to study their evolution. Lehman's laws of software evolution have been proposed and used to study the evolution of traditional, large software systems (also known as desktop apps). However, do Lehman's laws of software evolution hold for mobile apps?, especially since developing mobile apps presents different challenges compared to the development of desktop apps. In this paper, we examine the applicability of three of Lehman's laws on mobile apps. In particular, we focused on three laws: the law of continuing change, increasing complexity, and declining quality. We extracted a number of metrics and performed a case study on two applications: VLC and ownCloud. Our findings show that the law of continuing change and declining quality seem to apply for mobile apps, however, we find different outcomes for the law of increasing complexity. Then, we compare the mobile app version to the desktop version and find that the two versions follow the same trends for the law of continuing change. On the contrary, the desktop and mobile version have different trends for the law of increasing complexity and the law of declining quality. ![]() |
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Shihab, Emad |
![]() Jack Zhang, Shikhar Sagar, and Emad Shihab (Rochester Institute of Technology, USA) As mobile apps continue to grow in popularity, it is important to study their evolution. Lehman's laws of software evolution have been proposed and used to study the evolution of traditional, large software systems (also known as desktop apps). However, do Lehman's laws of software evolution hold for mobile apps?, especially since developing mobile apps presents different challenges compared to the development of desktop apps. In this paper, we examine the applicability of three of Lehman's laws on mobile apps. In particular, we focused on three laws: the law of continuing change, increasing complexity, and declining quality. We extracted a number of metrics and performed a case study on two applications: VLC and ownCloud. Our findings show that the law of continuing change and declining quality seem to apply for mobile apps, however, we find different outcomes for the law of increasing complexity. Then, we compare the mobile app version to the desktop version and find that the two versions follow the same trends for the law of continuing change. On the contrary, the desktop and mobile version have different trends for the law of increasing complexity and the law of declining quality. ![]() |
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Yatzkar-Haham, Tali |
![]() Eli Packer, Tali Yatzkar-Haham, Alexander Kofman, and Jonathan Bnayahu (IBM, Israel) In recent years we have been witness to rapidly growing adoption and spread of smart mobile devices, not only for personal use but also by enterprises. An important feature provided by majority of these devices is location awareness – ability to detect the device’s location on Earth and use it in applications. For enterprises, there is tremendous value in ability to leverage location context in business logic. However, implementing location awareness in enterprise environments introduces new challenges, both technical and organizational. In this paper we present and discuss main technical challenges associated with building location aware enterprise software systems. ![]() |
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Zhang, Jack |
![]() Jack Zhang, Shikhar Sagar, and Emad Shihab (Rochester Institute of Technology, USA) As mobile apps continue to grow in popularity, it is important to study their evolution. Lehman's laws of software evolution have been proposed and used to study the evolution of traditional, large software systems (also known as desktop apps). However, do Lehman's laws of software evolution hold for mobile apps?, especially since developing mobile apps presents different challenges compared to the development of desktop apps. In this paper, we examine the applicability of three of Lehman's laws on mobile apps. In particular, we focused on three laws: the law of continuing change, increasing complexity, and declining quality. We extracted a number of metrics and performed a case study on two applications: VLC and ownCloud. Our findings show that the law of continuing change and declining quality seem to apply for mobile apps, however, we find different outcomes for the law of increasing complexity. Then, we compare the mobile app version to the desktop version and find that the two versions follow the same trends for the law of continuing change. On the contrary, the desktop and mobile version have different trends for the law of increasing complexity and the law of declining quality. ![]() |
11 authors
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