Input-output examples are a simple and accessible way of describing program behaviour. Program synthesis from input-output examples has the potential of extending the range of computational tasks achievable by end-users who have no programming knowledge, but can articulate their desired computations by describing input-output behaviour. In this paper, we present Escher, a generic and efficient ...

This paper presents a dynamic technique for predicting the e ect that a \location" of a program will have on the program's computational behavior. The technique is based on the three necessary and su cient conditions for software failure to occur: (1) a fault must be executed, (2) the fault must adversely a ect the data state, and (3) the adverse e ect in a data state must a ect program output....

The feasibility of inverting imperative computations using logic programming technology is informally explored. Program inversion is the process of determining the possible input values that will produce a given output for a program. The relational semantics of imperative computations treats programs as logical relations over the observable environment, which is usually taken to be the state of...

A novel ultra-high compliance, low power, very accurate and high output impedance current output stage (COS) with extremely high output current drive capability is proposed in this paper. The principle of operation of this unique structure is discussed, its most important formulas are derived and its outstanding performance is verified by HSPICE simulation in TSMC 0.18µm CMOS, BSIM3, and Level4...

We study the problem of efficiently predicting a correct program from a large set of programs induced from few input-output examples in Programming-byExample (PBE) systems. This is an important problem for making PBE systems usable so that users do not need to provide too many examples to learn the desired program. We first formalize the two classes of sharing that occurs in version-space algeb...

Programming by Example (PBE) targets at automatically inferring a computer program for accomplishing a certain task from sample input and output. In this paper, we propose a deep neural networks (DNN) based PBE model called Neural Programming by Example (NPBE), which can learn from input-output strings and induce programs that solve the string manipulation problems. Our NPBE model has four neur...

Practically all programming languages used in software engineering allow to split a program into several modules. For fully declarative and nonmonotonic logic programming languages, however, the modular structure of programs is hard to realise, since the output of an entire program cannot in general be composed from the output of its component programs in a direct manner. In this paper, we cons...

This paper explores new ways of doing input to and output from TEX. These new ways bypass our current habits, and provide fresh opportunities. Usually, TEX is run as a batch program. But when run as a daemon, TEX can be part of an interactive program. Daemons often that run forever, or at least for a long time. Hence the title of this paper. Usually, parsing and transformation of the input data...

BACKGROUND Typically, randomization software should allow users to exert control over the different aspects of randomization including block design, provision of unique identifiers and control over the format and type of program output. While some of these characteristics have been addressed by available software, none of them have all of these capabilities integrated into one package. The main...

In [1] a recursive warrant semantics for Defeasible Logic Programming extended with levels of possibilistic uncertainty for defeasible rules was introduced. The resulting argumentation framework, called RP-DeLP, is based on a general notion of collective (non-binary) conflict among arguments allowing to ensure direct and indirect consistency properties with respect to the strict knowledge. An o...