Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Refactoring (16)
- Java (13)
- Java 8 (11)
- Default methods (8)
- Streams (7)
-
- Automated refactoring (6)
- Software evolution (6)
- Software maintenance (6)
- Software tools (6)
- Typestate analysis (6)
- Aspect-oriented programming (5)
- Static analysis (5)
- Automatic parallelization (4)
- Empirical studies (4)
- Enumerated types (4)
- Interfaces (4)
- Aspect-Oriented programming (3)
- Aspect-oriented software (3)
- Concurrency (3)
- Deep learning (3)
- Imperative programs (3)
- Programming (3)
- Software engineering (3)
- Software environments (3)
- Empirical study (2)
- Graph execution (2)
- Icse2017 (2)
- Lambda expressions (2)
- Parallelization (2)
- Pointcut expression recovery (2)
Articles 1 - 30 of 48
Full-Text Articles in Physical Sciences and Mathematics
Μakka: Mutation Testing For Actor Concurrency In Akka Using Real-World Bugs, Mohsen Moradi Moghadam, Mehdi Bagherzadeh, Raffi Takvor Khatchadourian Ph,D,, Hamid Bagheri
Μakka: Mutation Testing For Actor Concurrency In Akka Using Real-World Bugs, Mohsen Moradi Moghadam, Mehdi Bagherzadeh, Raffi Takvor Khatchadourian Ph,D,, Hamid Bagheri
Publications and Research
Actor concurrency is becoming increasingly important in the real-world and mission-critical software. This requires these applications to be free from actor bugs, that occur in the real world, and have tests that are effective in finding these bugs. Mutation testing is a well-established technique that transforms an application to induce its likely bugs and evaluate the effectiveness of its tests in finding these bugs. Mutation testing is available for a broad spectrum of applications and their bugs, ranging from web to mobile to machine learning, and is used at scale in companies like Google and Facebook. However, there still is …
Towards Safe Automated Refactoring Of Imperative Deep Learning Programs To Graph Execution, Raffi Takvor Khatchadourian Ph.D., Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja
Towards Safe Automated Refactoring Of Imperative Deep Learning Programs To Graph Execution, Raffi Takvor Khatchadourian Ph.D., Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja
Publications and Research
Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code—supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged at the expense of run-time performance. Though hybrid approaches aim for the “best of both worlds,” using them effectively requires subtle considerations to make code amenable to safe, accurate, and efficient graph execution. We present our ongoing work on automated refactoring that assists developers in specifying whether …
Towards Safe Automated Refactoring Of Imperative Deep Learning Programs To Graph Execution, Raffi T. Khatchadourian Ph,D,, Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja
Towards Safe Automated Refactoring Of Imperative Deep Learning Programs To Graph Execution, Raffi T. Khatchadourian Ph,D,, Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja
Publications and Research
Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code—supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged at the expense of run-time performance. Though hybrid approaches aim for the "best of both worlds," using them effectively requires subtle considerations to make code amenable to safe, accurate, and efficient graph execution. We present our ongoing work on automated refactoring that assists developers in specifying whether …
How Many Mutex Bugs Can A Simple Analysis Find In Go Programs?, Fumi Takeuchi, Hidehiko Masuhara, Raffi T. Khatchadourian, Youyou Cong, Keisuke Ishibashi
How Many Mutex Bugs Can A Simple Analysis Find In Go Programs?, Fumi Takeuchi, Hidehiko Masuhara, Raffi T. Khatchadourian, Youyou Cong, Keisuke Ishibashi
Publications and Research
In open-source software, it is known that there are many concurrency bugs. A previous study in Go revealed that a considerable number of such bugs are simple (for example, 9% of the bugs are the ones that forget to unlock a mutex,) through a manual program investigation. This paper tries to detect such bugs by applying a simple analysis to see how far such a tool can match the manual analysis. We built a simple intraprocedural control flow analysis in Go, and evaluated its performance concerning the open source programs with concurrency bugs reported in the previous study. Consequently, as …
Challenges In Migrating Imperative Deep Learning Programs To Graph Execution: An Empirical Study, Tatiana Castro Vélez, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Anita Raja
Challenges In Migrating Imperative Deep Learning Programs To Graph Execution: An Empirical Study, Tatiana Castro Vélez, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Anita Raja
Publications and Research
Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code that supports symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development tends to produce DL code that is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, less error-prone imperative DL frameworks encouraging eager execution have emerged at the expense of run-time performance. While hybrid approaches aim for the "best of both worlds," the challenges in applying them in the real world are largely unknown. We conduct a data-driven analysis of challenges—and resultant bugs—involved …
A Tool For Rejuvenating Feature Logging Levels Via Git Histories And Degree Of Interest, Yiming Tang, Allan Spektor, Raffi T. Khatchadourian, Mehdi Bagherzadeh
A Tool For Rejuvenating Feature Logging Levels Via Git Histories And Degree Of Interest, Yiming Tang, Allan Spektor, Raffi T. Khatchadourian, Mehdi Bagherzadeh
Publications and Research
Logging is a significant programming practice. Due to the highly transactional nature of modern software applications, a massive amount of logs are generated every day, which may overwhelm developers. Logging information overload can be dangerous to software applications. Using log levels, developers can print the useful information while hiding the verbose logs during software runtime. As software evolves, the log levels of logging statements associated with the surrounding software feature implementation may also need to be altered. Maintaining log levels necessitates a significant amount of manual effort. In this paper, we demonstrate an automated approach that can rejuvenate feature log …
An Empirical Study Of Refactorings And Technical Debt In Machine Learning Systems, Yiming Tang, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Rhia Singh, Ajani Stewart, Anita Raja
An Empirical Study Of Refactorings And Technical Debt In Machine Learning Systems, Yiming Tang, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Rhia Singh, Ajani Stewart, Anita Raja
Publications and Research
Machine Learning (ML), including Deep Learning (DL), systems, i.e., those with ML capabilities, are pervasive in today’s data-driven society. Such systems are complex; they are comprised of ML models and many subsystems that support learning processes. As with other complex systems, ML systems are prone to classic technical debt issues, especially when such systems are long-lived, but they also exhibit debt specific to these systems. Unfortunately, there is a gap in knowledge of how ML systems evolve and are maintained. In this paper, we fill this gap by studying refactorings, i.e., source-to-source semantics-preserving program transformations, performed in real-world, open-source software, …
An Empirical Study Of Refactorings And Technical Debt In Machine Learning Systems, Yiming Tang, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Rhia Singh, Ajani Stewart, Anita Raja
An Empirical Study Of Refactorings And Technical Debt In Machine Learning Systems, Yiming Tang, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Rhia Singh, Ajani Stewart, Anita Raja
Publications and Research
Machine Learning (ML), including Deep Learning (DL), systems, i.e., those with ML capabilities, are pervasive in today’s data-driven society. Such systems are complex; they are comprised of ML models and many subsystems that support learning processes. As with other complex systems, ML systems are prone to classic technical debt issues, especially when such systems are long-lived, but they also exhibit debt specific to these systems. Unfortunately, there is a gap of knowledge in how ML systems actually evolve and are maintained. In this paper, we fill this gap by studying refactorings, i.e., source-to-source semantics-preserving program transformations, performed in real-world, open-source …
Actor Concurrency Bugs: A Comprehensive Study On Symptoms, Root Causes, Api Usages, And Differences, Mehdi Bagherzadeh, Nicholas Fireman, Anas Shawesh, Raffi T. Khatchadourian
Actor Concurrency Bugs: A Comprehensive Study On Symptoms, Root Causes, Api Usages, And Differences, Mehdi Bagherzadeh, Nicholas Fireman, Anas Shawesh, Raffi T. Khatchadourian
Publications and Research
Actor concurrency is becoming increasingly important in the development of real-world software systems. Although actor concurrency may be less susceptible to some multithreaded concurrency bugs, such as low-level data races and deadlocks, it comes with its own bugs that may be different. However, the fundamental characteristics of actor concurrency bugs, including their symptoms, root causes, API usages, examples, and differences when they come from different sources are still largely unknown. Actor software development can significantly benefit from a comprehensive qualitative and quantitative understanding of these characteristics, which is the focus of this work, to foster better API documentations, development practices, …
An Empirical Study On The Use And Misuse Of Java 8 Streams, Raffi T. Khatchadourian, Yiming Tang, Mehdi Bagherzadeh, Baishakhi Ray
An Empirical Study On The Use And Misuse Of Java 8 Streams, Raffi T. Khatchadourian, Yiming Tang, Mehdi Bagherzadeh, Baishakhi Ray
Publications and Research
Streaming APIs allow for big data processing of native data structures by providing MapReduce-like operations over these structures. However, unlike traditional big data systems, these data structures typically reside in shared memory accessed by multiple cores. Although popular, this emerging hybrid paradigm opens the door to possibly detrimental behavior, such as thread contention and bugs related to non-execution and non-determinism. This study explores the use and misuse of a popular streaming API, namely, Java 8 Streams. The focus is on how developers decide whether or not to run these operations sequentially or in parallel and bugs both specific and tangential …
Safe Automated Refactoring For Intelligent Parallelization Of Java 8 Streams, Raffi T. Khatchadourian, Yiming Tang, Mehdi Bagherzadeh
Safe Automated Refactoring For Intelligent Parallelization Of Java 8 Streams, Raffi T. Khatchadourian, Yiming Tang, Mehdi Bagherzadeh
Publications and Research
Streaming APIs are becoming more pervasive in mainstream Object-Oriented programming languages and platforms. For example, the Stream API introduced in Java 8 allows for functional-like, MapReduce-style operations in processing both finite, e.g., collections, and infinite data structures. However, using this API efficiently involves subtle considerations such as determining when it is best for stream operations to run in parallel, when running operations in parallel can be less efficient, and when it is safe to run in parallel due to possible lambda expression side-effects. ics-preserving fashion. The approach, based on a novel data ordering and typestate analysis, consists of preconditions and …
Safe Automated Refactoring For Intelligent Parallelization Of Java 8 Streams, Raffi T. Khatchadourian, Yiming Tang, Mehdi Bagherzadeh, Syed Ahmed
Safe Automated Refactoring For Intelligent Parallelization Of Java 8 Streams, Raffi T. Khatchadourian, Yiming Tang, Mehdi Bagherzadeh, Syed Ahmed
Publications and Research
Streaming APIs are becoming more pervasive in mainstream Object-Oriented programming languages and platforms. For example, the Stream API introduced in Java 8 allows for functional-like, MapReduce-style operations in processing both finite, e.g., collections, and infinite data structures. However, using this API efficiently involves subtle considerations such as determining when it is best for stream operations to run in parallel, when running operations in parallel can be less efficient, and when it is safe to run in parallel due to possible lambda expression side-effects. Also, streams may not run all operations in parallel depending on particular collectors used in reductions. In …
Safe Automated Refactoring For Intelligent Parallelization Of Java 8 Streams, Raffi T. Khatchadourian, Yiming Tang, Mehdi Bagherzadeh, Syed Ahmed
Safe Automated Refactoring For Intelligent Parallelization Of Java 8 Streams, Raffi T. Khatchadourian, Yiming Tang, Mehdi Bagherzadeh, Syed Ahmed
Publications and Research
Streaming APIs are becoming more pervasive in mainstream Object-Oriented programming languages. For example, the Stream API introduced in Java 8 allows for functional-like, MapReduce-style operations in processing both finite and infinite data structures. However, using this API efficiently involves subtle considerations like determining when it is best for stream operations to run in parallel, when running operations in parallel can be less efficient, and when it is safe to run in parallel due to possible lambda expression side-effects. In this paper, we present an automated refactoring approach that assists developers in writing efficient stream code in a semantics-preserving fashion. The …
A Tool For Optimizing Java 8 Stream Software Via Automated Refactoring, Raffi T. Khatchadourian, Yiming Tang, Mehdi Bagherzadeh, Syed Ahmed
A Tool For Optimizing Java 8 Stream Software Via Automated Refactoring, Raffi T. Khatchadourian, Yiming Tang, Mehdi Bagherzadeh, Syed Ahmed
Publications and Research
Streaming APIs are pervasive in mainstream Object-Oriented languages. For example, the Java 8 Stream API allows for functional-like, MapReduce-style operations in processing both finite and infinite data structures. However, using this API efficiently involves subtle considerations like determining when it is best for stream operations to run in parallel, when running operations in parallel can be less efficient, and when it is safe to run in parallel due to possible lambda expression side-effects. In this paper, we describe the engineering aspects of an open source automated refactoring tool called Optimize Streams that assists developers in writing optimal stream software in …
Poster: Towards Safe Refactoring For Intelligent Parallelization Of Java 8 Streams, Yiming Tang, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Syed Ahmed
Poster: Towards Safe Refactoring For Intelligent Parallelization Of Java 8 Streams, Yiming Tang, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Syed Ahmed
Publications and Research
The Java 8 Stream API sets forth a promising new programming model that incorporates functional-like, MapReduce-style features into a mainstream programming language. However, using streams correctly and efficiently may involve subtle considerations. In this poster, we present our ongoing work and preliminary results towards an automated refactoring approach that assists developers in writing optimal stream code. The approach, based on ordering and typestate analysis, determines when it is safe and advantageous to convert streams to parallel and optimize a parallel streams.
Designing Smart Applications Using Ar (Augmented Reality), Kimberly A. De La Santa
Designing Smart Applications Using Ar (Augmented Reality), Kimberly A. De La Santa
Publications and Research
Augmented Reality is rapidly developing in popularity because it brings elements of the virtual world, into our real world. Augmented Reality (AR) is a variation of Virtual Reality (VR). VR technologies immerses a user inside an imaginary environment. While immersed, the user cannot see the real world around them. In contrast, AR allows the user to see the real world, with virtual objects and information intertwined. Therefore, AR supplements reality and enhances the things we see, hear, and feel. This research project will implement a Web page that gives the user the opportunity to experiment with AR.
Proactive Empirical Assessment Of New Language Feature Adoption Via Automated Refactoring: The Case Of Java 8 Default Methods, Raffi T. Khatchadourian, Hidehiko Masuhara
Proactive Empirical Assessment Of New Language Feature Adoption Via Automated Refactoring: The Case Of Java 8 Default Methods, Raffi T. Khatchadourian, Hidehiko Masuhara
Publications and Research
Programming languages and platforms improve over time, sometimes resulting in new language features that offer many benefits. However, despite these benefits, developers may not always be willing to adopt them in their projects for various reasons. In this paper, we describe an empirical study where we assess the adoption of a particular new language feature. Studying how developers use (or do not use) new language features is important in programming language research and engineering because it gives designers insight into the usability of the language to create meaning programs in that language. This knowledge, in turn, can drive future innovations …
Proactive Empirical Assessment Of New Language Feature Adoption Via Automated Refactoring: The Case Of Java 8 Default Methods, Raffi T. Khatchadourian, Hidehiko Masuhara
Proactive Empirical Assessment Of New Language Feature Adoption Via Automated Refactoring: The Case Of Java 8 Default Methods, Raffi T. Khatchadourian, Hidehiko Masuhara
Publications and Research
Programming languages and platforms improve over time, sometimes resulting in new language features that offer many benefits. However, despite these benefits, developers may not always be willing to adopt them in their projects for various reasons. In this paper, we describe an empirical study where we assess the adoption of a particular new language feature. Studying how developers use (or do not use) new language features is important in programming language research and engineering because it gives designers insight into the usability of the language to create meaning programs in that language. This knowledge, in turn, can drive future innovations …
Poster: Towards Safe Refactoring For Intelligent Parallelization Of Java 8 Streams, Yiming Tang, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Syed Ahmed
Poster: Towards Safe Refactoring For Intelligent Parallelization Of Java 8 Streams, Yiming Tang, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Syed Ahmed
Publications and Research
The Java 8 Stream API sets forth a promising new programming model that incorporates functional-like, MapReduce-style features into a mainstream programming language. However, using streams correctly and efficiently may involve subtle considerations. In this poster, we present our ongoing work and preliminary results to- wards an automated refactoring approach that assists developers in writing optimal stream code. The approach, based on ordering and typestate analysis, determines when it is safe and advantageous to convert streams to parallel and optimize a parallel streams.
On The Use Of Semantic-Based Aig To Automatically Generate Programming Exercises, Laura Zavala, Benito Mendoza
On The Use Of Semantic-Based Aig To Automatically Generate Programming Exercises, Laura Zavala, Benito Mendoza
Publications and Research
In introductory programming courses, proficiency is typically achieved through substantial practice in the form of relatively small assignments and quizzes. Unfortunately, creating programming assignments and quizzes is both, time-consuming and error-prone. We use Automatic Item Generation (AIG) in order to address the problem of creating numerous programming exercises that can be used for assignments or quizzes in introductory programming courses. AIG is based on the use of test-item templates with embedded variables and formulas which are resolved by a computer program with actual values to generate test-items. Thus, hundreds or even thousands of test-items can be generated with a single …
Defaultification Refactoring: A Tool For Automatically Converting Java Methods To Default, Raffi T. Khatchadourian, Hidehiko Masuhara
Defaultification Refactoring: A Tool For Automatically Converting Java Methods To Default, Raffi T. Khatchadourian, Hidehiko Masuhara
Publications and Research
Enabling interfaces to declare (instance) method implementations, Java 8 default methods can be used as a substitute for the ubiquitous skeletal implementation software design pattern. Performing this transformation on legacy software manually, though, may be non-trivial. The refactoring requires analyzing complex type hierarchies, resolving multiple implementation inheritance issues, reconciling differences between class and interface methods, and analyzing tie-breakers (dispatch precedence) with overriding class methods. All of this is necessary to preserve type-correctness and confirm semantics preservation. We demonstrate an automated refactoring tool called Migrate Skeletal Implementation to Interface for transforming legacy Java code to use the new default construct. The …
Automated Refactoring Of Legacy Java Software To Default Methods, Raffi T. Khatchadourian, Hidehiko Masuhara
Automated Refactoring Of Legacy Java Software To Default Methods, Raffi T. Khatchadourian, Hidehiko Masuhara
Publications and Research
Java 8 default methods, which allow interfaces to contain (instance) method implementations, are useful for the skeletal implementation software design pattern. However, it is not easy to transform existing software to exploit default methods as it requires analyzing complex type hierarchies, resolving multiple implementation inheritance issues, reconciling differences between class and interface methods, and analyzing tie-breakers (dispatch precedence) with overriding class methods to preserve type-correctness and confirm semantics preservation. In this paper, we present an efficient, fully-automated, type constraint-based refactoring approach that assists developers in taking advantage of enhanced interfaces for their legacy Java software. The approach features an extensive …
Automated Refactoring Of Legacy Java Software To Default Methods, Raffi T. Khatchadourian, Hidehiko Masuhara
Automated Refactoring Of Legacy Java Software To Default Methods, Raffi T. Khatchadourian, Hidehiko Masuhara
Publications and Research
Java 8 introduces enhanced interfaces, allowing for default (instance) methods that implementers will inherit if none are provided [3]. Default methods can be used [2] as a replacement of the skeletal implementation pattern [1], which creates abstract skeletal implementation classes that implementers extend. Migrating legacy code using the skeletal implementation pattern to instead use default methods can require significant manual effort due to subtle language and semantic restrictions. It requires preserving typecorrectness by analyzing complex type hierarchies, resolving issues arising from multiple inheritance, reconciling differences between class and interface methods, and ensuring tie-breakers with overriding class methods do not alter …
Comparing Tensorflow Deep Learning Performance Using Cpus, Gpus, Local Pcs And Cloud, John Lawrence, Jonas Malmsten, Andrey Rybka, Daniel A. Sabol, Ken Triplin
Comparing Tensorflow Deep Learning Performance Using Cpus, Gpus, Local Pcs And Cloud, John Lawrence, Jonas Malmsten, Andrey Rybka, Daniel A. Sabol, Ken Triplin
Publications and Research
Deep learning is a very computational intensive task. Traditionally GPUs have been used to speed-up computations by several orders of magnitude. TensorFlow is a deep learning framework designed to improve performance further by running on multiple nodes in a distributed system. While TensorFlow has only been available for a little over a year, it has quickly become the most popular open source machine learning project on GitHub. The open source version of TensorFlow was originally only capable of running on a single node while Google’s proprietary version only was capable of leveraging distributed systems. This has now changed. In this …
Automated Refactoring Of Legacy Java Software To Default Methods, Raffi T. Khatchadourian, Hidehiko Masuhara
Automated Refactoring Of Legacy Java Software To Default Methods, Raffi T. Khatchadourian, Hidehiko Masuhara
Publications and Research
Java 8 default methods, which allow interfaces to contain (instance) method implementations, are useful for the skeletal implementation software design pattern. However, it is not easy to transform existing software to exploit default methods as it requires analyzing complex type hierarchies, resolving multiple implementation inheritance issues, reconciling differences between class and interface methods, and analyzing tie-breakers (dispatch precedence) with overriding class methods to preserve type-correctness and confirm semantics preservation. In this paper, we present an efficient, fully-automated, type constraint-based refactoring approach that assists developers in taking advantage of enhanced interfaces for their legacy Java software. The approach features an extensive …
Make A Twitter Bot In Python: Iterative Code Examples, Robin Camille Davis, Mark E. Eaton
Make A Twitter Bot In Python: Iterative Code Examples, Robin Camille Davis, Mark E. Eaton
Publications and Research
A tutorial based upon the LACUNY Emerging Technologies Committee’s “Build Your Own Twitter Bot” day in December 2015, which was billed as a gentle introduction to programming in Python.
Towards Improving Interface Modularity In Legacy Java Software Through Automated Refactoring, Raffi T. Khatchadourian, Olivia Moore, Hidehiko Masuhara
Towards Improving Interface Modularity In Legacy Java Software Through Automated Refactoring, Raffi T. Khatchadourian, Olivia Moore, Hidehiko Masuhara
Publications and Research
The skeletal implementation pattern is a software design pattern that defines an abstract class that provides a partial interface implementation. However, since Java allows only single class inheritance, if implementers decide to extend a skeletal implementation, they will not be allowed to extend any other class. Also, discovering the skeletal implementation may require a global analysis. Java 8 enhanced interfaces alleviate these problems by enabling interfaces to contain (default) method implementations, which implementers inherit. Java classes are then free to extend a different class, and a separate abstract class is no longer needed; developers considering implementing an interface need only …
Towards Improving Interface Modularity In Legacy Java Software Through Automated Refactoring, Raffi T. Khatchadourian, Olivia Moore, Hidehiko Masuhara
Towards Improving Interface Modularity In Legacy Java Software Through Automated Refactoring, Raffi T. Khatchadourian, Olivia Moore, Hidehiko Masuhara
Publications and Research
The skeletal implementation pattern is a software design pattern consisting of defining an abstract class that provides a partial interface implementation. However, since Java allows only single class inheritance, if implementers decide to extend a skeletal implementation, they will not be allowed to extend any other class. Also, discovering the skeletal implementation may require a global analysis. Java 8 enhanced interfaces alleviate these problems by allowing interfaces to contain (default) method implementations, which implementers inherit. Java classes are then free to extend a different class, and a separate abstract class is no longer needed; developers considering implementing an interface need …
Automated Refactoring Of Legacy Java Software To Enumerated Types, Raffi T. Khatchadourian
Automated Refactoring Of Legacy Java Software To Enumerated Types, Raffi T. Khatchadourian
Publications and Research
Modern Java languages introduce several new features that offer significant improvements over older Java technology. In this article we consider the new enum construct, which provides language support for enumerated types. Prior to recent Java languages, programmers needed to employ various patterns (e.g., the weak enum pattern) to compensate for the absence of enumerated types in Java. Unfortunately, these compensation patterns lack several highly-desirable properties of the enum construct, most notably, type safety. We present a novel fully-automated approach for transforming legacy Java code to use the new enumeration construct. This semantics-preserving approach increases type safety, produces code that is …
Detecting Broken Pointcuts Using Structural Commonality And Degree Of Interest, Raffi T. Khatchadourian, Awais Rashd, Hidehiko Masuhara, Takuya Watanabe
Detecting Broken Pointcuts Using Structural Commonality And Degree Of Interest, Raffi T. Khatchadourian, Awais Rashd, Hidehiko Masuhara, Takuya Watanabe
Publications and Research
Pointcut fragility is a well-documented problem in Aspect-Oriented Programming; changes to the base code can lead to join points incorrectly falling in or out of the scope of pointcuts. Deciding which pointcuts have broken due to base-code changes is daunting, especially in large and complex systems. We present an automated approach that recommends pointcuts that are likely to require modification due to a certain base-code change and ones that do not. Our hypothesis is that join points selected by a pointcut exhibit common structural characteristics. Patterns describing such commonalities recommend pointcuts that have potentially broken to the developer. The approach …