Improving reusability of software libraries through usage pattern mining
Modern software systems are increasingly dependent on third-party libraries. It is widely recognized that reusing functionality provided by mature and well-tested third-party libraries can improve developers’ productivity, reduce time-to-market, and produce more reliable software. Today’s open-source repositories provide a wide range of libraries that can be freely downloaded and used. However, as software libraries are documented separately but intended to be used together, developers are unlikely to fully take advantage of these reuse opportunities. In this paper, we present a novel approach to automatically identify third-party library usage patterns, i.e., collections of libraries that are commonly used together by developers. Our approach employs a hierarchical clustering technique to group together software libraries based on external client usage. Our approach is based on the analysis of the joint versus separate use of the libraries. The pattern’s libraries are distributed on different usage cohesion levels/layers. Each layer reflects the co-usage frequency between a set of libraries, while the distribution on the different levels demonstrates the graduation in the degree of co-usage frequency. To evaluate our approach, we mined a large set of over 6000 popular libraries from Maven Central Repository and investigated their usage by over 38,000 client systems from the GitHub repository. Our experiments show that our technique is able to detect the majority (77%) of highly consistent and cohesive library usage patterns across a considerable number of client systems.
Thu 14 Nov
13:40 - 15:20: Papers - Mining and Bug Detection at Cortez 2&3 Chair(s): Chanchal K. RoyUniversity of Saskatchewan | ||||||||||||||||||||||||||||||||||||||||||
13:40 - 14:00 Talk | Automatically 'Verifying' Complex Systems through Learning, Abstraction and Refinement Jingyi WangNational University of Singapore, Singapore, Jun SunSingapore Management University, Singapore, Shengchao QinUniversity of Teesside, Cyrille JegourelISTD, Singapore University of Technology and Design Link to publication | |||||||||||||||||||||||||||||||||||||||||
14:00 - 14:20 Talk | Interactive semi-automated specification mining for debugging: An experience report Mohammad Jafar MashhadiUniversity of Calgary, Taha R. SiddiquiInfoMagnetics Technologies Corp, Hadi HemmatiUniversity of Calgary, Howard W. LoewenDepartment of Electrical & Computer Engineering, University of Calgary Link to publication | |||||||||||||||||||||||||||||||||||||||||
14:20 - 14:40 Talk | Improving reusability of software libraries through usage pattern mining Mohamed Aymen SaiedConcordia University, Ali OuniETS Montreal, University of Quebec, Houari SahraouiUniversité de Montréal, Raula Gaikovina KulaNAIST, Katsuro InoueOsaka University, David LoSingapore Management University Link to publication | |||||||||||||||||||||||||||||||||||||||||
14:40 - 15:00 Talk | Rule-based specification mining leveraging learning to rank Zherui CaoZhejiang University, Yuan TianQueens University, Kingston, Canada, Tien-Duy B. LeSchool of Information Systems, Singapore Management University, David LoSingapore Management University Link to publication | |||||||||||||||||||||||||||||||||||||||||
15:00 - 15:10 Demonstration | TsmartGP: A Tool for Finding Memory Defects with Pointer Analysis Yuexing WangTsinghua University, Guang ChenTsinghua University, Min ZhouTsinghua University, Ming GuTsinghua University, Jiaguang SunTsinghua University | |||||||||||||||||||||||||||||||||||||||||
15:10 - 15:20 Demonstration | Ares: Inferring Error Specifications through Static Analysis Li ChiTsinghua University, Zuxing GuSchool of Software, Tsinghua University, Min ZhouTsinghua University, Ming GuTsinghua University, Hongyu ZhangThe University of Newcastle |