Automated testing of Android apps is essential for app users, developers, and market maintainer communities alike. Given the widespread adoption specificities its development model, literature has proposed various approaches ensuring that not only functional requirements but also nonfunctional are satisfied. In this paper, we aim at providing a clear overview state-of-the-art works around topic testing, in an attempt to highlight main trends, pinpoint methodologies applied, enumerate...

This paper presents the first attempt at fusing data from inertial and vision depth sensors within framework of a hidden Markov model for application hand gesture recognition. The fusion approach introduced in this is general purpose sense that it can be used recognition various body movements. It shown act complementary manner leading to more robust outcome compared with situations when each sensor individually on its own. obtained rates single gestures Microsoft MSR set indicate our...

Fix pattern-based patch generation is a promising direction in Automated Program Repair (APR). Notably, it has been demonstrated to produce more acceptable and correct patches than the obtained with mutation operators through genetic programming. The performance of APR systems, however, depends on fix ingredients mined from changes development histories. Unfortunately, collecting reliable set bug fixes repositories can be challenging. In this paper, we propose investigate possibility an...

Properly benchmarking Automated Program Repair (APR) systems should contribute to the development and adoption of research outputs by practitioners.To that end, community must ensure it reaches significant milestones reliably comparing state-of-the-art tools for a better understanding their strengths weaknesses.In this work, we identify investigate practical bias caused fault localization (FL) step in repair pipeline.We propose highlight different configurations used literature, impact on...

To ensure code readability and facilitate software maintenance, program methods must be named properly. In particular, method names consistent with the corresponding implementations. Debugging remains an important topic in literature, where various approaches analyze commonalities among a large dataset to detect inconsistent suggest better ones. We note that state-of-the-art does not implemented itself assess consistency. thus propose novel automated approach debugging based on analysis of...

Several static analysis tools, such as Splint or FindBugs, have been proposed to the software development community help detect security vulnerabilities bad programming practices. However, adoption of these tools is hindered by their high false positive rates. If rate too high, developers may get acclimated violation reports from causing concrete and severe bugs being overlooked. Fortunately, some violations are actually addressed resolved developers. We claim that those recurrently fixed...

Test-based automated program repair has been a prolific field of research in software engineering the last decade. Many approaches have indeed proposed, which leverage test suites as weak, but affordable, approximation to specifications. Although literature regularly sets new records on number benchmark bugs that can be fixed, several studies increasingly raise concerns about limitations and biases state-of-the-art approaches. For example, correctness generated patches questioned studies,...

A large body of the literature automated program repair develops approaches where patches are generated to be validated against an oracle (e.g., a test suite). Because such can imperfect, patches, although by oracle, may actually incorrect. While state art explore research directions that require dynamic information or rely on manually-crafted heuristics, we study benefit learning code representations in order learn deep features encode properties patch correctness. Our empirical work mainly...

To improve software quality, just-in-time defect prediction (JIT-DP) (identifying defect-inducing commits) and localization (JIT-DL) code lines in have been widely studied by learning semantic features or expert respectively, indeed achieved promising performance. Semantic describe change commits from different aspects, however, the best of two not fully explored together to boost literature yet. Additional, JIT-DP identifies defects at coarse commit level, while as consequent task JIT-DP,...

Automated program repair (APR) has extensively been developed by leveraging search-based techniques, in which fix ingredients are explored and identified different granularities from a specific search space. State-of-the approaches often find using mutation operators or manually-crafted templates. We argue that the can be searched an online mode, code techniques to potentially-fixed versions of buggy fragments actions extracted. In this study, we present APR tool, LSRepair, automatically...

We revisit the performance of template-based APR to build comprehensive knowledge about effectiveness fix patterns, and highlight importance complementary steps such as fault localization or donor code retrieval. To that end, we first investigate literature collect, summarize label recurrently-used patterns. Based on investigation, TBar, a straightforward tool systematically attempts apply these patterns program bugs. thoroughly evaluate TBar Defects4J benchmark. In particular, assess actual...

Bug fixing is a time-consuming and tedious task. To reduce the manual efforts in bug fixing, researchers have presented automated approaches to software repair. Unfortunately, recent studies shown that state-of-the-art techniques repair tend generate patches only for small number of bugs even with quality issues (e.g., incorrect behavior nonsensical changes). improve program (APR) techniques, community should deepen its knowledge on actions from real-world since most rely written by human...

In this paper, we present the first exploratory study of deprecated Python library APIs to understand status quo API deprecation in realm libraries. Specifically, aim comprehend how are declared and documented practice by their maintainers, users react them. By thoroughly looking into six reputed libraries 1,200 GitHub projects, experimentally observe that is poorly handled contributors, which subsequently introduce difficulties for developers resolve usage APIs. This empirical evidence...

Issue tracking systems are commonly used in modern software development for collecting feedback from users and developers. An ultimate automation target of maintenance is then the systematization patch generation user-reported bugs. Although this ambition aligned with momentum automated program repair, literature has, so far, mostly focused on generate-and-validate setups where fault localization driven by a well-defined test suite. On one hand, however, common (yet strong) assumption...

How do we know a generated patch is correct? This key challenging question that automated program repair (APR) systems struggle to address given the incompleteness of available test suites. Our intuition can triage correct patches by checking whether each implements code changes (i.e., behavior) are relevant bug it addresses. Such commonly specified failing case. Towards predicting correctness in APR, propose novel yet simple hypothesis on how link between behavior and specifications be...

Numerous mobile apps have leveraged deep learning capabilities. However, on-device models are vulnerable to attacks as they can be easily extracted from their corresponding apps. Although the structure and parameters information of these accessed, existing attacking approaches only generate black-box (i.e., indirect white-box attacks), which less effective efficient than strategies. This is because (DL) frameworks like TensorFlow Lite (TFLite) do not support gradient computing (referred...

In deeper layers, ResNet heavily depends on skip connections and Relu. Although have demonstrated their usefulness in networks, a major issue arises when the dimensions between layers are not consistent. such cases, it is necessary to use techniques as zero-padding or projection match layers. These adjustments increase complexity of network architecture, resulting an parameter number rise computational costs. Another problem vanishing gradient caused by utilizing our model, after making...

This paper presents a multi-Hidden Markov Model (HMM) classification approach for hand gesture recognition by utilizing two differing modality and low-cost sensors. The sensors consist of Kinect depth camera wearable inertial sensor. It is shown that the multi-HMM based on nine signals are simultaneously captured these leads to more robust compared situation when only single HMM used generate likelihood probabilities gestures. applied gestures $1Unistroke Recognizer application results...

Code comments are key to program comprehension. When they not consistent with the code, maintenance is hindered. Yet developers often forget update along their code evolution. With recent advances in neural machine translation, research community contemplating novel approaches for automatically generating up-to-date following changes. CUP such an example state-of-the-art approach whose promising performance remains however be comprehensively assessed. Our study contributes literature by...

The heavy fragmentation of the Android ecosystem has led to severe compatibility issues with apps, including those that crash at runtime or cannot be installed on certain devices but work well other devices. To address this problem, various approaches have been proposed detect and fix automatically. However, these all come limitations fixing issues, e.g., can only one specific type deal multi-invocation in a single line released apps. overcome limitations, we propose generic approach aims...