Policy Enforcement with Proactive Libraries

Software libraries implement APIs that deliver reusable functionalities. To correctly use these functionalities, software applications must satisfy certain correctness policies, for instance policies about the order some API methods can be invoked and about the values that can be used for the parameters. If these policies are violated, applications may produce misbehaviors and failures at runtime. Although this problem is general, applications that incorrectly use API methods are more frequent in certain contexts. For instance, Android provides a rich and rapidly evolving set of APIs that might be used incorrectly by app developers who often implement and publish faulty apps in the marketplaces. To mitigate this problem, we introduce the novel notion of proactive library, which augments classic libraries with the capability of proactively detecting and healing misuses at run- time. Proactive libraries blend libraries with multiple proactive modules that collect data, check the correctness policies of the libraries, and heal executions as soon as the violation of a correctness policy is detected. The proactive modules can be activated or deactivated at runtime by the users and can be implemented without requiring any change to the original library and any knowledge about the applications that may use the library. We evaluated proactive libraries in the context of the Android ecosystem. Results show that proactive libraries can automati- cally overcome several problems related to bad resource usage at the cost of a small overhead.Comment: O. Riganelli, D. Micucci and L. Mariani, "Policy Enforcement with Proactive Libraries" 2017 IEEE/ACM 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), Buenos Aires, Argentina, 2017, pp. 182-19

A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache

NLP2Code: Code Snippet Content Assist via Natural Language Tasks

Developers increasingly take to the Internet for code snippets to integrate into their programs. To save developers the time required to switch from their development environments to a web browser in the quest for a suitable code snippet, we introduce NLP2Code, a content assist for code snippets. Unlike related tools, NLP2Code integrates directly into the source code editor and provides developers with a content assist feature to close the vocabulary gap between developers' needs and code snippet meta data. Our preliminary evaluation of NLP2Code shows that the majority of invocations lead to code snippets rated as helpful by users and that the tool is able to support a wide range of tasks.Comment: tool demo video available at https://www.youtube.com/watch?v=h-gaVYtCznI; to appear as a tool demo paper at ICSME 2017 (https://icsme2017.github.io/

De-ossifying the Internet Transport Layer : A Survey and Future Perspectives

ACKNOWLEDGMENT The authors would like to thank the anonymous reviewers for their useful suggestions and comments.Peer reviewedPublisher PD

Raising the Datagram API to Support Transport Protocol Evolution

Some application developers can wield huge resources to build new transport protocols, for these developers the present UDP Socket API is perfectly fine. They have access to large test beds and sophisticated tools. Many developers do not have these resources. This paper presents a new high-level Datagram API that is for everyone else, this has an advantage of offering a clear evolutionary path to support new requirements. This new API is needed to move forward the base of the system, allowing developers with limited resources to evolve their applications while accessing new network services

Overcoming Language Dichotomies: Toward Effective Program Comprehension for Mobile App Development

Mobile devices and platforms have become an established target for modern software developers due to performant hardware and a large and growing user base numbering in the billions. Despite their popularity, the software development process for mobile apps comes with a set of unique, domain-specific challenges rooted in program comprehension. Many of these challenges stem from developer difficulties in reasoning about different representations of a program, a phenomenon we define as a "language dichotomy". In this paper, we reflect upon the various language dichotomies that contribute to open problems in program comprehension and development for mobile apps. Furthermore, to help guide the research community towards effective solutions for these problems, we provide a roadmap of directions for future work.Comment: Invited Keynote Paper for the 26th IEEE/ACM International Conference on Program Comprehension (ICPC'18