ArCode: Facilitating the Use of Application Frameworks to Implement Tactics and Patterns
This addresses the problem for novice programmers in software development by providing a tool to facilitate correct API usage in application frameworks, though it is incremental as it builds on existing techniques.
The paper tackles the challenge of learning and correctly using frameworks' APIs to implement architectural tactics and patterns by introducing ArCode, a learning-based approach that includes graph-based specification learning, program analysis, and a recommender module, and shows it outperforms prior techniques like MAPO and GrouMiner in API recommendation and misuse detection.
Software designers and developers are increasingly relying on application frameworks as first-class design concepts. They instantiate the services that frameworks provide to implement various architectural tactics and patterns. One of the challenges in using frameworks for such tasks is the difficulty of learning and correctly using frameworks' APIs. This paper introduces a learning-based approach called ArCode to help novice programmers correctly use frameworks' APIs to implement architectural tactics and patterns. ArCode has several novel components: a graph-based approach for learning specification of a framework from a limited number of training software, a program analysis algorithm to eliminate erroneous training data, and a recommender module to help programmers use APIs correctly and identify API misuses in their programs. We evaluated our technique across two popular frameworks: JAAS security framework used for authentication and authorization tactic and Java RMI framework used to enable remote method invocation between client and server and other object-oriented patterns. Our evaluation results show (i) the feasibility of using ArCode to learn the specification of a framework; (ii) ArCode generates accurate recommendations for finding the next API call to implement an architectural tactic/pattern based on the context of the programmer's code; (iii) it accurately detects API misuses in the code that implements a tactic/pattern and provides fix recommendations. Comparison of ArCode with two prior techniques (MAPO and GrouMiner) on API recommendation and misuse detection shows that ArCode outperforms these approaches.