Modular Synthesis of Sketches Using Models

One problem with the constraint-based approaches to synthesis that have become popular over the last few years is that they only scale to relatively small routines, on the order of a few dozen lines of code. This paper presents a mechanism for modular reasoning that allows us to break larger synthesis problems into small manageable pieces. The approach builds on previous work in the verification community of using high-level specifications and partially interpreted functions (we call them models) in place of more complex pieces of code in order to make the analysis modular. The main contribution of this paper is to show how to combine these techniques with the counterexample guided synthesis approaches used to efficiently solve synthesis problems. Specifically, we show two new algorithms; one to efficiently synthesize functions that use models, and another one to synthesize functions while ensuring that the behavior of the resulting function will be in the set of behaviors allowed by the model. We have implemented our approach on top of the open-source Sketch synthesis system, and we demonstrate its effectiveness on several Sketch benchmark problems.National Science Foundation (U.S.) (Grant NSF-1116362)National Science Foundation (U.S.) (Grant NSF-1139056)United States. Dept. of Energy (Grant DE-SC0005372

A double-cartridge SPE-HPLC-UV method for monitoring a humanfriendly anticancer in plasma: Ketoglutarate levels in metastatic carcinoma

We present a fully validated HPLC-UV assay for the concurrent quantification of ketoglutaric acid and hydroxymethylfurfural, a ‘targeted therapy’ composition inducing a synergistic metabolic distress to the tumoral microenvironment. The analytes were exclusively extracted from the biomatrix via a combined-cartridge solid phase extraction assembly. The method is based on derivatizing both analytes with 2-nitrophenylhydrazine directed to their chemically divergent but commonly occurring carbonyl function. The reaction is kinetically catalyzed. Acidifying the buffered eluate post-extraction is critical for the feasibility of the reaction. The chromatographic separation is successfully accomplished on octyl columns in less than 15 min at 330 nm using 0.028% TFAA-methanol-acetonitrile (58:32:10, v/v) as eluant. The assay was validated using the concept of accuracy profile. The selectivity of the method was demonstrated in pre- and post-dosed patients from a pilot study. Quality control samples were prepared and analyzed during the routine use of the method. Life samples collected from patients enduring oesophageal and breast carcinoma with lung metastases were monitored for ketoglutarate in a trial to correlate its plasma levels with the malignancy

Chromatographic analysis of sympathomimetic amines after fluorescence derivatization with benzocoumarin-3-carboxylic acid chloride

This work reports the use of a new fluorescent reagents in derivatization procedures prior toTLC and HPLC separations of sympathomimetic amines. Experiments were performed to optimize the reaction conditions /time, temperature, reagent amount, choice and amount of catalyst)

Method development and validation for the analysis of a new anti-cancer infusion solution via HPLC

A fast and simple HPLC method has been developed and validated for the quantification of a completely new anti-cancer drug during the manufacturing process. The combination of four compounds including alpha-ketoglutaric acid, hydroxymethylfurfural, N-acetyl-L-methionine and N-acetyl-L-selenomethionine, administered intravenously, is still in test phase but has already shown promising results in cancer therapy. HPLC separation was achieved on an RP-18 column with a gradient system. However, the highly different concentrations of the compounds required a variation in the detection wavelength within one run. In order to produce a chromatogram where peaks were comparable on a similar range scale, detection at absorption maxima for the two most concentrated components was avoided. After optimization of the gradient program it was possible to detect all four substances within 14 min in spite of their strongly different chemical structure. The method developed was validated for accuracy, repeatability, reproducibility and robustness in relation to temperature and pH of buffer. Linearity as well as the limit of detection and quantification were determined. This HPLC method was found to be precise, accurate and reproducible and can be easily used for in-line process control during the manufacture of the anti-tumour infusion solution

Evaluating the reliability of analytical results using a probability criterion: a Bayesian perspective

Methods validation is mandatory in order to assess the fitness of purpose of the developed analytical method. Of core importance at the end of the validation is the evaluation of the reliability of the individual results that will be generated during the routine application of the method. Regulatory guidelines provide a general framework to assess the validity of a method, but none address the issue of results reliability. In this study, a Bayesian approach is proposed to address this concern. Results reliability is defined here as “the probability of an analytical method to provide analytical results within predefined acceptance limits around their reference or conventional true concentration values over a defined concentration range and under given environmental and operating conditions.” By providing the minimum reliability probability needed for the subsequent routine application of the method, as well as specifications or acceptance limits , the proposed Bayesian approach provides the effective probability of obtaining reliable future analytical results over the whole concentration range investigated. This is summarized in a single graph: the reliability profile. This Bayesian reliability profile is also compared to two frequentist approaches, the first one derived from the work of Dewé et al. [Dewé W., Govaerts B., Boulanger B., Rozet E., Chiap P., Hubert Ph., Chemometr. Intell. Lab. Syst. 85 (2007) 262-268] and the second proposed by Govaerts et al. [B. Govaerts, W. Dewé, M. Maumy, B. Boulanger, Qual. Reliab. Engng. Int. 24 (2008) 667-680]. Furthermore, to illustrate the applicability of the Bayesian reliability profile, this approach is also applied here to a bioanalytical method dedicated to the determination of ketoglutaric acid (KG) and hydroxymethylfurfural (HMF) in human plasma by SPE-HPLC-UV

Multi-solver Support in Symbolic Execution

Abstract. One of the main challenges of dynamic symbolic execution— an automated program analysis technique which has been successfully employed to test a variety of software—is constraint solving. A key decision in the design of a symbolic execution tool is the choice of a constraint solver. While different solvers have different strengths, for most queries, it is not possible to tell in advance which solver will perform better. In this paper, we argue that symbolic execution tools can, and should, make use of multiple constraint solvers. These solvers can be run competitively in parallel, with the symbolic execution engine using the result from the best-performing solver. We present empirical data obtained by running the symbolic execution engine KLEE on a set of real programs, and use it to highlight several important characteristics of the constraint solving queries generated during symbolic execution. In particular, we show the importance of constraint caching and counterexample values on the (relative) performance of KLEE configured to use different SMT solvers. We have implemented multi-solver support in KLEE, using the metaSMT framework, and explored how different state-of-the-art solvers compare on a large set of constraint-solving queries. We also report on our ongoing experience building a parallel portfolio solver in KLEE.