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Programming by example (PBE) is an emerging programming paradigm that automatically synthesizes programs specified by user-provided input-output examples. Despite the convenience for end-users, implementing PBE tools often requires strong expertise in programming language and synthesis algorithms. Such a level of knowledge is uncommon among software developers. It greatly limits the broad adoption of PBE by the industry. To facilitate the adoption of PBE techniques, we propose a PBE framework called Bee, which leverages an "entity-action" model based on relational tables to ease PBE development for a wide but restrained range of domains. Implementing PBE tools with Bee only requires adapting domain-specific data entities and user actions to tables, with no need to design a domain-specific language or an efficient synthesis algorithm. The synthesis algorithm of Bee exploits bidirectional searching and constraint-solving techniques to address the challenge of value computation nested in table transformation. We evaluated Bee's effectiveness on 64 PBE tasks from three different domains and usability with a human study of 12 participants. Evaluation results show that Bee is easier to learn and use than the state-of-the-art PBE framework, and the bidirectional algorithm achieves comparable performance to domain-specifically optimized synthesizers., Comment: Accepted by ACM Transactions on Software Engineering and Methodology

WebView is a UI widget that helps integrate web applications into the native context of Android apps. It provides powerful mechanisms for bi-directional interactions between the native-end (Java) and the web-end (JavaScript) of an Android app. However, these interaction mechanisms are complicated and have induced various types of bugs. To mitigate the problem, various techniques have been proposed to detect WebView-induced bugs via dynamic analysis, which heavily relies on executing tests to explore WebView behaviors. Unfortunately, these techniques either require manual effort or adopt random test generation approaches, which are not able to effectively explore diverse WebView behaviors. In this paper, we study the problem of test generation for WebViews in Android apps. Effective test generation for WebViews requires identifying the essential program properties to be covered by the generated tests. To this end, we propose WebView-specific properties to characterize WebView behaviors, and devise a cross-language dynamic analysis method to identify these properties. We develop $ω$Test, a test generation technique that searches for event sequences covering the identified WebView-specific properties. An evaluation on 74 real-world open-/closed-source Android apps shows that $ω$Test can cover diverse WebView behaviors and detect WebView-induced bugs effectively. $ω$Test detected 36 previously-unknown bugs. From the 22 bugs that we have reported to the app developers, 13 bugs were confirmed, 9 of which were fixed., Accepted by the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2023)

A scoping review to identify methodological challenges when using routinely collected healthcare data for research.

Additional file 1.

Aminoglycosides (AGs) are a class of broad spectrum antibiotics that have bactericidal activity against some aerobic gram-positive and gram-negative organisms. AGs have been extensively employed in animal husbandry for the treatment of bacterial infections or growth promotion. Many countries have issued strict maximum residue levels (MRLs) for AGs in many animal-origin foods. Analysis of AGs is quite challenging due to their physicochemical properties. The lack of any notable chromophores or fluorophores makes direct detection using ultraviolet (UV) or fluorescence (FLR) spectroscopy unfeasible. Therefore, AGs must be derivatized before they can be analyzed by UV or FLR detection techniques. However, the sensitivity of such derivatization methods is relatively low. Methods based on chromatographic analysis coupled with tandem mass spectrometric detection are emerging as the most common way of identification and quantification. The retention of AGs on reversed-phase column is poor due to the presence of various amino and hydroxyl groups in their structures. Therefore, ion-pair chromatography has reportedly been used to improve the retention of AGs. However, electrospray ionization-mass spectrometric detection was hampered by using an ion pairing reagent due to the suppression of ionization. In this study, a method based on mixed-mode ion exchange liquid chromatography-tandem mass spectrometry was developed for the determination of ten AGs residues (streptomycin, dihydrostreptomycin, hygromycin B, kanamycin, amikacin, tobramycin, apramycin, spectinomycin, neomycin, and gentamycin) in eggs. The main factors governing the method, such as the type of chromatographic column used, the type and proportion of the mobile phase used, mass spectroscopy parameters, type and volume of the extraction solvent used, pH, and the type of solid phase extraction (SPE) column, were investigated during sample pretreatment and instrument analysis. The residues of AGs in the test samples were extracted by ultrasonication with 10 mmol/L ammonium acetate buffer solution (comprising 0.4 mmol/L EDTA and 50 g/L trichloroacetic acid). After adjusting the pH, the AG residues in the sample were purified and enriched using a PRiME HLB SPE column. The target analytes were separated on a SIELC Obelisc R column (150 mm×2.1mm, 5 μm), the column temperature being 40 ℃, the flow rate being 0.3 mL/min, and the injection volume being 5 μL. Gradient elution was carried out with acetonitrile and 1.0%(v/v) formic acid aqueous solution (including 1 mmol/L ammonium formate) as the mobile phases. The detection was performed by electrospray ionization-tandem mass spectrometry (ESI-MS/MS) in multiple reaction monitoring (MRM) mode. The retention times and ionic ratios were used for qualitative analysis, and the peak areas were used for quantitative analysis by the external standard method. Good correlation coefficients exceeding 0.99 were observed for all the AGs in the concentration range of 5-200 μg/L under the optimum conditions. The limits of detection (LODs, S/N ≥ 3) and limits of quantification (LOQs, S/N≥10) for the ten AGs were 2-5 μg/kg and 5-10 μg/kg, respectively. The recoveries ranged from 68.1% to 111.3% (n=6) at three levels (LODs, 20 μg/kg, and 100 μg/kg) in spiked blank egg samples, and the relative standard deviations were 1.2%-12.3%. The matrix effects of the analytes were between 0.3% and 94.3% after purification on the PRiME HLB column. The applicability of the method was validated by analyzing egg samples purchased from local markets. Overall, the method of mixed-mode ion exchange liquid chromatography-tandem mass spectrometry has proven to be a reliable and powerful technique for the simultaneous quantification and confirmation of ten AGs without using an ion pair reagent. Moreover, the clean-up step only required a kind of PRiME HLB sorbent cartridge. The relative parameter data of established method were consistent with GB/T 27404-2008. With simple pretreatment, rapid determination and high sensitivity, the method can be used in the determination of AGs in eggs.

XML configuration files are widely used in Android to define an app's user interface and essential runtime information such as system permissions. As Android evolves, it might introduce functional changes in the configuration environment, thus causing compatibility issues that manifest as inconsistent app behaviors at different API levels. Such issues can often induce software crashes and inconsistent look-and-feel when running at specific Android versions. Existing works incur plenty of false positive and false negative issue-detection rules by conducting trivial data-flow analysis while failing to model the XML tree hierarchies of the Android configuration files. Besides, little is known about how the changes in an Android framework can induce such compatibility issues. To bridge such gaps, we conducted a systematic study by analyzing 196 real-world issues collected from 43 popular apps. We identified common patterns of Android framework code changes that induce such configuration compatibility issues. Based on the findings, we propose \textsc{ConfDroid} that can automatically extract rules for detecting configuration compatibility issues. The intuition is to perform symbolic execution based on a model learned from the common code change patterns. Experiment results show that ConfDroid can successfully extract 282 valid issue-detection rules with a precision of 91.9%. Among them, 65 extracted rules can manifest issues that cannot be detected by the rules of state-of-the-art baselines. More importantly, 11 out of them have led to the detection of 107 reproducible configuration compatibility issues that the baselines cannot detect in 30 out of 316 real-world Android apps.