A Comparative Study of Code Query Technologies

When analyzing software systems we are faced with the challenge of how to implement a particular analysis for different programming languages. A solution for this problem is to write a single analysis using a code query language abstracting from the specificities of languages being analyzed. Over the past ten years many code query technologies have been developed, based on different formalisms. Each technology comes with its own query language and set of features. To determine the state of the art of code querying we compare the languages and tools for seven code query technologies: Grok, Rscript, JRelCal, SemmleCode, JGraLab, CrocoPat and JTransformer. The specification of a package stability metric is used as a running example to compare the languages. The comparison involves twelve criteria, some of which are concerned with properties of the query language (paradigm, types, parametrization, polymorphism, modularity, and libraries), and some of which are concerned with the tool itself (output formats, interactive interface, API support, interchange formats, extraction support, and licensing). We contextualize the criteria in two usage scenarios: interactive and tool integration. We conclude that there is no particularly weak or dominant tool. As important improvement points, we identify the lack of library mechanisms, interchange formats, and possibilities for integration with source code extraction components

Performance and Health Monitoring and Analysis of Hive Scales Portal Web Application

Honey bee health and colony collapse disorder (CCD), a term coined in 2006, have been drawing global attention as bees are dying at a rapid rate. The University of Maryland reported that beekeepers across the US lost more than 40 percent of their honey bee colonies during the year spanning April 2014 to April 2015[1]. With seventy out of the top 100 human food crops, which supply about 90 percent of the world’s nutrition, being pollinated by bees [4], this puts our food supply at serious risk! Formed from a grant from the US Department of Agriculture, the Bee Informed Partnership (BIP) is a collaborative effort to address the declining honey bee population. A major part of this effort is being led by GVSU through the Hive Scales Portal web application. This application aggregates and stores data, collected from hive scales around the world, for researchers and scientists with the intent of identifying patterns that lead to best practices for caring for bees. As the quantity of contributing hives scales increase, the hive scale portal will need to scale proportionally. Knowing when or how much to scale is a guessing game without the proper visibility. The purpose of this project is to analyze the application and ensure it can scale. The key piece of this analysis is to integrate the necessary tools to ensure site health and performance visibility is available for continued monitoring

Board Games: A Perfect Match for Reading Comprehension

Analog board games greatly benefit students’ development and overall well-being. Board games offer opportunities for early learning, help boost language skills, sharpen students’ ability to focus, teach the value of teamwork, and soothe anxiety. Integrating board games with literacy skills allows students to assimilate information and develop into lifelong learners. Without solid literacy skills, the future is bleak for most students. To compound the problem, a trend today is to replace traditional board games as an educational tool with digital alternatives. This trend has seen a downward correlation with students having significant reading deficiencies in their reading comprehension in grades three through five. This thesis will examine how utilizing analog board games in elementary classrooms can improve reading comprehension skills in students. To better understand how analog board games an effective as an instructional tool in the classroom, research will be conducted through a series of research questions: 1. How has the increased use of technology in the classroom affected students’ learning outcomes? 2. What is the difference between an analogy and a digital board game? 3. What are the environmental aspects that aid in employing analog board games in the learning process of the classroom? 4. What effects do board games have on the learning process in the classroom? 5. What are the opposing concerns about using analog board games in the classroom? After completing this research, a literate review was conducted in addition to visual and content analyses. A graphical solution will be created as an analog board game to aid in developing reading comprehension skills in elementary school students, grades three through five. The creation of the deliverable will provide the stakeholders at all levels, individual, institutional, and societal, with a concrete example of a reading comprehension game that can aid in developing literacy skills in students

Interactive Query Language for Code Comprehension

Code comprehension is a fundamental task for software development. Every bug fix, maintenance or new feature development requires the whole understanding of the affectedcode. There exist a number of code comprehension tools but most of them has a limitedfeature set and they are binded with a fixed (usually) graphical user interface. This putlimitations for their use. In this thesis we will define a flexible but safe query language to execute the most fundamental comprehension queries against a large code base. We will investigate how much this language could be language agnostic and how to support specificlanguage features. I will implement a prototype tool to prove the concept using the opensource CodeCompass code comprehension platform. In this prototype i mainly target C and C++ languages

A Secured Cloud System based on Log Analysis

Now-a-days, enterprises’ acceptance over the Cloud is increasing but businesses are now finding issues related to security. Everyday, users store a large amount of data in the Cloud and user input may be malicious. Therefore, security has become the critical feature in the applications stored in the Cloud. Though there are many existing systems which provide us different encryption algorithms and security methods, there is still a possibility of attacks to applications and increasing data modifications. The idea behind this project is to find attacks and protect the applications stored in the Cloud using log analysis. The proposed solution detects the SQL injection attack, which is supposed to be the most critical security risk of vulnerable applications. The goal of this research is to detect the SQL injection attacks for an application stored in the Cloud by analyzing the logs. To achieve this, the proposed system automates the intrusion detection process for an application by performing log analysis. Log Analysis is performed by combining the implementation of two different methodologies called learn and detect methodology and pattern recognition system. The accuracy of SQL injections detected on log data is dependent on the order in which these two methodologies are applied. The outcome after applying these two methodologies results in information which helps a security analyst to understand and know the root cause of every attack that is detected on an application

Alternative Phrases Theoretical Analysis and Practical Application

Institute for Communicating and Collaborative Systems"All right, but apart from the sanitation, the medicine, education, wine, public order, irrigation, roads, the fresh-water system and public health, what have the Romans ever done for us?" (Monty Python, The Life of Brian) Alternative phrases identify selected elements from a set and subject them to particular scrutiny with respect to the sentence's predicate. For instance, in the above example, sanitation, medicine, etc. are all identified as elements in the set of things the Romans have done for us" that should not be included in the response to the question. They are alternative responses to the desired ones. Alternative phrases come in a variety of constructions and perform a variety of tasks: excluding elements (apart from), expressing preference for particular elements (especially), and simply identifying representative examples (such as). Not a great deal of work has been done on alternative phrases in general. Hearst (1992) used a pattern-matching analysis of certain alternative phrases to learn hyponyms from unannotated corpora. Also, a few examples from a subset of alternative phrases, called exceptive phrases, have been studied, most recently, by von Fintel (1993) and Hoeksema (1995). But not all constructions are amenable to pattern-matching techniques, and the work on exceptive phrases focuses on some very specific semantic points. The focus of this thesis is to present a general program for analyzing a wide variety of alternative phrases including their presuppositional and anaphoric properties. I perform my analyses in Combinatory Categorial Grammar, a lexicalized formalism. The semantic aspects of the analysis benefit greatly from the concept of alternative sets, sets of propositions that differ in one or more argument (Karttunen and Peters, 1979; Rooth, 1985, 1992; Prevost and Steedman, 1994; Steedman, 2000a). In addition, elegant solutions are made possible by separating the semantics into assertion and presupposition (Stalnaker, 1974; Karttunen and Peters, 1979; Stone and Doran, 1997; Stone and Webber, 1998; Webber et al., 1999b)| with each performing quite different tasks. My second goal is to demonstrate the practicality and importance of this analysis to real systems. Although it is relevant to many practical applications, I will focus primarily on natural language information retrieval (NLIR) as a case study. In such a domain, queries like Where can I find other web browsers than Netscape for download? and Where can I find shoes made by Bufialino, such as the Bushwackers? are often observed. I review several techniques for NLIR and demonstrate that implementations of those techniques perform poorly on such queries. I show that understanding alternative phrases can enable simple techniques which greatly improve precision. To bridge the gap between these goals, I present Grok, a modular natural language system. Several general NLP issues necessary to support my linguistic analysis are discussed: anaphora resolution, processing of presuppositions, interface to knowledge representation, and the creation of a wide-coverage lexicon. Special attention is paid to the lexicon, which is a combination of a hand-built and an acquired lexicon