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Plackett-Luce Regression Mixture Model For Heterogeneous Rankings, Maksim Tkachenko, Hady W. Lauw
Plackett-Luce Regression Mixture Model For Heterogeneous Rankings, Maksim Tkachenko, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Learning to rank is an important problem in many scenarios, such as information retrieval, natural language processing, recommender systems, etc. The objective is to learn a function that ranks a number of instances based on their features. In the vast majority of the learning to rank literature, there is an implicit assumption that the population of ranking instances are homogeneous, and thus can be modeled by a single central ranking function. In this work, we are concerned with learning to rank for a heterogeneous population, which may consist of a number of sub-populations, each of which may rank objects dierently. …
Hydra: Massively Compositional Model For Cross-Project Defect Prediction, Xin Xia, David Lo, Sinno Jialin Pan, Nachiappan Nagappan, Xinyu Wang
Hydra: Massively Compositional Model For Cross-Project Defect Prediction, Xin Xia, David Lo, Sinno Jialin Pan, Nachiappan Nagappan, Xinyu Wang
Research Collection School Of Computing and Information Systems
Most software defect prediction approaches are trained and applied on data from the same project. However, often a new project does not have enough training data. Cross-project defect prediction, which uses data from other projects to predict defects in a particular project, provides a new perspective to defect prediction. In this work, we propose a HYbrid moDel Reconstruction Approach (HYDRA) for cross-project defect prediction, which includes two phases: genetic algorithm (GA) phase and ensemble learning (EL) phase. These two phases create a massive composition of classifiers. To examine the benefits of HYDRA, we perform experiments on 29 datasets from the …
Online Adaptive Passive-Aggressive Methods For Non-Negative Matrix Factorization And Its Applications, Chenghao Liu, Hoi, Steven C. H., Peilin Zhao, Jianling Sun, Ee-Peng Lim
Online Adaptive Passive-Aggressive Methods For Non-Negative Matrix Factorization And Its Applications, Chenghao Liu, Hoi, Steven C. H., Peilin Zhao, Jianling Sun, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
This paper aims to investigate efficient and scalable machine learning algorithms for resolving Non-negative Matrix Factorization (NMF), which is important for many real-world applications, particularly for collaborative filtering and recommender systems. Unlike traditional batch learning methods, a recently proposed online learning technique named "NN-PA" tackles NMF by applying the popular Passive-Aggressive (PA) online learning, and found promising results. Despite its simplicity and high efficiency, NN-PA falls short in at least two critical limitations: (i) it only exploits the first-order information and thus may converge slowly especially at the beginning of online learning tasks; (ii) it is sensitive to some key …
Combining Word Embedding With Information Retrieval To Recommend Similar Bug Reports, Xinli Yang, David Lo, Xin Xia, Lingfeng Bao, Jianling Sun
Combining Word Embedding With Information Retrieval To Recommend Similar Bug Reports, Xinli Yang, David Lo, Xin Xia, Lingfeng Bao, Jianling Sun
Research Collection School Of Computing and Information Systems
Similar bugs are bugs that require handling of many common code files. Developers can often fix similar bugs with a shorter time and a higher quality since they can focus on fewer code files. Therefore, similar bug recommendation is a meaningful task which can improve development efficiency. Rocha et al. propose the first similar bug recommendation system named NextBug. Although NextBug performs better than a start-of-the-art duplicated bug detection technique REP, its performance is not optimal and thus more work is needed to improve its effectiveness. Technically, it is also rather simple as it relies only upon a standard information …
Recommending Code Changes For Automatic Backporting Of Linux Device Drivers, Ferdian Thung, Xuan Bach D. Le, David Lo
Recommending Code Changes For Automatic Backporting Of Linux Device Drivers, Ferdian Thung, Xuan Bach D. Le, David Lo
Research Collection School Of Computing and Information Systems
Device drivers are essential components of any operating system (OS). They specify the communication protocol that allows the OS to interact with a device. However, drivers for new devices are usually created for a specific OS version. These drivers often need to be backported to the older versions to allow use of the new device. Backporting is often done manually, and is tedious and error prone. To alleviate this burden on developers, we propose an automatic recommendation system to guide the selection of backporting changes. Our approach analyzes the version history for cues to recommend candidate changes. We have performed …
Attribute-Based Encryption With Granular Revocation, Hui Cui, Deng, Robert H., Xuhua Ding, Yingjiu Li
Attribute-Based Encryption With Granular Revocation, Hui Cui, Deng, Robert H., Xuhua Ding, Yingjiu Li
Research Collection School Of Computing and Information Systems
Attribute-based encryption (ABE) enables an access control mechanism over encrypted data by specifying access policies over attributes associated with private keys or ciphertexts, which is a promising solution to protect data privacy in cloud storage services. As an encryption system that involves many data users whose attributes might change over time, it is essential to provide a mechanism to selectively revoke data users’ attributes in an ABE system. However, most of the previous revokable ABE schemes consider how to disable revoked data users to access (newly) encrypted data in the system, and there are few of them that can be …
Empirical Study On Synthesis Engines For Semantics-Based Program Repair, Le Dinh Xuan Bach, David Lo, Claire Le Goues
Empirical Study On Synthesis Engines For Semantics-Based Program Repair, Le Dinh Xuan Bach, David Lo, Claire Le Goues
Research Collection School Of Computing and Information Systems
Automatic Program Repair (APR) is an emerging and rapidly growing research area, with many techniques proposed to repair defective software. One notable state-of-the-art line of APR approaches is known as semantics-based techniques, e.g., Angelix, which extract semantics constraints, i.e., specifications, via symbolic execution and test suites, and then generate repairs conforming to these constraints using program synthesis. The repair capability of such approaches-expressive power, output quality, and scalability-naturally depends on the underlying synthesis technique. However, despite recent advances in program synthesis, not much attention has been paid to assess, compare, or leverage the variety of available synthesis engine capabilities in …
Enhancing Automated Program Repair With Deductive Verification, Xuan-Bach D. Le, Quang Loc Le, David Lo, Claire Le Goues
Enhancing Automated Program Repair With Deductive Verification, Xuan-Bach D. Le, Quang Loc Le, David Lo, Claire Le Goues
Research Collection School Of Computing and Information Systems
Automated program repair (APR) is a challenging process of detecting bugs, localizing buggy code, generating fix candidates and validating the fixes. Effectiveness of program repair methods relies on the generated fix candidates, and the methods used to traverse the space of generated candidates to search for the best ones. Existing approaches generate fix candidates based on either syntactic searches over source code or semantic analysis of specification, e.g., test cases. In this paper, we propose to combine both syntactic and semantic fix candidates to enhance the search space of APR, and provide a function to effectively traverse the search space. …
Satt: Tailoring Code Metric Thresholds For Different Software Architectures, Maurício Aniche, Christoph Treude, Andy Zaidman, Arie Van Deursen, Marco Aurélio Gerosa
Satt: Tailoring Code Metric Thresholds For Different Software Architectures, Maurício Aniche, Christoph Treude, Andy Zaidman, Arie Van Deursen, Marco Aurélio Gerosa
Research Collection School Of Computing and Information Systems
Code metric analysis is a well-known approach for assessing the quality of a software system. However, current tools and techniques do not take the system architecture (e.g., MVC, Android) into account. This means that all classes are assessed similarly, regardless of their specific responsibilities. In this paper, we propose SATT (Software Architecture Tailored Thresholds), an approach that detects whether an architectural role is considerably different from others in the system in terms of code metrics, and provides a specific threshold for that role. We evaluated our approach on 2 different architectures (MVC and Android) in more than 400 projects. We …
"Automated Debugging Considered Harmful" Considered Harmful: A User Study Revisiting The Usefulness Of Spectra-Based Fault Localization Techniques With Professionals Using Real Bugs From Large Systems, Xin Xia, Lingfeng Bao, David Lo, Shanping Li
"Automated Debugging Considered Harmful" Considered Harmful: A User Study Revisiting The Usefulness Of Spectra-Based Fault Localization Techniques With Professionals Using Real Bugs From Large Systems, Xin Xia, Lingfeng Bao, David Lo, Shanping Li
Research Collection School Of Computing and Information Systems
Due to the complexity of software systems, bugs are inevitable. Software debugging is tedious and time consuming. To help developers perform this crucial task, a number of spectra-based fault localization techniques have been proposed. In general, spectra-based fault localization helps developers to find the location of a bug given its symptoms (e.g., program failures). A previous study by Parnin and Orso however implies that several assumptions made by existing work on spectra-based fault localization do not hold in practice, which hinders the practical usage of these tools. Moreover, a recent study by Xie et al. claims that spectra-based fault localization …
Inferring Links Between Concerns And Methods With Multi-Abstraction Vector Space Model, Yun Zhang, David Lo, Xin Xia, Tien-Duy B. Le, Giuseppe Scanniello, Jianling Sun
Inferring Links Between Concerns And Methods With Multi-Abstraction Vector Space Model, Yun Zhang, David Lo, Xin Xia, Tien-Duy B. Le, Giuseppe Scanniello, Jianling Sun
Research Collection School Of Computing and Information Systems
Concern localization refers to the process of locating code units that match a particular textual description. It takes as input textual documents such as bug reports and feature requests and outputs a list of candidate code units that are relevant to the bug reports or feature requests. Many information retrieval (IR) based concern localization techniques have been proposed in the literature. These techniques typically represent code units and textual descriptions as a bag of tokens at one level of abstraction, e.g., each token is a word, or each token is a topic. In this work, we propose a multi-abstraction concern …
Fast Covariant Vlad For Image Search, Wan-Lei Zhao, Chong-Wah Ngo, Hanzi Wang
Fast Covariant Vlad For Image Search, Wan-Lei Zhao, Chong-Wah Ngo, Hanzi Wang
Research Collection School Of Computing and Information Systems
Vector of locally aggregated descriptor (VLAD) is a popular image encoding approach for its simplicity and better scalability over conventional bag-of-visual-word approach. In order to enhance its distinctiveness and geometric invariance, covariant VLAD (CVLAD) is proposed to pool local features based on their dominant orientations/characteristic scales, which leads to a geometric-aware representation. This representation achieves rotation/scale invariance when being associated with circular matching. However, the circular matching induces several times of computation overhead, which makes CVLAD hardly suitable for large-scale retrieval tasks. In this paper, the issue of computation overhead is alleviated by performing the circular matching in CVLAD's frequency …
Developers’ Perceptions On Object-Oriented Design And Architectural Roles, Maurício Aniche, Marco Aurélio Gerosa, Christoph Treude
Developers’ Perceptions On Object-Oriented Design And Architectural Roles, Maurício Aniche, Marco Aurélio Gerosa, Christoph Treude
Research Collection School Of Computing and Information Systems
Software developers commonly rely on well-known software architecture patterns, such as MVC, to build their applications. In many of these patterns, classes play specific roles in the system, such as Controllers or Entities, which means that each of these classes has specific characteristics in terms of object-oriented class design and implementation. Indeed, as we have shown in a previous study, architectural roles are different from each other in terms of code metrics. In this paper, we present a study in a software development company in which we captured developers’ perceptions on object-oriented design aspects of the architectural roles in their …
Server-Aided Revocable Attribute-Based Encryption, Hui Cui, Deng, Robert H., Yingjiu Li, Baodong Qin
Server-Aided Revocable Attribute-Based Encryption, Hui Cui, Deng, Robert H., Yingjiu Li, Baodong Qin
Research Collection School Of Computing and Information Systems
As a one-to-many public key encryption system, attribute-based encryption (ABE) enables scalable access control over encrypted data in cloud storage services. However, efficient user revocation has been a very challenging problem in ABE. To address this issue, Boldyreva, Goyal and Kumar [5] introduced a revocation method by combining the binary tree data structure with fuzzy identity-based encryption, in which a key generation center (KGC) periodically broadcasts key update information to all data users over a public channel. The Boldyreva-Goyal-Kumar approach reduces the size of key updates from linear to logarithm in the number of users, and it has been widely …
Soft Confidence-Weighted Learning, Jialei Wang, Peilin Zhao, Hoi, Steven C. H.
Soft Confidence-Weighted Learning, Jialei Wang, Peilin Zhao, Hoi, Steven C. H.
Research Collection School Of Computing and Information Systems
Online learning plays an important role in many big datamining problems because of its high efficiency and scalability. In theliterature, many online learning algorithms using gradient information havebeen applied to solve online classification problems. Recently, more effectivesecond-order algorithms have been proposed, where the correlation between thefeatures is utilized to improve the learning efficiency. Among them,Confidence-Weighted (CW) learning algorithms are very effective, which assumethat the classification model is drawn from a Gaussian distribution, whichenables the model to be effectively updated with the second-order informationof the data stream. Despite being studied actively, these CW algorithms cannothandle nonseparable datasets and noisy datasets very …
Control Flow Integrity Enforcement With Dynamic Code Optimization, Yan Lin, Xiaoxiao Tang, Debin Gao, Jianming Fu
Control Flow Integrity Enforcement With Dynamic Code Optimization, Yan Lin, Xiaoxiao Tang, Debin Gao, Jianming Fu
Research Collection School Of Computing and Information Systems
Control Flow Integrity (CFI) is an attractive security property with which most injected and code reuse attacks can be defeated, including advanced attacking techniques like Return-Oriented Programming (ROP). However, comprehensive enforcement of CFI is expensive due to additional supports needed (e.g., compiler support and presence of relocation or debug information) and performance overhead. Recent research has been trying to strike the balance among reasonable approximation of the CFI properties, minimal additional supports needed, and acceptable performance. We investigate existing dynamic code optimization techniques and find that they provide an architecture on which CFI can be enforced effectively and efficiently. In …
Trustworthy Authentication On Scalable Surveillance Video With Background Model Support, Zhuo Wei, Zheng Yan, Yongdong Wu, Robert H. Deng
Trustworthy Authentication On Scalable Surveillance Video With Background Model Support, Zhuo Wei, Zheng Yan, Yongdong Wu, Robert H. Deng
Research Collection School Of Computing and Information Systems
H.264/SVC (Scalable Video Coding) codestreams, which consist of a single base layer and multiple enhancement layers, are designed for quality, spatial, and temporal scalabilities. They can be transmitted over networks of different bandwidths and seamlessly accessed by various terminal devices. With a huge amount of video surveillance and various devices becoming an integral part of the security infrastructure, the industry is currently starting to use the SVC standard to process digital video for surveillance applications such that clients with different network bandwidth connections and display capabilities can seamlessly access various SVC surveillance (sub)codestreams. In order to guarantee the trustworthiness and …
Predicting Crashing Releases Of Mobile Applications, Xin Xia, Emad Shihab, Yasutaka Kamei, David Lo, Xinyu Wang
Predicting Crashing Releases Of Mobile Applications, Xin Xia, Emad Shihab, Yasutaka Kamei, David Lo, Xinyu Wang
Research Collection School Of Computing and Information Systems
Context: The quality of mobile applications has a vital impact on their user's experience, ratings and ultimately overall success. Given the high competition in the mobile application market, i.e., many mobile applications perform the same or similar functionality, users of mobile apps tend to be less tolerant to quality issues. Goal: Therefore, identifying these crashing releases early on so that they can be avoided will help mobile app developers keep their user base and ensure the overall success of their apps. Method: To help mobile developers, we use machine learning techniques to effectively predict mobile app releases that are more …
Automated Bug Report Field Reassignment And Refinement Prediction, Xin Xia, David Lo, Emad Shihab, Xinyu Wang
Automated Bug Report Field Reassignment And Refinement Prediction, Xin Xia, David Lo, Emad Shihab, Xinyu Wang
Research Collection School Of Computing and Information Systems
Bug fixing is one of the most important activities in software development and maintenance. Bugs are reported, recorded, and managed in bug tracking systems such as Bugzilla. In general, a bug report contains many fields, such as product, component, severity, priority, fixer, operating system (OS), and platform, which provide important information for the bug triaging and fixing process. Our previous study finds that approximately 80% of bug reports have their fields reassigned and refined at least once, and bugs with reassigned and refined fields take more time to fix than bugs with no reassigned and refined fields. Thus, automatically predicting …
Indoor Localization Via Multi-Modal Sensing On Smartphones, Han Xu, Zheng Yang, Zimu Zhou, Longfei Shangguan, Ke Yi, Yunhao Liu
Indoor Localization Via Multi-Modal Sensing On Smartphones, Han Xu, Zheng Yang, Zimu Zhou, Longfei Shangguan, Ke Yi, Yunhao Liu
Research Collection School Of Computing and Information Systems
Indoor localization is of great importance to a wide range ofapplications in shopping malls, office buildings and publicplaces. The maturity of computer vision (CV) techniques andthe ubiquity of smartphone cameras hold promise for offering sub-meter accuracy localization services. However, pureCV-based solutions usually involve hundreds of photos andpre-calibration to construct image database, a labor-intensiveoverhead for practical deployment. We present ClickLoc, anaccurate, easy-to-deploy, sensor-enriched, image-based indoor localization system. With core techniques rooted insemantic information extraction and optimization-based sensor data fusion, ClickLoc is able to bootstrap with few images. Leveraging sensor-enriched photos, ClickLoc also enables user localization with a single photo of the …
How Practitioners Perceive The Relevance Of Esem Research, Jeffrey C. Carver, Oscar Dieste, Nicholas A. Kraft, David Lo, Thomas Zimmermann
How Practitioners Perceive The Relevance Of Esem Research, Jeffrey C. Carver, Oscar Dieste, Nicholas A. Kraft, David Lo, Thomas Zimmermann
Research Collection School Of Computing and Information Systems
Background: The relevance of ESEM research to industry practitioners is key to the long-term health of the conference. Aims: The goal of this work is to understand how ESEM research is perceived within the practitioner community and provide feedback to the ESEM community ensure our research remains relevant. Method: To understand how practitioners perceive ESEM research, we replicated previous work by sending a survey to several hundred industry practitioners at a number of companies around the world. We asked the survey participants to rate the relevance of the research described in 156 ESEM papers published between 2011 and 2015. Results: …
Pada: Power-Aware Development Assistant For Mobile Sensing Applications, Chulhong Min, Seungchul Lee, Changhun Lee, Youngki Lee, Seungwoo Kang, Seungpyo Choi, Wonjung Kim, Junehwa Song
Pada: Power-Aware Development Assistant For Mobile Sensing Applications, Chulhong Min, Seungchul Lee, Changhun Lee, Youngki Lee, Seungwoo Kang, Seungpyo Choi, Wonjung Kim, Junehwa Song
Research Collection School Of Computing and Information Systems
We propose PADA, a new power evaluation tool to measure and optimize power use of mobile sensing applications. Our motivational study with 53 professional developers shows they face huge challenges in meeting power requirements. The key challenges are from the significant time and effort for repetitive power measurements since the power use of sensing applications needs to be evaluated under various real-world usage scenarios and sensing parameters. PADA enables developers to obtain enriched power information under diverse usage scenarios in development environments without deploying and testing applications on real phones in real-life situations. We conducted two user studies with 19 …
An Intelligent System For Personalized Conference Event Recommendation And Scheduling, Aldy Gunawan, Hoong Chuin Lau, Pradeep Varakantham, Wenjie Wang
An Intelligent System For Personalized Conference Event Recommendation And Scheduling, Aldy Gunawan, Hoong Chuin Lau, Pradeep Varakantham, Wenjie Wang
Research Collection School Of Computing and Information Systems
Many conference mobile apps today lack the intelligent feature to automatically generates optimal schedules based on delegates' preferences. This entails two major challenges: (a) identifying preferences of users; and (b) given the preferences, generating a schedule that optimizes his preferences. In this paper, we specifically focus on academic conferences, where users are prompted to input their preferred keywords. Our key contribution is an integrated conference scheduling agent that automatically recognizes user preferences based on keywords, provides a list of recommended talks and optimizes user schedule based on these preferences. To demonstrate the utility of our integrated conference scheduling agent, we …
Representation Learning For Homophilic Preferences, Trong T. Nguyen, Hady W. Lauw
Representation Learning For Homophilic Preferences, Trong T. Nguyen, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Users express their personal preferences through ratings, adoptions, and other consumption behaviors. We seek tolearn latent representations for user preferences from such behavioral data. One representation learning model that has been shown to be effective for large preference datasets is Restricted Boltzmann Machine (RBM). While homophily, or the tendency of friends to share their preferences at some level, is an established notion in sociology, thus far it has not yet been clearly demonstrated on RBM-based preference models. The question lies in how to appropriately incorporate social network into the architecture of RBM-based models for learning representations of preferences. In this …
Is Only One Gps Point Position Sufficient To Locate You To The Road Network Accurately?, Hao Wu, Weiwei Sun, Baihua Zheng
Is Only One Gps Point Position Sufficient To Locate You To The Road Network Accurately?, Hao Wu, Weiwei Sun, Baihua Zheng
Research Collection School Of Computing and Information Systems
Locating only one GPS position to a road segment accurately is crucial to many location-based services such as mobile taxi-hailing service, geo-tagging, POI check-in, etc. This problem is challenging because of errors including the GPS errors and the digital map errors (misalignment and the same representation of bidirectional roads) and a lack of context information. To the best of our knowledge, no existing work studies this problem directly and the work to reduce GPS signal errors by considering hardware aspect is the most relevant. Consequently, this work is the first attempt to solve the problem of locating one GPS position …
Is Only One Gps Position Sufficient To Locate You To The Road Network Accurately?, Hao Wu, Weiwei Sun, Baihua Zheng
Is Only One Gps Position Sufficient To Locate You To The Road Network Accurately?, Hao Wu, Weiwei Sun, Baihua Zheng
Research Collection School Of Computing and Information Systems
Locating only one GPS position to a road segment accurately is crucial to many location-based services such as mobile taxihailing service, geo-tagging, POI check-in, etc. This problem is challenging because of errors including the GPS errors and the digital map errors (misalignment and the same representation of bidirectional roads) and a lack of context information. To the best of our knowledge, no existing work studies this problem directly and the work to reduce GPS signal errors by considering hardware aspect is the most relevant. Consequently, this work is the first attempt to solve the problem of locating one GPS position …
Autoquery: Automatic Construction Of Dependency Queries For Code Search, Shaowei Wang, David Lo, Lingxiao Jiang
Autoquery: Automatic Construction Of Dependency Queries For Code Search, Shaowei Wang, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Many code search techniques have been proposed to return relevant code for a user query expressed as textual descriptions. However, source code is not mere text. It contains dependency relations among various program elements. To leverage these dependencies for more accurate code search results, techniques have been proposed to allow user queries to be expressed as control and data dependency relationships among program elements. Although such techniques have been shown to be effective for finding relevant code, it remains a question whether appropriate queries can be generated by average users. In this work, we address this concern by proposing a …
Safegpu: Contract- And Library-Based Gpgpu For Object-Oriented Languages, Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz
Safegpu: Contract- And Library-Based Gpgpu For Object-Oriented Languages, Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz
Research Collection School Of Computing and Information Systems
Using GPUs as general-purpose processors has revolutionized parallel computing by providing, for a large and growing set of algorithms, massive data-parallelization on desktop machines. An obstacle to their widespread adoption, however, is the difficulty of programming them and the low-level control of the hardware required to achieve good performance. This paper proposes a programming approach, SafeGPU, that aims to make GPU data-parallel operations accessible through high-level libraries for object-oriented languages, while maintaining the performance benefits of lower-level code. The approach provides data-parallel operations for collections that can be chained and combined to express compound computations, with data synchronization and device …
Probabilistic Robust Route Recovery With Spatio-Temporal Dynamics, Hao Wu, Jiangyun Mao, Weiwei Sun, Baihua Zheng, Hanyuan Zhang, Ziyang Chen, Wei Wang
Probabilistic Robust Route Recovery With Spatio-Temporal Dynamics, Hao Wu, Jiangyun Mao, Weiwei Sun, Baihua Zheng, Hanyuan Zhang, Ziyang Chen, Wei Wang
Research Collection School Of Computing and Information Systems
Vehicle trajectories are one of the most important data in location-based services. The quality of trajectories directly affects the services. However, in the real applications, trajectory data are not always sampled densely. In this paper, we study the problem of recovering the entire route between two distant consecutive locations in a trajectory. Most existing works solve the problem without using those informative historical data or solve it in an empirical way. We claim that a data-driven and probabilistic approach is actually more suitable as long as data sparsity can be well handled. We propose a novel route recovery system in …
Api Recommendation System For Software Development, Ferdian Thung
Api Recommendation System For Software Development, Ferdian Thung
Research Collection School Of Computing and Information Systems
Nowadays, software developers often utilize existing third party libraries and make use of Application Programming Interface (API) to develop a software. However, it is not always obvious which library to use or whether the chosen library will play well with other libraries in the system. Furthermore, developers need to spend some time to understand the API to the point that they can freely use the API methods and putting the right parameters inside them. In this work, I plan to automatically recommend relevant APIs to developers. This API recommendation can be divided into multiple stages. First, we can recommend relevant …