LCLint: a tool for using specifications to check code
SIGSOFT '94 Proceedings of the 2nd ACM SIGSOFT symposium on Foundations of software engineering
Static detection of dynamic memory errors
PLDI '96 Proceedings of the ACM SIGPLAN 1996 conference on Programming language design and implementation
Dynamically Discovering Likely Program Invariants to Support Program Evolution
IEEE Transactions on Software Engineering - Special issue on 1999 international conference on software engineering
The Science of Programming
A Discipline of Programming
Program Development in Java: Abstraction, Specification, and Object-Oriented Design
Program Development in Java: Abstraction, Specification, and Object-Oriented Design
Invariant inference for static checking:
Proceedings of the 10th ACM SIGSOFT symposium on Foundations of software engineering
Dynamically discovering likely program invariants
Dynamically discovering likely program invariants
Dynamically inferring temporal properties
Proceedings of the 5th ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering
Automatically Inferring Temporal Properties for Program Evolution
ISSRE '04 Proceedings of the 15th International Symposium on Software Reliability Engineering
Perracotta: mining temporal API rules from imperfect traces
Proceedings of the 28th international conference on Software engineering
The spec# programming system: an overview
CASSIS'04 Proceedings of the 2004 international conference on Construction and Analysis of Safe, Secure, and Interoperable Smart Devices
DySy: dynamic symbolic execution for invariant inference
Proceedings of the 30th international conference on Software engineering
| Hi-index | 0.00 |
One goal of introductory software engineering courses is to motivate and instill good software engineering habits. Unfortunately, practical constraints on typical courses often lead to student experiences that are antithetical to that goal: instead of working in large teams and dealing with changing requirements and maintaining programs over many years, courses generally involve students working alone or in small teams with short projects that end the first time the program works correctly on some selected input. Small projects tend to reinforce poor software engineering practices. Since the programs are small enough to manage cognitively in ad hoc ways, effort spent more precisely documenting assumptions seems wasteful. It is infeasible to carry out full industrial software development within the context of a typical university course. However, it is possible to simulate some aspects of safety critical software engineering in an introductory software engineering course. This paper describes an approach that focuses on thinking about and precisely documenting invariants, and checking invariants using lightweight analysis tools. We describe how assignments were designed to emphasize the importance of invariants and to incorporate program analysis tools with typical software engineering material and report on results from an experiment measuring students understanding of program invariants.