Our work applies the dataflow algorithm to an area outside its traditional scope: functional languages. Our approach relies on a monadic intermediate language that provides low-level, imperative features like computed jumps and explicit allocations, while at the same time supporting high-level, functional-language features like case discrimination and partial application. We prototyped our work in Haskell using the HOOPL library and this dissertation shows numerous examples demonstrating its use. We prove the efficacy of our approach by giving a novel description of the uncurrying optimization in terms of the dataflow algorithm, as well as a complete implementation of the optimization using HOOPL.

Game engine programming involves a great number of software components, many of which perform similar tasks; for example, memory allocation must take place in the renderer as well as in the creation routines while other tasks such as error logging must take place everywhere. One area of all games which is critical to the success of the game is that of game balance and tuning. These balancing initiatives cut across all areas of code from the player and AI to the mission manager. In computer science, we’ve come to call these types of concerns “cross cutting”. Aspect oriented programming was developed, in part, to solve the problems of cross cutting: employing “advice” which can be incorporated across different pieces of functionality. Yet, despite the prevalence of a solution, very little work has been done to bring cross cutting to game engine programming. Additionally, the discipline involves a heavy amount of code rewriting and reuse while simultaneously relying on many common design patterns that are copied from one project to another. In the case of game balance, the code may be wildly different across two different games despite the fact that similar tasks are being done. These two problems are exacerbated by the fact that almost every game engine has its own custom DSL (domain specific language) unique to that situation. If a DSL could showcase the areas of cross cutting concerns while highlighting the ability to capture design patterns that can be used across games, significant productivity savings could be achieved while simultaneously creating a common thread for discussion of shared problems within the domain. This dissertation sought to do exactly that- create a metalanguage called GAMESPECT which supports multiple styles of DSLs while bringing aspect-oriented programming into the DSL’s to make them DSAL (domain specific aspect languages). The example cross cutting concern was game balance and tuning since it’s so pervasive and important to gaming. We have created GAMESPECT as a language and a composition framework which can assist engine developers and game designers in balancing their games, forming one central place for game balancing concerns even while these concerns may cross different languages and locations inside the source code. Generality was measured by showcasing the composition specifications in multiple contexts and languages. In addition to evaluating generality and performance metrics, effectiveness was be measured. Specifically, comparisons were made between a balancing initiative when performed with GAMESPECT vs a traditional methodology. In doing so, this work shows a clear advantage to using a Metalanguage such as GAMESPECT for this task. In general, a line of code reduction of 9-40% per task was achieved with negligible effects to performance. The use of a metalanguage in Unreal Engine 4 is a starting point to further discussions concerning other game engines. In addition, this work has implications beyond video game programming. The work described highlights benefits which might be achieved in other disciplines where design pattern implementations and cross-cutting concern usage is high; the real time simulation field and the field of Windows GUI programming are two examples of future domains.

This thesis presents Lighthouse, an experimental branch of the Haskell-based House operating system which integrates Li et al.'s Lightweight Concurrency framework. First and foremost, it improves House's viability as a "real operating system" by providing a new extensible scheduler framework which makes it easy to experiment with different scheduling policies. In particular, Lighthouse extends Concurrent Haskell with thread priority and implements a priority-based scheduler which significantly improves system responsiveness when compared with GHC's normal round-robin scheduler. Even while doing this, it improves on House's claim of being "written in Haskell" by moving a whole subsystem out of the complex C-based runtime system and into Haskell itself. In addition, Lighthouse also includes an alternate, simpler implementation of Lightweight Concurrency which takes advantage of House's unique setting (running directly on uniprocessor x86 hardware). This experience sheds light on areas that need further attention before the system can truly be viable---primarily interactions between blackholing and interrupt handling. In particular, this thesis uncovers a potential case of self-deadlock and suggests potential solutions. Finally, this work offers further insight into the viability of using high-level languages such as Haskell for systems programming. Although laziness and blackholing present unique problems, many parts of the system are still much easier to express in Haskell than traditional languages such as C.

Purely functional languages--with static type systems and dynamic memory management using garbage collection--are a known tool for helping programmers to reduce the number of memory errors in programs. By using such languages, we can establish correctness properties relating to memory-safety through our choice of implementation language alone. Unfortunately, the language characteristics that make purely functional languages safe also make them more difficult to apply in a low-level domain like operating systems construction. The low-level features that support the kinds of hardware manipulations required by operating systems are not typically available in memory-safe languages with garbage collection. Those that are provided may have the ability to violate memory- and type-safety, destroying the guarantees that motivate using such languages in the first place. This work demonstrates that it is possible to bridge the gap between the requirements of operating system implementations and the features of purely functional languages without sacrificing type- and memory-safety. In particular, we show that this can be achieved by isolating the potentially unsafe memory operations required by operating systems in an abstraction layer that is well integrated with a purely functional language. The salient features of this abstraction layer are that the operations it exposes are memory-safe and yet sufficiently expressive to support the implementation of realistic operating systems. The abstraction layer enables systems programmers to perform all of the low-level tasks necessary in an OS implementation, such as manipulating an MMU and executing user-level programs, without compromising the static memory-safety guarantees of programming in a purely functional language. A specific contribution of this work is an analysis of memory-safety for the abstraction layer by formalizing a meaning for memory-safety in the presence of virtual-memory using a novel application of noninterference security policies. In addition, we evaluate the expressiveness of the abstraction layer by implementing the L4 microkernel API, which has a flexible set of virtual memory management operations.

Due to the complex nature of parallel programming, it is difficult to diagnose and solve performance related problems. Knowledge of program behavior is obtained experimentally, with repeated runs of a slightly modified version of the application or the same code in different environments. In these circumstances, comparative performance analysis can provide meaningful insights into the subtle effects of system and code changes on parallel program behavior by highlighting the difference in performance results across executions. I have designed and implemented modules which extend the PPerfDB performance tool to allow access to existing performance data generated by several commonly used tracing tools. Access occurs from within the experiment management framework provided by PPerfDB for the identification of system parameters, the representation of multiple sets of execution data, and the formulation of data queries. Furthermore, I have designed and implemented an additional module that will generate new data using dynamic instrumentation under the control of PPerfDB. This was done to enable the creation of novel experiments for performance hypothesis testing and to ultimately automate the diagnostic and tuning process. As data from such diverse sources has very different representations, various techniques to allow comparisons are presented. I have generalized the definition of the Performance Difference operator, which automatically detects divergence in multiple data sets, and I have defined an Overlay operation to provide uniform access to both dynamically generated and tracefile based data. The use and application of these new operations along with an indication of some of the issues involved in the creation of a fully automatic comparative profilier is presented via several case studies performed on an IBM SP2 using different versions of an MPI application.

Generalized algebraic data types (GADTs) are a type system extension to algebraic data types that allows the type of an algebraic data value to vary with its shape. The GADT type system allows programmers to express detailed program properties as types (for example, that a function should return a list of the same length as its input), and a general-purpose type checker will automatically check those properties at compile time. Type inference for the GADT type system and the properties of the type system are both currently areas of active research. In this dissertation, I attack both problems simultaneously by exploiting the symbiosis between type system research and type inference research. Deficiencies of GADT type inference algorithms motivate research on specific aspects of the type system, and discoveries about the type system bring in new insights that lead to improved GADT type inference algorithms. The technical contributions of this dissertation are therefore twofold: in addition to new GADT type system properties (such as the prevalence of pointwise type information flow in GADT patterns, a generalized notion of existential types, and the effects of enforcing the GADT branch reachability requirement), I will also present a new GADT type inference algorithm that is significantly more powerful than existing algorithms. These contributions should help programmers use the GADT type system more effectively, and they should also enable language implementers to provide better support for the GADT type system.

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We often want a compiler to generate executable code that runs as fast as possible. One consideration toward this goal is to keep values in fast registers to limit the number of slower memory accesses that occur. When there are not enough physical registers available for use, values are ``spilled'' to the runtime stack. The need for spills is discovered during register allocation wherein values in use are mapped to physical registers. One factor in the efficacy of register allocation is the number of values in use at one time (register collisions). Register collision is affected by compiler optimizations that take place before register allocation. Though the main purpose of compiler optimizations is to make the overall code better and faster, some optimizations can actually increase register collisions. This may force the register allocation process to spill. This thesis studies the effects of different compiler optimizations on register collisions.

Data for empirical studies of software engineering can be difficult to obtain. Extrapolations from small controlled experiments to large development environments are tenuous and observation tends to change the behavior of the subjects. In this thesis we propose the use of data gathered from software repositories in observational studies of software engineering. We present tools we have developed to extract data from CVS repositories and the SourceForge Research Archive. We use these tools to gather data from 9,999 Open Source projects. By analyzing these data we are able to provide insights into the structure of Open Source projects. For example, we find that the vast majority of the projects studied have never had more than three contributors and that the vast majority of authors studied have never contributed to more than one project. However, there are projects that have had up to 120 contributors in a single year and authors who have contributed to more than 20 projects which raises interesting questions about team dynamics in the Open Source community. We also use these data to empirically test the belief that productivity is constant in terms of lines of code per programmer per year regardless of the programming language used. We find that yearly programmer productivity is not constant across programming languages, but rather that developers using higher level languages tend to write fewer lines of code per year than those using lower level languages.