Technical Requirements Analysis and Control Systems (TRACS) Initial Operating Capability (IOC) documentation

The Technical Requirements Analysis and Control Systems (TRACS) software package is described. TRACS offers supplemental tools for the analysis, control, and interchange of project requirements. This package provides the fundamental capability to analyze and control requirements, serves a focal point for project requirements, and integrates a system that supports efficient and consistent operations. TRACS uses relational data base technology (ORACLE) in a stand alone or in a distributed environment that can be used to coordinate the activities required to support a project through its entire life cycle. TRACS uses a set of keyword and mouse driven screens (HyperCard) which imposes adherence through a controlled user interface. The user interface provides an interactive capability to interrogate the data base and to display or print project requirement information. TRACS has a limited report capability, but can be extended with PostScript conventions

Software Engineering Laboratory (SEL) database organization and user's guide

The organization of the Software Engineering Laboratory (SEL) database is presented. Included are definitions and detailed descriptions of the database tables and views, the SEL data, and system support data. The mapping from the SEL and system support data to the base tables is described. In addition, techniques for accessing the database, through the Database Access Manager for the SEL (DAMSEL) system and via the ORACLE structured query language (SQL), are discussed

Automating test oracles generation

Software systems play a more and more important role in our everyday life. Many relevant human activities nowadays involve the execution of a piece of software. Software has to be reliable to deliver the expected behavior, and assessing the quality of software is of primary importance to reduce the risk of runtime errors. Software testing is the most common quality assessing technique for software. Testing consists in running the system under test on a finite set of inputs, and checking the correctness of the results. Thoroughly testing a software system is expensive and requires a lot of manual work to define test inputs (stimuli used to trigger different software behaviors) and test oracles (the decision procedures checking the correctness of the results). Researchers have addressed the cost of testing by proposing techniques to automatically generate test inputs. While the generation of test inputs is well supported, there is no way to generate cost-effective test oracles: Existing techniques to produce test oracles are either too expensive to be applied in practice, or produce oracles with limited effectiveness that can only identify blatant failures like system crashes. Our intuition is that cost-effective test oracles can be generated using information produced as a byproduct of the normal development activities. The goal of this thesis is to create test oracles that can detect faults leading to semantic and non-trivial errors, and that are characterized by a reasonable generation cost. We propose two ways to generate test oracles, one derives oracles from the software redundancy and the other from the natural language comments that document the source code of software systems. We present a technique that exploits redundant sequences of method calls encoding the software redundancy to automatically generate test oracles named CCOracles. We describe how CCOracles are automatically generated, deployed, and executed. We prove the effectiveness of CCOracles by measuring their fault-finding effectiveness when combined with both automatically generated and hand-written test inputs. We also present Toradocu, a technique that derives executable specifications from Javadoc comments of Java constructors and methods. From such specifications, Toradocu generates test oracles that are then deployed into existing test suites to assess the outputs of given test inputs. We empirically evaluate Toradocu, showing that Toradocu accurately translates Javadoc comments into procedure specifications. We also show that Toradocu oracles effectively identify semantic faults in the SUT. CCOracles and Toradocu oracles stem from independent information sources and are complementary in the sense that they check different aspects of the system undertest

Development of the Web-Based Admissions and Management System for IELP

The academic program The Intensive English Language Program (IELP) at the University of New Orleans (UNO) offers one of the most effective and diverse language programs in the United States. This thesis is to report the development of the Webbased database application that manages admissions, students learning progress, and course offering of this program. The system development followed a simplified Unified Process for Software Development (UP) using the Unified Modeling Language (UML) models such as the requirement catch model – use cases, the analysis model – activity diagrams, and the design model –communication diagrams. The new system has met and exceeded all the business requirements and has been operating to support the further growth of the IELP at UNO. Significant attention has been given to information security; multiple techniques have been applied in addition to the security measures enforced in the hosting environment – the University Computing Center

Private-Library-Oriented Code Generation with Large Language Models

Large language models (LLMs), such as Codex and GPT-4, have recently showcased their remarkable code generation abilities, facilitating a significant boost in coding efficiency. This paper will delve into utilizing LLMs for code generation in private libraries, as they are widely employed in everyday programming. Despite their remarkable capabilities, generating such private APIs poses a formidable conundrum for LLMs, as they inherently lack exposure to these private libraries during pre-training. To address this challenge, we propose a novel framework that emulates the process of programmers writing private code. This framework comprises two modules: APIFinder first retrieves potentially useful APIs from API documentation; and APICoder then leverages these retrieved APIs to generate private code. Specifically, APIFinder employs vector retrieval techniques and allows user involvement in the retrieval process. For APICoder, it can directly utilize off-the-shelf code generation models. To further cultivate explicit proficiency in invoking APIs from prompts, we continuously pre-train a reinforced version of APICoder, named CodeGenAPI. Our goal is to train the above two modules on vast public libraries, enabling generalization to private ones. Meanwhile, we create four private library benchmarks, including TorchDataEval, TorchDataComplexEval, MonkeyEval, and BeatNumEval, and meticulously handcraft test cases for each benchmark to support comprehensive evaluations. Numerous experiments on the four benchmarks consistently affirm the effectiveness of our approach. Furthermore, deeper analysis is also conducted to glean additional insights

Automated metamorphic testing on the analyses of feature models

Copyright © 2010 Elsevier B.V. All rights reserved.Context: A feature model (FM) represents the valid combinations of features in a domain. The automated extraction of information from FMs is a complex task that involves numerous analysis operations, techniques and tools. Current testing methods in this context are manual and rely on the ability of the tester to decide whether the output of an analysis is correct. However, this is acknowledged to be time-consuming, error-prone and in most cases infeasible due to the combinatorial complexity of the analyses, this is known as the oracle problem.Objective: In this paper, we propose using metamorphic testing to automate the generation of test data for feature model analysis tools overcoming the oracle problem. An automated test data generator is presented and evaluated to show the feasibility of our approach.Method: We present a set of relations (so-called metamorphic relations) between input FMs and the set of products they represent. Based on these relations and given a FM and its known set of products, a set of neighbouring FMs together with their corresponding set of products are automatically generated and used for testing multiple analyses. Complex FMs representing millions of products can be efficiently created by applying this process iteratively.Results: Our evaluation results using mutation testing and real faults reveal that most faults can be automatically detected within a few seconds. Two defects were found in FaMa and another two in SPLOT, two real tools for the automated analysis of feature models. Also, we show how our generator outperforms a related manual suite for the automated analysis of feature models and how this suite can be used to guide the automated generation of test cases obtaining important gains in efficiency.Conclusion: Our results show that the application of metamorphic testing in the domain of automated analysis of feature models is efficient and effective in detecting most faults in a few seconds without the need for a human oracle.This work has been partially supported by the European Commission(FEDER)and Spanish Government under CICYT project SETI(TIN2009-07366)and the Andalusian Government project ISABEL(TIC-2533)

How can non-technical end users effectively test their spreadsheets?

Purpose – An alarming number of spreadsheet faults have been reported in the literature, indicating that effective and easy-to-apply spreadsheet testing techniques are not available for “non-technical,” end-user programmers. The purpose of this paper is to alleviate the problem by introducing a metamorphic testing (MT) technique for spreadsheets. Design/methodology/approach – The paper discussed four common challenges encountered by end-user programmers when testing a spreadsheet. The MT technique was then discussed and how it could be used to solve the common challenges was explained. An experiment involving several “real-world” spreadsheets was performed to determine the viability and effectiveness of MT. Findings – The experiment confirmed that MT is highly effective in spreadsheet fault detection, and yet MT is a general technique that can be easily used by end-user programmers to test a large variety of spreadsheet applications. Originality/value – The paper provides a detailed discussion of some common challenges of spreadsheet testing encountered by end-user programmers. To the best of the authors knowledge, the paper is the first that includes an empirical study of how effective MT is in spreadsheet fault detection from an end-user programmer's perspective