The authors introduce a new programming language concept, called typestate, which is a refinement of the concept of type. Whereas the type of a data object determines the set of operations over permitted on the object, typestate determines the subset of these operations which is permitted in a particular context. Typestate tracking is a program analysis technique which enhances program reliability by detecting at compile-time syntactically legal but semantically undefined execution sequences. These include reading a variable before it has been initialized and dereferencing a pointer after the dynamic object has been deallocated. The authors define typestate, give examples of its application, and show how typestate checking may be embedded into a compiler. They discuss the consequences of typestate checking for software reliability and software structure, and summarize their experience in using a high-level language incorporating typestate checking.

Typestate: A programming language concept for enhancing software reliability

Keywords: Knowledge representation ; semantic data models ; conceptual modelling Reference Record created on 2005-06-20, modified on 2016-08-08

On Conceptual Modelling

data type declarations appear in typed programming languages like Ada, Alphard, CLU and ML. This form of declaration binds a list of identifiers to a type with associated operations, a composite "value" we call a data algebra. We use a second-order typed lambda calculus SOL to show how data algebras may be given types, passed as parameters, and returned as results of function calls. In the process, we discuss the semantics of abstract data type declarations and review a connection between typed programming languages and constructive logic.

/pdf/abstract-types-have-existential-types-4hjnazoxno.pdf

Abstract types have existential types

Smart Energy Technologies in Everyday Life

This roadmap describes ways that researchers in four areas---specification languages, program generation, correctness by construction, and programming languages---might help further the goal of verified software. It also describes what advances the "verified software" grand challenge might anticipate or demand from work in these areas. That is, the roadmap is intended to help foster collaboration between the grand challenge and these research areas.A common goal for research in these areas is to establish language designs and tool architectures that would allow multiple annotations and tools to be used on a single program. In the long term, researchers could try to unify these annotations and integrate such tools.

/pdf/roadmap-for-enhanced-languages-and-methods-to-aid-4zq77dhvkj.pdf

Roadmap for enhanced languages and methods to aid verification

The major problems of modern software involve finding effective techniques and tools for organizing and maintaining large, complex programs. The key concept in modern programming for controlling complexity is abstraction, that is, selective emphasis on detail. This monograph discusses how the Ada programming language provides ways to support and exploit such abstraction techniques.

https://link.springer.com/content/pdf/10.1007%2F978-1-4612-5517-8_2.pdf

Introduction to the First Edition

Since the initial publication of Studies, some parts of the Ada1 language have been changed in response to the ANSI standardization process. The second edition of Studies has been updated to conform to the latest available Ada manual [Department of Defense 82].2 All of our references to the Ada manual come from this document (see page 36).

Introduction to the Second Edition

to the Second Edition.- to the First Edition.- I The Impact of Abstraction Concerns on Modern Programming Languages.- 1. The Impact of Abstraction Concerns on Modern Programming Languages.- 1.1 Issues of Modern Software.- 1.2 Historical Review of Abstraction Techniques.- 1.2.1 Early Abstraction Techniques.- 1.2.2 Extensible Languages.- 1.2.3 Structured Programming.- 1.2.4 Program Verification.- 1.2.5 Abstract Data Types.- 1.2.6 Interactions Between Abstraction and Specification Techniques.- 1.3 Abstraction Facilities in Modern Programming Languages.- 1.3.1 The New Ideas.- 1.3.2 Language Support for Abstract Data Types.- 1.3.3 Generic Definitions.- 1.4 Practical Realizations.- 1.4.1 A Small Example Program.- 1.4.2 Pascal.- 1.4.3 Ada.- 1.5 Status and Potential.- 1.5.1 How New Ideas Affect Programming.- 1.5.2 Limitations of Current Abstraction Techniques.- 1.5.3 Further Reading.- II Programming In Ada: Examples.- 1. Introduction to Example Programs.- 2. An Implementation of Queues.- 2.1 Description.- 2.2 Implementation.- 2.3 Program Text.- 2.4 Discussion.- 2.4.1 Use of Limited Private Types.- 2.4.2 Initialization and Finalization.- 2.4.3 Passing Discriminants to Tasks.- 2.4.4 Remove as a Procedure.- 3. A Simple Graph Package Providing an Iterator.- 3.1 Description.- 3.2 Specifications.- 3.3 Program Text.- 3.4 Discussion.- 3.4.1 The Algorithm.- 3.4.2 Information Hiding.- 3.4.3 In/In Out Parameters.- 3.4.4 Using the Iterator.- 3.4.5 Iterators Versus Generic Procedures.- 3.4.6 Separate Compilation.- 4. A Console Driver for a PDP-11.- 4.1 Description.- 4.2 Implementation.- 4.3 Program Text.- 4.4 Discussion.- 4.4.1 Use of a Package to Surround the Task.- 4.4.2 Distinction Between Task Types and Tasks.- 4.4.3 Resetting and Terminating the Terminal Driver.- 4.4.4 Interfacing to Devices.- 5. Table Creation and Table Searching.- 5.1 Description.- 5.2 Implementation.- 5.3 Program Text.- 5.4 Discussion.- 5.4.1 Use of The Package.- 5.4.2 Use of the Search Function.- 5.4.3 Use of Packages.- 5.4.4 The Type of the Entries in the Table.- 5.4.5 Use of a Private Type for the Pointers to the Table.- 5.4.6 Nesting a Generic Package Within a Generic Package.- 5.4.7 String Comparisons.- 5.4.8 Use of Integers in Find.- 6. Solution of Laplace's Equation with Several Ada Tasks.- 6.1 Description.- 6.2 Implementation.- 6.3 Program Text.- 6.3.1 A Protected Counter Task Type.- 6.3.2 Parallel.Relaxation Procedure.- 6.4 Discussion.- 6.4.1 Use of Shared Variables.- 6.4.2 Updates of Shared Variables From Registers.- 6.4.3 Generics and Generic Instantiation.- 6.4.4 Scheduling of Ada Tasks Onto Processors.- References.

Studies in Ada Style

We develop conventions to be followed when creating abstract data types in Ada. These conventions define a discipline for the use of initialization, finalization, assignment, private types, and generic packages in writing transportable and interchangeable abstract data types. We illustrate the conventions by presenting several implementations of an Ada package for a typical abstract data type, Set. The implications of these conventions for compiler implementation are discussed.

A methodology for programming abstract data types in Ada

This paper describes the final phase of an Ada compiler which produces code for the VAX 11/780 running the Unix operating system. Problems encountered in the implementation of subprogram calls, parameter passing, function return values, and exception handling and discussed and their solutions outlined.An underlying requirement for the code generator has been speed of implementation consistent with being a test bed for an Ada implementation. To accomplish this, a common model for the target environment has been assumed. The assumptions include: the VAX is a stack machine, a single address space is used, only the general case is implemented (no optimization of special cases), the hardware does as much work as possible, run time routines for lengthy code sequences are acceptable, and the conventions given in the VAX architecture, hardware, and software manuals are used.The code generator has been running on PDP-10 with Tops-10, producing a VAX assembly language source program as output. it has been available to local users since the beginning of 1980.

Jonathan Rosenberg

Papers

Introduction to the First Edition

Introduction to the Second Edition

Studies in Ada Style

A methodology for programming abstract data types in Ada

An Ada code generator for VAX 11/780 with Unix