Using formal methods to support testing

Formal methods and testing are two important approaches that assist in the development of high quality software. While traditionally these approaches have been seen as rivals, in recent years a new consensus has developed in which they are seen as complementary. This article reviews the state of the art regarding ways in which the presence of a formal specification can be used to assist testing

FORTEST: Formal methods and testing

Formal methods have traditionally been used for specification and development of software. However there are potential benefits for the testing stage as well. The panel session associated with this paper explores the usefulness or otherwise of formal methods in various contexts for improving software testing. A number of different possibilities for the use of formal methods are explored and questions raised. The contributors are all members of the UK FORTEST Network on formal methods and testing. Although the authors generally believe that formal methods are useful in aiding the testing process, this paper is intended to provoke discussion. Dissenters are encouraged to put their views to the panel or individually to the authors

Design Criteria to Architect Continuous Experimentation for Self-Driving Vehicles

The software powering today's vehicles surpasses mechatronics as the dominating engineering challenge due to its fast evolving and innovative nature. In addition, the software and system architecture for upcoming vehicles with automated driving functionality is already processing ~750MB/s - corresponding to over 180 simultaneous 4K-video streams from popular video-on-demand services. Hence, self-driving cars will run so much software to resemble "small data centers on wheels" rather than just transportation vehicles. Continuous Integration, Deployment, and Experimentation have been successfully adopted for software-only products as enabling methodology for feedback-based software development. For example, a popular search engine conducts ~250 experiments each day to improve the software based on its users' behavior. This work investigates design criteria for the software architecture and the corresponding software development and deployment process for complex cyber-physical systems, with the goal of enabling Continuous Experimentation as a way to achieve continuous software evolution. Our research involved reviewing related literature on the topic to extract relevant design requirements. The study is concluded by describing the software development and deployment process and software architecture adopted by our self-driving vehicle laboratory, both based on the extracted criteria.Comment: Copyright 2017 IEEE. Paper submitted and accepted at the 2017 IEEE International Conference on Software Architecture. 8 pages, 2 figures. Published in IEEE Xplore Digital Library, URL: http://ieeexplore.ieee.org/abstract/document/7930218

A survey on software testability

Context: Software testability is the degree to which a software system or a unit under test supports its own testing. To predict and improve software testability, a large number of techniques and metrics have been proposed by both practitioners and researchers in the last several decades. Reviewing and getting an overview of the entire state-of-the-art and state-of-the-practice in this area is often challenging for a practitioner or a new researcher. Objective: Our objective is to summarize the body of knowledge in this area and to benefit the readers (both practitioners and researchers) in preparing, measuring and improving software testability. Method: To address the above need, the authors conducted a survey in the form of a systematic literature mapping (classification) to find out what we as a community know about this topic. After compiling an initial pool of 303 papers, and applying a set of inclusion/exclusion criteria, our final pool included 208 papers. Results: The area of software testability has been comprehensively studied by researchers and practitioners. Approaches for measurement of testability and improvement of testability are the most-frequently addressed in the papers. The two most often mentioned factors affecting testability are observability and controllability. Common ways to improve testability are testability transformation, improving observability, adding assertions, and improving controllability. Conclusion: This paper serves for both researchers and practitioners as an "index" to the vast body of knowledge in the area of testability. The results could help practitioners measure and improve software testability in their projects

A method for tailoring the information content of a software process model

The framework is defined for a general method for selecting a necessary and sufficient subset of a general software life cycle's information products, to support new software development process. Procedures for characterizing problem domains in general and mapping to a tailored set of life cycle processes and products is presented. An overview of the method is shown using the following steps: (1) During the problem concept definition phase, perform standardized interviews and dialogs between developer and user, and between user and customer; (2) Generate a quality needs profile of the software to be developed, based on information gathered in step 1; (3) Translate the quality needs profile into a profile of quality criteria that must be met by the software to satisfy the quality needs; (4) Map the quality criteria to set of accepted processes and products for achieving each criterion; (5) Select the information products which match or support the accepted processes and product of step 4; and (6) Select the design methodology which produces the information products selected in step 5

Design for testability in hardware-software systems

Clearly, in today's complex systems, hardware and software approaches to DFT must work together to achieve a successful overall solution. The authors investigate existing and new concepts that may lead to a single design for test strategy in the futur

Silicon compilation

Silicon compilation is a term used for many different purposes. In this paper we define silicon compilation as a mapping from some higher level description into layout. We define the basic issues in structural and behavioral silicon compilation and some possible solutions to those issues. Finally, we define the concept of an intelligent silicon compiler in which the compiler evaluates the quality of the generated design and attempts to improve it if it is not satisfactory

Benchmarking for high-level synthesis

This paper discusses issues in benchmarking for synthesis, and suggests techniques for the comparison of benchmark descriptions, the synthesis tools used, as well as the synthesized designs finally generated. We propose a classification scheme for the assumptions made for the comparison of different synthesis tools, and present an Assumptions Chart that can be used to visualize different benchmarks, tools and synthesis results. We illustrate application of this Assumptions Chart using synthesis experiments that were conducted on some sample High-Level Synthesis Workshop bench-marks