A framework for assertion-based debugging in constraint logic programming

We propose a general framework for assertion-based debugging of constraint logic programs. Assertions are linguistic constructions which allow expressing properties of programs. We define assertion schemas which allow writing (partial) specifications for constraint logic programs using quite general properties, including user-defined programs. The framework is aimed at detecting deviations of the program behavior (symptoms) with respect to the given assertions, either at compile-time or run-time. We provide techniques for using information from global analysis both to detect at compile-time assertions which do not hold in at least one of the possible executions (i.e., static symptoms) and assertions which hold for all possible executions (i.e., statically proved assertions). We also provide program transformations which introduce tests in the program for checking at run-time those assertions whose status cannot be determined at compile-time. Both the static and the dynamic checking are provably safe in the sense that all errors flagged are definite violations of the specifications. Finally, we report on an implemented instance of the assertion language and framework

Combined static and dynamic assertion-based debugging of constraint logic programs

We propose a general framework for assertion-based debugging of constraint logic programs. Assertions are linguistic constructions for expressing properties of programs. We define several assertion schemas for writing (partial) specifications for constraint logic programs using quite general properties, including user-defined programs. The framework is aimed at detecting deviations of the program behavior (symptoms) with respect to the given assertions, either at compile-time (i.e., statically) or run-time (i.e., dynamically). We provide techniques for using information from global analysis both to detect at compile-time assertions which do not hold in at least one of the possible executions (i.e., static symptoms) and assertions which hold for all possible executions (i.e., statically proved assertions). We also provide program transformations which introduce tests in the program for checking at run-time those assertions whose status cannot be determined at compile-time. Both the static and the dynamic checking are provably safe in the sense that all errors flagged are definite violations of the pecifications. Finally, we report briefly on the currently implemented instances of the generic framework

Inference with Constrained Hidden Markov Models in PRISM

A Hidden Markov Model (HMM) is a common statistical model which is widely used for analysis of biological sequence data and other sequential phenomena. In the present paper we show how HMMs can be extended with side-constraints and present constraint solving techniques for efficient inference. Defining HMMs with side-constraints in Constraint Logic Programming have advantages in terms of more compact expression and pruning opportunities during inference. We present a PRISM-based framework for extending HMMs with side-constraints and show how well-known constraints such as cardinality and all different are integrated. We experimentally validate our approach on the biologically motivated problem of global pairwise alignment

Using global analysis, partial specifications, and an extensible assertion language for program validation and debugging

We discuss a framework for the application of abstract interpretation as an aid during program development, rather than in the more traditional application of program optimization. Program validation and detection of errors is first performed statically by comparing (partial) specifications written in terms of assertions against information obtained from (global) static analysis of the program. The results of this process are expressed in the user assertion language. Assertions (or parts of assertions) which cannot be checked statically are translated into run-time tests. The framework allows the use of assertions to be optional. It also allows using very general properties in assertions, beyond the predefined set understandable by the static analyzer and including properties defined by user programs. We also report briefly on an implementation of the framework. The resulting tool generates and checks assertions for Prolog, CLP(R), and CHIP/CLP(fd) programs, and integrates compile-time and run-time checking in a uniform way. The tool allows using properties such as types, modes, non-failure, determinacy, and computational cost, and can treat modules separately, performing incremental analysis

Exploiting Term Hiding to Reduce Run-time Checking Overhead

One of the most attractive features of untyped languages is the flexibility in term creation and manipulation. However, with such power comes the responsibility of ensuring the correctness of these operations. A solution is adding run-time checks to the program via assertions, but this can introduce overheads that are in many cases impractical. While static analysis can greatly reduce such overheads, the gains depend strongly on the quality of the information inferred. Reusable libraries, i.e., library modules that are pre-compiled independently of the client, pose special challenges in this context. We propose a technique which takes advantage of module systems which can hide a selected set of functor symbols to significantly enrich the shape information that can be inferred for reusable libraries, as well as an improved run-time checking approach that leverages the proposed mechanisms to achieve large reductions in overhead, closer to those of static languages, even in the reusable-library context. While the approach is general and system-independent, we present it for concreteness in the context of the Ciao assertion language and combined static/dynamic checking framework. Our method maintains the full expressiveness of the assertion language in this context. In contrast to other approaches it does not introduce the need to switch the language to a (static) type system, which is known to change the semantics in languages like Prolog. We also study the approach experimentally and evaluate the overhead reduction achieved in the run-time checks.Comment: 26 pages, 10 figures, 2 tables; an extension of the paper version accepted to PADL'18 (includes proofs, extra figures and examples omitted due to space reasons

Dependence-Based Source Level Tracing and Replay for Networked Embedded Systems

Error detection and diagnosis for networked embedded systems remain challenging and tedious due to issues such as a large number of computing entities, hardware resource constraints, and non-deterministic behaviors. The run-time checking is often necessitated by the fact that the static verification fails whenever there exist conditions unknown prior to execution. Complexities in hardware, software and even the operating environments can also defeat the static analysis and simulations. Record-and-replay has long been proposed for distributed systems error diagnosis. Under this method, assertions are inserted in the target program for run-time error detection. At run-time, the violation of any asserted property triggers actions for reporting an error and saving an execution trace for error replay. This dissertation takes wireless sensor networks, a special but representative type of networked embedded systems, as an example to propose a dependence-based source-level tracing-and-replay methodology for detecting and reproducing errors. This work makes three main contributions towards making error detection and replay automatic. First, SensorC, a domain-specific language for wireless sensor networks, is proposed to specify properties at a high level. This property specification approach can be not only used in our record-replay methodology but also integrated with other verification analysis approaches, such as model checking. Second, a greedy heuristic method is developed to decompose global properties into a set of local ones with the goal of minimizing the communication traffic for state information exchanges. Each local property is checked by a certain sensor node. Third, a dependence-based multi-level method for memory-efficient tracing and replay is proposed. In the interest of portability across different hardware platforms, this method is implemented as a source-level tracing and replaying tool. To test our methodology, we have built different wireless sensor networks by using TelosB motes and Zolertia Z1 motes separately. The experiments\u27 results show that our work has made it possible to instrument several test programs on wireless sensor networks under the stringent program memory constraint, reduce the data transferring required for error detection, and find and diagnose realistic errors

Practical Run-time Checking via Unobtrusive Property Caching

The use of annotations, referred to as assertions or contracts, to describe program properties for which run-time tests are to be generated, has become frequent in dynamic programing languages. However, the frameworks proposed to support such run-time testing generally incur high time and/or space overheads over standard program execution. We present an approach for reducing this overhead that is based on the use of memoization to cache intermediate results of check evaluation, avoiding repeated checking of previously verified properties. Compared to approaches that reduce checking frequency, our proposal has the advantage of being exhaustive (i.e., all tests are checked at all points) while still being much more efficient than standard run-time checking. Compared to the limited previous work on memoization, it performs the task without requiring modifications to data structure representation or checking code. While the approach is general and system-independent, we present it for concreteness in the context of the Ciao run-time checking framework, which allows us to provide an operational semantics with checks and caching. We also report on a prototype implementation and provide some experimental results that support that using a relatively small cache leads to significant decreases in run-time checking overhead.Comment: 30 pages, 1 table, 170 figures; added appendix with plots; To appear in Theory and Practice of Logic Programming (TPLP), Proceedings of ICLP 201

Abstract verification and debugging of constraint logic programs

The technique of Abstract Interpretation [13] has allowed the development of sophisticated program analyses which are provably correct and practical. The semantic approximations produced by such analyses have been traditionally applied to optimization during program compilation. However, recently, novel and promising applications of semantic approximations have been proposed in the more general context of program verification and debugging [3],[10],[7]