MOTIVATION: Many genomes are sequenced by a collaboration of several centers, and then each center produces an assembly using their own assembly software. The collaborators then pick the draft assembly that they judge to be the best and the information contained in the other assemblies is usually not used. METHODS: We have developed a technique that we call assembly reconciliation that can merge draft genome assemblies. It takes one draft assembly, detects apparent errors, and, when possible, patches the problem areas using pieces from alternative draft assemblies. It also closes gaps in places where one of the alternative assemblies has spanned the gap correctly. RESULTS: Using the Assembly Reconciliation technique, we produced reconciled assemblies of six Drosophila species in collaboration with Agencourt Bioscience and The J. Craig Venter Institute. These assemblies are now the official (CAF1) assemblies used for analysis. We also produced a reconciled assembly of Rhesus Macaque genome, and this assembly is available from our website http://www.genome.umd.edu. AVAILABILITY: The reconciliation software is available for download from http://www.genome.umd.edu/software.htm

The ASE conference series is rooted in the 1981 Knowledge-Based Software Assistant (KBSA) document [1] and the ensuing US Air Force Rome Labs research program. KBSA addressed automated tool support for the entire software lifecycle, including project management, requirements, specifications, code generation, and evolution. A core goal of KBSA and ASE is the automated generation of code from requirement-level specifications, which promises benefits in three directions: (1) High Assurance - generation of correct code, as well as certification information as a by-product, (2) Productivity through automation, and (3) High Performance through machine application of best-practice design knowledge. Benefits should also include lowering of the cost of lifecycle ownership, due to automated treatment of evolving requirements. This talk lays out a more modern unifying framework for automated software development that is consistent with these goals [2]. Recent progress in automated support for algorithm design and system development is highlighted

This roadmap describes ways that researchers in four areas---specification languages, program generation, correctness by construction, and programming languages---might help further the goal of verified software. It also describes what advances the "verified software" grand challenge might anticipate or demand from work in these areas. That is, the roadmap is intended to help foster collaboration between the grand challenge and these research areas.A common goal for research in these areas is to establish language designs and tool architectures that would allow multiple annotations and tools to be used on a single program. In the long term, researchers could try to unify these annotations and integrate such tools.

SUMMARY: The easiest way to gain a quick overall understanding of genomic data is with a visual display that allows the user to view information about an entire genome or chromosome at once. We have constructed GenomePlot, a Perl/Tk script with a series of modules that allow us to display many types of information simultaneously. Menu options allow the user to zoom to the desired view of the data and to print or save the image to a file to produce publication quality illustrations. AVAILABILITY: The program is available on request. A license is required for commercial use.

This paper presents a mechanizable framework for specifying, developing, and reasoning about complex systems. The framework combines features from algebraic specifications, abstract state machines, and refinement calculus, all couched in a categorical setting. In particular, we show how to extend algebraic specifications to evolving specifications (especs) in such a way that composition and refinement operations extend to capture the dynamics of evolving, adaptive, and self-adaptive software development, while remaining efficiently computable. The framework is partially implemented in the Epoxi system.

Planware is a domain-specific generator of high-performance scheduling software, currently being developed at the Kestrel Institute. Architecturally, Planware is an extension of the Specware system with domain-independent and domain-dependent parts. The domain-independent part includes a general algorithm design facility (including mechanisms to synthesize global-search and constraint propagation algorithms), as well as support for theorem-proving and witness finding. The domain-dependent part includes scheduling domain knowledge and architecture representations, and other domain-specific refinement knowledge that relates the scheduling domain to general algorithm design and data type refinement. Using Planware, the user interactively specifies a problem and then the system automatically generates a formal specification and refines it.

The Kestrel Interactive Development System (KIDS) provides automated support for the development of correct and efficient programs from formal specifications. The system has components for performing algorithm design, deductive inference, program simplification, partial evaluation, finite differencing optimizations, data type refinement, compilation, and other development operations. Although their application is interactive, all of the KIDS operations are automatic except the algorithm design tactics which require some interaction at present. Dozens of programs have been derived using the system and we believe that KIDS could be developed to the point that it becomes economical to use for routine programming. To illustrate the use of KIDS, we trace the derivation of an algorithm for enumerating solutions to the k-queens problem. The initial algorithm that KIDS designs takes about sixty minutes on a SUN-4/110 to find all 92 solutions to the 8-queens problem instance. The final optimize...

We present a summary of the CHI project conducted at Kestrel Institute through mid-1984. The objective of this project was to perform research on knowledge-based software environments. Toward this end, key portions of a prototype environment, called CHI, were built that established the feasibility of this approach. One result of this research was the development of a wide-spectrum language that could be used to express all stages of the program development process in the system. Another result was that the prototype compiler was used to synthesize itself from very-high-level description of itself. In this way the system was bootstrapped. We describe the overall nature of the work done on this project, give highlights of implemented prototypes, and describe the implications that this work suggests for the future of software engineering. In addition to this historical perspective, current research projects at Kestrel Institute as well as commercial applications of the technology at Reasoning Systems are briefly surveyed.

Branch and bound procedures are the most efficient known means for solving many NP-hard problems A special class of branch and bound procedures called relaxation-gutded procedures ig presented.While for some branch and bound procedures a worst-case complexity bound is known, the average case complexity is usually unknown, despite the fact that it may g~ve more useful information about the performance of the algorithm.A random process which generates labeled trees is introduced as a model of the kind of trees that a relaxatlon-gutded procedure generates over random instances of a problem Results concerning the expected time and space complexity of searching these random trees are derived with respect to several search strategies.The best-bound search strategy is shown to be optimal in both time and space.These results are illustrated by data from random traveling salesman instances Evidence ~s presented that the asymmetric traveling salesman problem can be solved exactly in time O(n31n(n)) on the average.

Production rule schemas are given which hold the basic information necessary for coding recursive loops and branches in LISP. Information from the user concerning the desired program is used to instantiate the schemas to yield production rules, and then these rules generate executable code in a strictly syntactic fashion. Emphasis is placed on decomposing the synthesis problem into a hierarchy of tasks which can each be solved by application of a schema. The method is demonstrated by showing how programs can be synthesized from examples of their input-output behaviors.