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Git is a widely used version control system that is powerful but complicated. Its complexity may not be an inevitable consequence of its power but rather evidence of flaws in its design. To explore this hypothesis, we analyzed the design of Git using a theory that identifies concepts, purposes, and misfits. Some well-known difficulties with Git are described, and explained as misfits in which underlying concepts fail to meet their intended purpose. Based on this analysis, we designed a reworking of Git (called Gitless) that attempts to remedy these flaws. To correlate misfits with issues reported by users, we conducted a study of Stack Overflow questions. And to determine whether users experienced fewer complications using Gitless in place of Git, we conducted a small user study. Results suggest our approach can be profitable in identifying, analyzing, and fixing design problems., SUTD-MIT International Design Centre (IDC)

High-level scripting languages have become tremendously popular for development of dynamic Web applications. Many programmers appreciate the productivity benefits of automatic storage management, freedom from verbose type annotations, and so on. While it is often possible to improve performance substantially by rewriting an application in C or a similar language, very few programmers bother to do so, because of the consequences for human development effort. This paper describes a compiler that makes it possible to have most of the best of both worlds, coding Web applications in a high-level language but compiling to native code with performance comparable to handwritten C code. The source language is Ur/Web, a domain-specific, purely functional, statically typed language for the Web. Through a coordinated suite of relatively straightforward program analyses and algebraic optimizations, we transform Ur/Web programs into almost-idiomatic C code, with no garbage collection, little unnecessary memory allocation for intermediate values, etc. Our compiler is in production use for commercial Web sites supporting thousands of users, and microbenchmarks demonstrate very competitive performance versus mainstream tools.

A daunting challenge faced by program performance autotuning is input sensitivity, where the best autotuned configuration may vary with different input sets. This paper presents a novel two-level input learning algorithm to tackle the challenge for an important class of autotuning problems, algorithmic autotuning. The new approach uses a two-level input clustering method to automatically refine input grouping, feature selection, and classifier construction. Its design solves a series of open issues that are particularly essential to algorithmic autotuning, including the enormous optimization space, complex influence by deep input features, high cost in feature extraction, and variable accuracy of algorithmic choices. Experimental results show that the new solution yields up to a 3x speedup over using a single configuration for all inputs, and a 34x speedup over a traditional one-level method for addressing input sensitivity in program optimizations., United States. Dept. of Energy (Award DE-SC0005288), United States. Dept. of Energy (Award DE-SC0008923), United States. Dept. of Energy (Early Career Award), National Science Foundation (U.S.) (Grant 1464216), National Science Foundation (U.S.) (Grant 1320796), National Science Foundation (U.S.) (CAREER Award)

Many verifications of realistic software systems are monolithic, in the sense that they define single global invariants over complete system state. More modular proof techniques promise to support reuse of component proofs and even reduce the effort required to verify one concrete system, just as modularity simplifies standard software development. This paper reports on one case study applying modular proof techniques in the Coq proof assistant. To our knowledge, it is the first modular verification certifying a system that combines infrastructure with an application of interest to end users. We assume a nonblocking API for managing TCP networking streams, and on top of that we work our way up to certifying multithreaded, database-backed Web applications. Key verified components include a cooperative threading library and an implementation of a domain-specific language for XML processing. We have deployed our case-study system on mobile robots, where it interfaces with off-the-shelf components for sensing, actuation, and control., National Science Foundation (U.S.) (NSF grant CCF-1253229), United States. Defense Advanced Research Projects Agency (DARPA, agreement number FA8750-12-2-0293)

The World Wide Web has evolved gradually from a document delivery platform to an architecture for distributed programming. This largely unplanned evolution is apparent in the set of interconnected languages and protocols that any Web application must manage. This paper presents Ur/Web, a domain-specific, statically typed functional programming language with a much simpler model for programming modern Web applications. Ur/Web's model is unified, where programs in a single programming language are compiled to other "Web standards" languages as needed; modular, supporting novel kinds of encapsulation of Web-specific state; and exposes simple concurrency, where programmers can reason about distributed, multithreaded applications via a mix of transactions and cooperative preemption. We give a tutorial introduction to the main features of Ur/Web, formalize the basic programming model with operational semantics, and discuss the language implementation and the production Web applications that use it., National Science Foundation (U.S.) (Grant CCF-1217501)

We present Bolt, a novel system for escaping from infinite and long-running loops. Directed by a user, Bolt can attach to a running process and determine if the program is executing an infinite loop. If so, Bolt can deploy multiple strategies to escape the loop, restore the responsiveness of the program, and enable the program to deliver useful output. Bolt operates on stripped x86 and x64 binaries, dynamically attaches and detaches to and from the program as needed, and dynamically detects loops and creates program state checkpoints to enable exploration of different escape strategies. Bolt can detect and escape from loops in off-the-shelf software, without available source code, and with no overhead in standard production use. Copyright © 2012 ACM., NSF (Grant CCF-0811397), NSF (Grant CCF-0905244), NSF (IIS-0835652), NSF (Grant CCF-1036241), DARPA (Grant FA8650-11-C-7192), DARPA (Grant FA8750-12-2-0110), United States Department of Energy (Grant DE-SC0005288)

Shadow memory is used by dynamic program analysis tools to store metadata for tracking properties of application memory. The efficiency of mapping between application memory and shadow memory has substantial impact on the overall performance of such analysis tools. However, traditional memory mapping schemes that work well on 32-bit architectures cannot easily port to 64-bit architectures due to the much larger 64-bit address space. This paper presents EMS64, an efficient memory shadowing scheme for 64-bit architectures. By taking advantage of application reference locality and unused regions in the 64-bit address space, EMS64 provides a fast and flexible memory mapping scheme without relying on any underlying platform features or requiring any specific shadow memory size. Our experiments show that EMS64 is able to reduce the runtime shadow memory translation overhead to 81% on average, which almost halves the overhead of the fastest 64-bit shadow memory system we are aware of.