Distilling the Real Cost of Production Garbage Collectors

Abridged abstract: despite the long history of garbage collection (GC) and its prevalence in modern programming languages, there is surprisingly little clarity about its true cost. Without understanding their cost, crucial tradeoffs made by garbage collectors (GCs) go unnoticed. This can lead to misguided design constraints and evaluation criteria used by GC researchers and users, hindering the development of high-performance, low-cost GCs. In this paper, we develop a methodology that allows us to empirically estimate the cost of GC for any given set of metrics. By distilling out the explicitly identifiable GC cost, we estimate the intrinsic application execution cost using different GCs. The minimum distilled cost forms a baseline. Subtracting this baseline from the total execution costs, we can then place an empirical lower bound on the absolute costs of different GCs. Using this methodology, we study five production GCs in OpenJDK 17, a high-performance Java runtime. We measure the cost of these collectors, and expose their respective key performance tradeoffs. We find that with a modestly sized heap, production GCs incur substantial overheads across a diverse suite of modern benchmarks, spending at least 7-82% more wall-clock time and 6-92% more CPU cycles relative to the baseline cost. We show that these costs can be masked by concurrency and generous provisioning of memory/compute. In addition, we find that newer low-pause GCs are significantly more expensive than older GCs, and, surprisingly, sometimes deliver worse application latency than stop-the-world GCs. Our findings reaffirm that GC is by no means a solved problem and that a low-cost, low-latency GC remains elusive. We recommend adopting the distillation methodology together with a wider range of cost metrics for future GC evaluations.Comment: Camera-ready versio

Dynamic Assignment of Scoped Memory Regions in the Translation of Java to Real-Time Java

Advances in middleware, operating systems, and popular, general-purpose languages have brought the ideal of reasonably-bound execution time closer to developers who need such assurances for real-time and embedded systems applications. Extensions to the Java libraries and virtual machine have been proposed in a real-time Java standard, which provides for specification of release times, execution costs, and deadlines for a restricted class of threads. To use such features, the programmer is required to use unwieldy code constructs to create region-like areas of storage, associate them with execution scopes, and allocate objects from them. Further, the developer must ensure that they do not violate strict inter-region reference rules. Unfortunately, it is difficult to determine manually how to map object instantiations to execution scopes. Moreover, if ordinary Java code is modified to effect instantiations in scopes, the resulting code is difficult to read, maintain, and reuse. We present a dynamic approach to determining proper placement of objects within scope-bounded regions, and we employ a procedure that utilizes aspect-oriented programming to instrument the original program, realizing the program’s scoped memory concerns in a modular fashion. Using this approach, Java programs can be converted into region-aware Java programs automatically

Teaching and learning introductory programming : a model-based approach

The dissertation identifies and discusses impact of a model-based approach to teaching and learning introductory object-oriented programming both for practitioners and for computer science education research.Learning to program is notoriously difficult. This dissertation investigates ways to teach introductory object-oriented programming at the university level. It focuses on a model-based approach, describes and argues for this approach and investigates several of its aspects. It gives an overview of the research in teaching introductory programming in an objects-first way. The dissertation also investigates ways for university teachers to share and document best practices in teaching introductory object-oriented programming through pedagogical patterns. The dissertation addresses both traditional young full-time students and experienced programmers (although not in object-orientation) participating in part-time education. It examines whether the same success factors for learning programming apply to a model-based approach as to introductory programming courses in general for full-time students and gives a general overview of research in success factors for introductory programming. Some factors are the same, because students‘ math competence is positively correlated with their success. The dissertation examines how experienced programmers link a model-based programming course to their professional practices. The general answer is that the part-time students do not need to have a direct link to their specific work-practice, they expect to create the link themselves; but the teacher must be aware of the conditions facing the part-time students in industry. Furthermore, the dissertation addresses interaction patterns for part-time students learning model-based introductory programming in a net-based environment. A previously prepared solution to an exercise is found to mediate the interaction in three different ways. Design patterns have had a major impact on the quality of object-oriented software. Inspired by this, researchers have suggested pedagogical patterns for sharing best practices in teaching introductory object-oriented programming. It was expected that university teachers‘ knowledge of pedagogical patterns was limited, but this research proved that to be wrong; about half of the teachers know pedagogical patterns. One of the problems this dissertation identifies is the lack of a structuring principle for pedagogical patterns; potential users have problems identifying the correct patterns to apply. An alternative structuring principle based on a constructivist learning theory is suggested and analysed

Supporting feature-level software maintenance

Software maintenance is the process of modifying a software system to fix defects, improve performance, add new functionality, or adapt the system to a new environment. A maintenance task is often initiated by a bug report or a request for new functionality. Bug reports typically describe problems with incorrect behaviors or functionalities. These behaviors or functionalities are known as features. Even in very well-designed systems, the source code that implements features is often not completely modularized. The delocalized nature of features makes maintaining them challenging. Since maintenance tasks are expressed in terms of features, the goal of this dissertation is to support software maintenance at the feature-level. We focus on two tasks in particular: feature location and impact analysis via feature coupling.;Feature location is the process of identifying the source code that implements a feature, and it is an essential first step to any maintenance task. There are many existing techniques for feature location that incorporate various types of analyses such as static, dynamic, and textual. In this dissertation, we recognize the advantages of leveraging several types of analyses and introduce a new approach to feature location based on combining dynamic analysis, textual analysis, and web mining algorithms applied to software. The use of web mining for feature location is a novel contribution, and we show that our new techniques based on web mining are significantly more effective than the current state of the art.;After using feature location to identify a feature\u27s source code, maintenance can be completed on that feature. Impact analysis should then be performed to revalidate the system and determine which other features may have been affected by the modifications. We define three feature coupling metrics that capture the relationship between features based on structural information, textual information, and their combination. Our novel feature coupling metrics can be used for impact analysis to quantify the strength of coupling between pairs of features. We performed three empirical studies on open-source software systems to assess the feature coupling metrics and established three major results. First, there is a moderate to strong statistically significant correlation between feature coupling and faults. Second, feature coupling can be used to correctly determine about half of the other features that would be affected by a change to a given feature. Finally, we found that the metrics align with developers\u27 opinions about pairs of features that are actually coupled

Management of object-oriented action-based distributed programs

Phd ThesisThis thesis addresses the problem of managing the runtime behaviour of distributed programs. The thesis of this work is that management is fundamentally an information processing activity and that the object model, as applied to actionbased distributed systems and database systems, is an appropriate representation of the management information. In this approach, the basic concepts of classes, objects, relationships, and atomic transition systems are used to form object models of distributed programs. Distributed programs are collections of objects whose methods are structured using atomic actions, i.e., atomic transactions. Object models are formed of two submodels, each representing a fundamental aspect of a distributed program. The structural submodel represents a static perspective of the distributed program, and the control submodel represents a dynamic perspective of it. Structural models represent the program's objects, classes and their relationships. Control models represent the program's object states, events, guards and actions-a transition system. Resolution of queries on the distributed program's object model enable the management system to control certain activities of distributed programs. At a different level of abstraction, the distributed program can be seen as a reactive system where two subprograms interact: an application program and a management program; they interact only through sensors and actuators. Sensors are methods used to probe an object's state and actuators are methods used to change an object's state. The management program is capable to prod the application program into action by activating sensors and actuators available at the interface of the application program. Actions are determined by management policies that are encoded in the management program. This way of structuring the management system encourages a clear modularization of application and management distributed programs, allowing better separation of concerns. Managemental concerns can be dealt with by the management program, functional concerns can be assigned to the application program. The object-oriented action-based computational model adopted by the management system provides a natural framework for the implementation of faulttolerant distributed programs. Object orientation provides modularity and extensibility through object encapsulation. Atomic actions guarantee the consistency of the objects of the distributed program despite concurrency and failures. Replication of the distributed program provides increased fault-tolerance by guaranteeing the consistent progress of the computation, even though some of the replicated objects can fail. A prototype management system based on the management theory proposed above has been implemented atop Arjuna; an object-oriented programming system which provides a set of tools for constructing fault-tolerant distributed programs. The management system is composed of two subsystems: Stabilis, a management system for structural information, and Vigil, a management system for control information. Example applications have been implemented to illustrate the use of the management system and gather experimental evidence to give support to the thesis.CNPq (Consellho Nacional de Desenvolvimento Cientifico e Tecnol6gico, Brazil): BROADCAST (Basic Research On Advanced Distributed Computing: from Algorithms to SysTems)

Senior Computer Science Students’ Task and Revised Task Interpretation While Engaged in Programming Endeavor

Developing a computer program is not an easy task. Studies reported that a large number of computer science students decided to change their major due to the extreme challenge in learning programming. Fortunately, studies also reported that learning various self-regulation strategies may help students to continue studying computer science. This study is interested in assessing students’ self-regulation, in specific their task understanding and its revision during programming endeavors. Task understanding is specifically selected because it affects the entire programming endeavor. In this qualitative case study, two female and two male senior computer science students were voluntarily recruited as research participants. They were asked to think aloud while answering five programming problems. Before solving the problem, they had to explain their understanding of the task and after that answer some questions related to their problem-solving process. The participants’ problem-solving process were video and audio-recorded, transcribed, and analyzed. This study found that the participants’ were capable of tailoring their problem-solving approach to the task types, including when understanding the tasks. Given enough time, the participants can understand the problem correctly. When the task is complicated, the participants will gradually update their understanding during the problem-solving endeavor. Some situations may have prevented the participants from understanding the task correctly, including overconfidence, being overwhelmed, utilizing an inappropriate presentation technique, or drawing knowledge from irrelevant experience. Last, the participants tended to be inexperienced in managing unfavorable outcomes

A Framework for Model-Driven Development of Mobile Applications with Context Support

Model-driven development (MDD) of software systems has been a serious trend in different application domains over the last 15 years. While technologies, platforms, and architectural paradigms have changed several times since model-driven development processes were first introduced, their applicability and usefulness are discussed every time a new technological trend appears. Looking at the rapid market penetration of smartphones, software engineers are curious about how model-driven development technologies can deal with this novel and emergent domain of software engineering (SE). Indeed, software engineering of mobile applications provides many challenges that model-driven development can address. Model-driven development uses a platform independent model as a crucial artifact. Such a model usually follows a domain-specific modeling language and separates the business concerns from the technical concerns. These platform-independent models can be reused for generating native program code for several mobile software platforms. However, a major drawback of model-driven development is that infrastructure developers must provide a fairly sophisticated model-driven development infrastructure before mobile application developers can create mobile applications in a model-driven way. Hence, the first part of this thesis deals with designing a model-driven development infrastructure for mobile applications. We will follow a rigorous design process comprising a domain analysis, the design of a domain-specific modeling language, and the development of the corresponding model editors. To ensure that the code generators produce high-quality application code and the resulting mobile applications follow a proper architectural design, we will analyze several representative reference applications beforehand. Thus, the reader will get an insight into both the features of mobile applications and the steps that are required to design and implement a model-driven development infrastructure. As a result of the domain analysis and the analysis of the reference applications, we identified context-awareness as a further important feature of mobile applications. Current software engineering tools do not sufficiently support designing and implementing of context-aware mobile applications. Although these tools (e.g., middleware approaches) support the definition and the collection of contextual information, the adaptation of the mobile application must often be implemented by hand at a low abstraction level by the mobile application developers. Thus, the second part of this thesis demonstrates how context-aware mobile applications can be designed more easily by using a model-driven development approach. Techniques such as model transformation and model interpretation are used to adapt mobile applications to different contexts at design time or runtime. Moreover, model analysis and model-based simulation help mobile application developers to evaluate a designed mobile application (i.e., app model) prior to its generation and deployment with respected to certain contexts. We demonstrate the usefulness and applicability of the model-driven development infrastructure we developed by seven case examples. These showcases demonstrate the designing of mobile applications in different domains. We demonstrate the scalability of our model-driven development infrastructure with several performance tests, focusing on the generation time of mobile applications, as well as their runtime performance. Moreover, the usability was successfully evaluated during several hands-on training sessions by real mobile application developers with different skill levels

Compiler and Runtime Optimizations for Fine-Grained Distributed Shared Memory Systems

Bal, H.E. [Promotor

On The Human Factors Impact of Polyglot Programming on Programmer Productivity

Polyglot programming is a common practice in modern software development. This practice is often considered useful to create software by allowing developers to use whichever language they consider most well suited for the different parts of their software. Despite this ubiquity of polyglot programming there is no empirical research into how this practice affects software developers and their productivity. In this dissertation, after reviewing the state of the art in programming language and linguistic research pertaining to the topic, this matter is investigated by way of two empirical studies with 109 and 171 participants solving programming tasks. Based on the findings, the design of a data management library, a common use-case for polyglot programming, is proposed broadly and then applied specifically to the language Quorum as a case study. The review of previous studies finds that there is a pattern of productivity gain that can be explained by the occurrence of type annotations in programming, which gives insight into how programmers comprehend code. Study results show that there is a significant improvement of programmer productivity when programmers are using polyglot programming in an embedded context (partial eta squared = 0.039) and that less experienced programmers do better in a group with more frequent, but less severe, switches, while more experienced developers perform better with less frequent but more complete switches between languages. A study on language switches on a file level shows that file level programming language switching has a clear negative impact on programmer productivity (partial eta squared = 0.059) and is most likely caused by the increased occurrence of errors when switching