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The alarms of the program-semantic defect-detection report based on static analysis include defects and false positives. The repair of defects and the elimination of false positives are time-consuming and laborious, and new defects may be introduced in the process. To solve these problems, the safe constraints interval of related variables and methods are proposed for the semantic defects in the program, and proposes a functionally equivalent no-side-effect program-semantic defect repair and false-positive elimination strategy based on the test-equivalence theory. This paper realizes the automatic repair of the typical semantic defects of Java programs and the automatic elimination of false positives by adding safe constraint patches. After the repair, the program functions are equivalent and the status of each program point is within the safety range, so that the functions before and after the defect repair are consistent, and the functions and semantics before and after the false positives are eliminated. We have evaluated our approach by repairing 5 projects, our results show that the repair strategy does not require manual confirmation of alarms, automated repair of the program effectively, shortened the repair time greatly, and ensured the correctness of the program after the repair.

Automated program repair is an effective way to ensure software quality and improve software development efficiency. At present, there are many methods and tools of automated program reapir in real world, but most of them have low repair accuracy, resulting in a large number of incorrect patches in the generated patches. To solve this problem, we propose a patch quality evaluation method based on semantic distance, which measures the semantic distance of patches by using features of interval distance, output coverage, and path matching. For each evaluation feature, we give a quantitative formula to obtain a specific distance value and use the distance to calculate the recommended patch value to measure the quality of the patch. Our quality evaluation method evaluated 279 patches from previous program repair tools, including Nopol, DynaMoth, ACS, jGenProg, and CapGen. This quality evaluation method successfully arranged the correct patches before the plausible but incorrect patches, and it recommended the higher-ranked patches to users first. On this basis, we compared our evaluation method with the existing evaluation methods and judged the evaluation ability of each feature. We showed that our proposed patch quality evaluation method can improve the repair accuracy of repair tools.

With the rapid growth of the Internet-of-Things (IoT), security issues for the IoT are becoming increasingly serious. Memory leaks are a common and harmful software defect for IoT programs running on resource-limited devices. Static analysis is an effective method for memory leak detection, however, because the existing methods cannot fully describe the memory state of IoT programs at run time, false positives and false negatives frequently occur. To improve the precision of memory leak detection, we propose an abstract memory model SeqMM to describe sequential storage structures. SeqMM differs from other abstract memory models in its ability to handle both points-to analysis and numerical analysis of pointers, which contributes to eliminating false positives in defect detection. In addition, based on the analysis of the sequential storage structure, we introduce the analysis of its operations in C programs, including transfer operations and predicate operations. Moreover, we present a memory leak detection algorithm by determining the state of the program points related to allocated memory blocks. The experimental results of five real projects indicate that the false positive rates of DTSC_SeqMM, Klocwork12 and DTSC_RSTVL are 29.0%, 15.0% and 40.6% respectively, and the corresponding false negative rates are 0%, 22.7% and 13.6%.

Recently, software, especially CPS and Internet of Things (IoT), increasingly have high requirements for quality, while program defects exist inevitably duo to the high complexity. Program defect repair faces serious challenges in that such repairs require considerable manpower, and the existing automatic repair approaches have difficulty generating correct patches efficiently. This paper proposes an automatic method for repairing semantic defects in Java programs based on restricted sets which refer to the interval domains of related variables that can trigger program semantic defects. Our work introduces a repair mechanism symmetrically combining defect patterns and repair templates. First, the program semantic defects are summarized into defect patterns according to their grammar and semantic features. A repair template for each type of defect pattern is predefined based on a restricted-set. Then, for each specific defect, a patch statement is automatically synthesized according to the repair template, and the detected defect information is reported by the static detection tool (DTSJava). Next, the patch location is determined by the def-use chain of defect-related variables. Finally, we evaluate the patches generated by our method using DTSJava. We implemented the method in the defect automatic repair prototype tool DTSFix to verify the effect of repairing the semantic defects detected by DTSJava in 6 Java open-source projects. The experimental results showed that 109 of 129 program semantic defects were repaired.

In the management of capital assets owned by major enterprise, there exist some information disconnection including no information about equipment working conditions when bidding for them, no information about installation and debugging when the equipment was overhauled. Therefore, the paper proposes to establish a equipment management system based on BOM tree and RFID. Giving asset devices lifetime identity through RFID coding, which will be utilized throughout all procedures including planning and designing, bidding and procurement, construction building and so on. The paper develops some apps, such as engineering construction, warehouse management to realize data circulation throughout the equipment. Besides, with data analysis, the paper carries on equipment unit cost allocation and collection and supplier comprehensive evaluation, to guide equipment procurement and management, strengthen the whole process monitoring of asset operation status, improve the management level of asset lean management, and optimize the asset operation strategy of the company.

In the present work, a direct bond between glass and silicon with optical contact was formed by 515 nm picosecond laser controlled by the galvanometer scanning system. A crack-free welding effect without edge breakage and residues was obtained with breaking strength as high as 122 MPa. New crystalline phase (SiO2) was produced and silicon and oxygen have a spatial distribution gradient in the welding area analyzed by XRD and EDS, respectively, revealing that mixing and inter-diffusion of substances have occurred during laser irradiation. The transmission of near infrared light in the welding area is significantly increased compared with the non-welding area analyzed by inverted microscope. A confocal laser scanning microscope was used to observe the morphology and width of welds, which variation trend of axial focal positions is consistent with the teardrop structure produced by nonlinear absorption effect. Scanning speeds and laser repetition frequencies also affect the width and morphology of the weld.